Scientific Evolution LLS Services Catalog v5.0 (2020)

QUANTITATIVE
Learning & Tactical Performance Center
V5
MATHEMATICS • ANALYSIS • MODELING • SIMULATION • AUDITING
modeling data, creating knowledge
High Performance Analytics
It's not about being the best, it's about being better than you were yesterday

Scientific Evolution Sàrl – Quant. Learning & Performance Center for High-Potentials
info@scientific-evolution.com – www.scientific-evolution.com
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Contents
re you an individual or a team wanting to get exposed to some of the major quantitative
techniques and looking for a customizable bachelor, master or PhD advanced analytics level
program? As a “HiP” you want to deeply understand mathematical analysis and modeling tools?
Because science is the worldwide intensive source of innovation since more than 300 hundred years,
this catalog will perhaps help you to find solutions to the specific needs of your company and to keep and
develop key talent!
Scientific Evolution Sàrl wish in a near future to be a leader in Quantitative Scientific Management with
a comprehensive range of open enrollment “quant” seminar programs, all aimed at the real needs of
today's employees (especially high-potentials, aka HiPos) and customer's expectations. Passionate about
our business, we believe in what we do and we take pleasure in doing it!
Introduction
When Science meet Management ............................................................................................................2
Quant Skills..............................................................................................................................................5
Information...............................................................................................................................................8
Seminars
IDTT01: Probabilities.............................................................................................................................9
IDTT02: Descriptive statistics................................................................................................................11
IDTT03: Parametric inferential Statistics (hypothesis testing) ..........................................................14
IDTT04: Non-parametric Statistics.......................................................................................................17
IDTT05: Quantitative Forecasting and Time series analysis..............................................................19
IDTT06: Quantitative Quality control (industrial statistics) ..............................................................22
IDTT07: Quantitative Finance...............................................................................................................25
IDTT08: Quantitative Decisioneering ...................................................................................................29
IDTT09: Quantitative Data analysis (data mining/machine learning) ..............................................31
IDTT10: Quantitative Failure Modes and Effects Analysis................................................................34
IDTT11: Quantitative Project Management (Statistical Thinking for Managers)...........................36
IDTT12: Quantitative Optimization techniques ..................................................................................38
IDTT13: Quantitative Supply chain......................................................................................................41
IDTT14: Quantitative Insurance techniques........................................................................................43
IDTT15: Engineering Mathematics.......................................................................................................45
Prices..........................................................................................................................................................47
When you can measure what you are speaking about and express it in numbers, you know something
about it; but when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory
kind. Lord Kelvin
A

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When Science meets Management
he further you go in your company's business system, the greater the responsibilities that you must
take on, and the more visible will the results for which you are accountable. And these
responsibilities and this visibility will occur in the context of ever-increasing complexity. The
quantitative stream is an integral part evolution for all activities to understand and solve/improve complex
situations using Master/PhD state of the art scientific tools and processes based on extremely useful and
rigorous REX (return on experience).
Scientific Evolution Sàrl 100% focused on Quantitative Scientific Management with a comprehensive
range of open enrollment quant seminar programs, all aimed at the real needs of today's employees
(especially high-potentials), a radical high level approach to the management of organizations using an
efficient proven method: math's analysis and scientific methodologies for project management to resolve
real business issues and analyze strategic challenges!
The ability to reason in an organized and mathematically correct manner is essential to solving critical
business problems, and helping employees to improve their reasoning skill is also one of our primary
goals.
We hope that our approach will transform the way your company executes the revenue generating process
in a wide variety of complex problems in business, government, health care, education and many others
through his scientific strategy for each hard skill or soft skill high-potential employee.
T

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Others say it, We prove it!
Even though many business decisions can be made intuitively, based on hunches and experience, there
are more and more situations in which quantitative models can assist. Some managers, however, fear that
the use of a formal analysis process will reduce their decision-making power. Others fear that it may
expose some previous intuitive decisions as inadequate. Still others just feel uncomfortable about having
to reverse their thinking patterns with formal decision making. These managers often argue against the
use of quantitative methods. Many action-oriented managers do not like the lengthy formal decision-
making process and prefer to get things done quickly. They prefer “quick and dirty” qualitative
techniques that can yield immediate results. Once managers see some quick results of quantitative
technics that have a substantial payoff, the stage is set for convincing them that quantitative analysis is a
beneficial tool.
When you participate to our quantitative seminars, you will:
•learn through real-life case studies with real accessible tools and practical research material
•learn to turn numbers into real scientific knowledge
•learn from experts, all researchers or authors
•choose to work on a specific challenge related to your company
•share knowledge with other high-potentials skills through active class discussions
•gain access to our website (Forum, Wiki, MS Excel Spreadsheets, Scripts/Codes, Lectures, Videos)
These elements make naturally of Scientific Evolution Sàrl your ideal partner for all trainings of very
high level of complexity and rigor.
Memorization is important, however understanding is even more important.
Theory
• Purpose
• Hypothesis
• Assumptions
• Limitations
• Proofs
Applications
• Finance
• Management
• Supply chain
• Quality
• R&D
• Forecasting
• …
Discussions
• Processes
• Implementation
• Business cases
• Critics
• Lectures
• Traps
• Tips & Tricks

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State of the art
Mathematic is the most fascinating and satisfying subject to research and to learn. No matter how much
you read, and how well informed you are, there is nothing comparable to deeply understand the
mechanisms of applied science to gain the managerial insights that are necessary for succeeding in the
future and mastering the present. We share our passion for all branches of mathematics and our diverse,
high-quality seminars list reflects this.
We offer real learning approach with powerful professional tools and methodologies align with the needs
of your daily business subject to uncertainties. Our program gives you a grounding in core disciplines
such as quantitative marketing, quantitative finance, quantitative project management, quantitative quality
control, quantitative process management and decisioneering. This approach enables you to look at
various challenging issues from a different perspective and dig out gold of your company's data,
independent of the sector you are situated in.
For this purpose, we are constantly updating our programs keeping them relevant, and bringing
innovative material to the classroom. By investing the necessary time to work closely with key clients and
understand their needs, we always offer tailored and comprehensive services that addresses your specific
needs as accurately as possible.
Participants should come with an open mind to learn from thought leaders and peers, to build efficient
business and sustainable business environment. Also, we will discuss how scientific methodology has
increase knowledge and comfort in all fields.
Quantitative techniques and tools provide the executive with scientific basis for decision making and
enhance the abilities to make long range plans and to solve some of the many problems of running a
business and industry with greater efficiency and confidence. Quantitative techniques and tools are
instead nothing more than a high-quality tool for the professional involved in the high-level business
areas and is not a guarantee of specific results! There are number of advantages in using mathematical
models:
1. Models can accurately represent reality (if properly formulated)
2. Models can help a decision maker formulate problems
3. Models can give us insight and information
4. Models can save time and money rather than trying for real
5. A model may be the only way to solve some large or complex problems in a timely fashion
6. A model can be used to communicate problems and solutions to others
Everything should be made as simple as possible, but not simpler.
Albert Einstein

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Quant skills
Quant skills and High-Potentials expect from their employer more development, support, and investment
– and they get it. Their also receive more development opportunities – such as special assignments and
seminar as well as mentoring and coaching from senior leaders – than other employees to keep them in
the organization. The extra investment from their employer is one reason why being formally recognized
as a Quant skill and also a High-Potential is considered important to face a more complex range of
challenges.
Because High-Potentials are that illustrious group of individuals who are the rising stars in your
organization they have to receive differentiated seminar that often includes additional options for "higher
dollar" seminar to take on greater risks and responsibilities. Our seminars prepare your high-potentials
skills in three ways for keeping them engaged so you can retain them:
•Deepening understanding of fundamentals and advanced quant techniques (finance, forecasting,
supply chain, quality control, optimization, etc.).
•Providing a solid foundation in the principles of quant techniques and a unique opportunity for self-
development and for your company management methods.
•A learning approach that is highly informal and interactive with thought-provoking assignments, and
real-life case discussions.
When an organization sends us a Quant or High-Potential, it gains a more confident, competent business
leader:
•To manage change rigorously and drive results in a scientific way.
•Thanks to his heightened curiosity about the world and the possibilities it holds.
•Through his aptitude to turn ideas into actions and measure their efficiency scientifically.

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DMAIC Training process
We aim to be as transparent as possible with your projects by providing very detailed contents of all
levels: business-oriented, with varying intensity and based if possible, on a statistical analysis of your
business. Our main goal is to provide highly tailored solution to minimize your financial and time
investment.
We apply the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) approach for building
your customize trainings and to be sure that there are really useful for your employees:
• Define a detailed specification book and research of (Critical To Quality) CTQ points
• Measure knowledge before training with skills assessments tests and interviews
• Analyze with statistics (when possible) the needs and the level of company employees by profession
• Improve skills with appropriate training prepared using the previous DMA steps.
• Control and report the short- and long-term return on investment and performance
And for sure you can follow our trainings or seminars in our classrooms, in your office building (if the
meeting rooms are adapted) or by using e-learning technologies (webcasts, videos).
To be sure our services are successful and sustainable, we need to understand and have a clear picture on
the details of your core business and implicit variables on your environment!
•Planning simulations?
•Budget simulations?
•Time management?
•Decisioneering?
•Data analysis (data mining)?
•Forecasting?
•Controlling?
•Statistical process control?
•Failure probabilities?
•Financial simulations?
•Risk convolution?
•Optimization?
•Stress tests?
•Heuristics?
•Working methodologies?
•….
•Who is in charge of your
statistics for data analysis and
forecasting?
•What level of statistics are you
using today (undergraduate,
postgraduate…)?
•Are you doing projects and
financial simulations?
•Who is in charge in statistical
process control and
optimization?
•Do you calculate failures
probabilities of your products
and services?
•Do you know how real science
has improved technologies and
working methodologies?
•Identify your quants
•Define your conditions and
constraints
•Pass admission test
•Interviews
•Plan and design an efficient
custom program that have
lasting impact
•Transfer you business cases to
the training center
•Train on real world examples
with experts with real tool
•Pass post-test
•Measure efficiency (ROI)

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What's new
At Scientific Evolution Sàrl we always put quality first. By investing the
necessary resources to study international norms and standards and last
scientific publication, we can offer high level tailored services with
demonstrated results:
• With a radical approach
• With passionate and innovative speaker, trainers and experts
• With state-of-the-art techniques
• With high level business tools
Our distinctive portfolio of open and seminars caters to individuals, teams and organizations. To remain
at the forefront of quant education, we update once per year our programs keeping them relevant and
assess our company organization and services using EFQM (European Foundation for Quality
Management) scale value.
Top 5 benefits:
Most education centers add undergraduates' trainings about social responsibility, communication, ethics,
computing and management methodologies. At Scientific Evolution Sàrl this is a part of the assumed
curriculum because we think that only a deeper understanding can bring people to have better ideas.
Our Credentials include PhDs in Statistics and Engineer grade in Nuclear Physics, and authorship of
worldwide known textbooks and videos about statistics, finance, mechanics and well-known data analysis
softwares.
Quant trainings with proofs
Real world oriented problems
BMD-level tools and techniques
Scientific methodologies
Valuable return on investment

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Information
For all seminars:
▪ Subjects are all detailed with accessible undergraduate or postgraduate math proofs and real-world business
examples
▪ A four-hour test with an interview is strongly recommended before and after the seminar (ISO 10015:1999,
EduQua:2004, AFNOR X50-756)
▪ Admission decisions are based using a combination of factors, including academic degrees and records, the
statement of purpose, letters of recommendation, test scores, and relevant work experience
▪ There is a delay of three months minimum between your request and the first seminar date for quality
purposes
▪ We strongly recommend four weeks between each seminar session (trainees can digest, apply and review
new knowledge between each session: see Forgetting curve on Wikipedia)
▪ We also strongly recommend to split the whole training duration in sessions of four hours occurring at the
beginning of the week (avoid Friday)
▪ All suggested durations are indicated for a group of six attendees who satisfies prerequisites
▪ You can book also Saturdays and Sundays for seminars dates and customize seminars around a corporate
team task in a neutral setting with our support as a launch pad for a new project
▪ After the seminar, trainees can follow for free "beta" presentations to update their skills
▪ We strictly respect ISO 9001:2008, ISO 10015:1999 and EduQua:2004 processes for our seminars
For dates or any other information (seminars details, prices, tailor-made seminars, consulting services,
suggestions, processes, place reservation, etc.) contact: info@scientific-evolution.com. After you have sent
your request a consultant will contact you in order to schedule an appointment for an initial consultation. There
may be a waiting period of several days or more during times when we receive many requests.

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IDTT01: Probabilities
AIM AND OBJECTIVE
The aim of this seminar is to define rigorously and
clearly all fundamentals concepts used in all
quantitative statistical techniques and tools. The
objective will be to open the doors to bachelor level
concepts and accurate trainee's data analysis skills in
sales, marketing, supply chain, quality control,
finance, surveys, measures, laboratories, human
resource, insurance, etc. This seminar is very
important to be sure that trainees will deeply
understand assumptions and construction of
quantitative tools.
TARGET AUDIENCE
Anyone who wants to acquire a solid background in
statistical thinking or people with a (E)MBA, CFA,
FRM, CAIA, CII, CAPM/PMP or 6 Master Black
Belt certificate who wish to refresh their knowledge
and deeply understands limitations and hypothesis in
further seminars.
PREREQUISITES / ADMISSION CRITERIA
A four-hour admission test with a one-hour
interview is strongly recommended before and after
the seminar to test mathematics and business skills.
Attendees must have at least an undergraduate
degree or global equivalent if the seminar is
requested with mathematical proofs.
SUGGESTED DURATION
The whole program is on 4 days (7 hours per day)
without proofs (WhP) and on 6 days with proofs
(WP). It can be customized on needs (available in
minutes next to each module conforming to AFNOR
NF X50 756) including or not an assessment test
(open book exam).
ORGANIZATION
The sessions occur in a classroom with computers
installed and up-to-date tools, a beamer and a
flipchart/whiteboard or blackboard. Cellphones and
mails are forbidden during the seminar.
ATTENDEES
Maximum 50/Minimum 1
CERTIFICATION
An e-Certificate with a supplement will be awarded
to each participant who has successfully attended at
least 80% of the seminar and pass the exam.
PEDAGOGICAL METHOD
You will learn from relevant case studies, open
sessions to discuss your issues, group or individual
computer-based exercises, videos and simulations
and paper readings.
This instructor-led seminar is based on business
case exercises related to the attendees' professional
needs and ~95% is practical when asked without
mathematical proofs, otherwise the practical part is
~66%. The attendees may bring (recommended)
their professional data and issues to work on.
TRAINER(S)
1-2 BMD physicists or mathematicians
TOOLS
MS Office Excel, Open Calc, Minitab, MSBNX,
Tanagra, SPSS, R or any other spreadsheet/stat like
software. Laptops or computers with VirtualPC or
VMware player are strongly recommended.
BOOK
Elements of Applied Mathematics for Engineers
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
This complete and detailed book frees participants
from the distracting task of note taking.
AVAILABLE SEMINAR LANGUAGES
Material and discussion language can be in French,
English or German depending on the audience.
CONTACT
info@scientific-evolution.com
FUNCTIONAL LEVEL
Business Analyst, Financial/Insurance/Treasury
Analyst, Engineer, Project Manager/Analyst,
Clinician, Laboratory Assistant, Team Leader, Dpt.
Leader, Quality Manager/Analyst, CEO, CFO,
CRO, Human Resource Manager, Students, etc.
DIFFICULTY / BLOOM'S TAXONOMY LEVEL
Bachelor (Level 3/6)/Evaluations (Level 6/6)
EXAM / TEST
A four-hour test is strongly recommended before
and after the seminar to assess trainee's knowledge
and performance.
PRICE / DATES
For estimate prices refer to page 45
Dates on demand
Keywords: probabilities, bayesian, permutations, combination, seminar, course, training

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Detailed seminar program =
Goal Description ~Duration [min.]
01 Introduction 30
02 Tools and implementation 10
03 About the rigor level 10
04 Statistical thinking 20
05 Axiom of probabilities 30
06 Conditional (Bayesian) prior & posterior discrete probabilities WP 145/WhP 60
07 Conditional (Bayesian) prior continuous probabilities
(conjugate bayesian prior to Normal and Binomial distributions)
WP 80/WhP 30
08 Conditional mean based on Pareto distribution (Analytical & Monte Carlo) WP 160/WhP 60
09 Iterated conditional mean WP 20/WhP 10
10 Bayesian network WP 90/WhP 60
11 Likelihood and left, right, interval censored likelihood WP 120/WhP 80
12 Fisher Information Matrix (with score function and score vector) WP 80/WhP 20
13 Markov chains WP 120/WhP 90
14 Permutations without repetitions WP 30/WhP 20
15 Permutations with repetitions WP 30/WhP 20
16 Arrangements with repetitions WP 30/WhP 20
17 Arrangements without repetitions WP 60/WhP 20
18 Combinations without repetitions 15
19 Combinations with repetitions WP 40/WhP 20
20 Probability generating function WP 70/WhP20
21 Entropy and Kullback-Leibler divergence WP 90/WhP20
22 Seminar conclusion and feedback 30
23 Open Book Exam (on demand only) 240
Good to know: This seminar will help you to understand important models used in insurance and credit risk (like the Cox
Proportional Hazard, Kaplan-Meier models, Credit Suisse First Boston CreditRisk+) and how some Internet search and
translation engines work and how the biggest worldwide supermarkets analyze customer behaviors with Markov chains. But
above all you will see and study typical errors of reasoning occurring in business and industrial practice. Depending on the
country and university or engineering school, this seminar outline corresponds to an undergraduate or Bachelor level.

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IDTT02: Descriptive statistics
AIM AND OBJECTIVE
The aim of this seminar is to study rigorously and
clearly all fundamentals and highly critical concepts
used in all quantitative statistical bachelor level and
further techniques and tools. The objective is to be
able to understand how to apply and the advantages
of using graduate statistical level tools in daily basis
business.
TARGET AUDIENCE
Anyone who wants to acquire a solid background in
statistical thinking or people with a (E)MBA, CFA,
FRM, CAIA, CII, CAPM/PMP or 6 Master Black
certificate who wants to go much deeper in statistics
or refresh their knowledge.
degree or global equivalent to the content of IDTT01
if the seminar is requested with mathematical proofs.
SUGGESTED DURATION
(open book exam).
ORGANIZATION
installed and up-to-date, a beamer and a
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
MS Office Excel, Open Calc, Minitab, Tanagra,
SPSS, R or any other spreadsheet/stat like software.
Laptops or computers with VirtualPC or VMware
player are strongly recommended.
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: indicators, average, standard deviation, percentiles, survey analysis, seminar, course, training

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01 Introduction 30
02 Purpose and limitations of statistics (statistical thinking) 30
05 About ISO standards for statistics 15
06 How to communicate statistics 10
07 Population and sample 20
08 Class interval and Laplace smoothing 15
09 Measure (punctual) of location and dispersion 45
10 Arithmetic average (mean) 15
11 Geometric average (mean) 20
12 Moving and pondered average (weighted arithmetic mean) 25
13 Percentiles (median, quartile, etc.) and their use for outliers detection in the
case of skewed or non-skewed distributions
WP 75/WhP 25
14 Mode(s) vs Median vs Average 5
15 Box and Whisker plots 25
16 Standard Deviation/Variance (Pearson Stdev) and semi-Variance 20
17 Average and Standard deviation properties WP 70/WhP 25
18 Huygens relation WP 10/WhP 5
19 Average of the absolute deviation 10
20 Standard error (of the mean) WP 30/WhP 10
21 Coefficient of variation 5
22 Finite population correction factor (fpc) WP 60/WhP 10
23 Covariance WP 25/WhP 15
24 Covariance matrix and nearest correlation matrix problem WP 15/WhP 20
25 Correlation coefficient (Pearson), partial correlation and predicted correlation WP 50/WhP 20
26 Braford Hill criterion 15
27 Outliers analysis WP 70/WhP 15
28 Diversity index WP 90/WhP 15
29 Discrete and continuous mean and standard deviation WP 15/WhP 10
30 Jensen's inequality WP 30/WhP 10
31 Distribution and density function definition 20
32 Density plot and class interval (Sturges rule) WP 40/WhP 20
33 Empirical distribution function (EDF) and fundamental postulate 15
34 Discrete and continuous uniform distribution WP 40/WhP 20
35 Triangular distribution (three-point estimates) WP 40/WhP 20
36 Bernoulli distribution WP 35/WhP 20
37 Geometric distribution WP 30/WhP 20
38 Binomial distribution WP 30/WhP 20
39 Negative binomial distribution WP 50/WhP 20

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38 Hypergeometric distribution WP 60/WhP 20
39 Poisson distribution WP 50/WhP 20
40 Gauss-Laplace/Normal distribution WP 90/WhP 20
41 Henry and Q-Q plot 40
42 Stability of a distribution WP 60/WhP 15
43 Bivariate Normal Distribution WP 40/WhP 15
44 Log-normal distribution WP 60/WhP 20
45 Weibull distribution WP 50/WhP 20
46 Type I Pareto distribution (fractal nature) WP 70/WhP 20
47 Exponential distribution WP 60/WhP 20
48 Cauchy distribution WP 50/WhP 20
49 Beta distribution & Beta distribution of the first kind (two-points estimate) WP 110/WhP 20
50 Gamma and Generalized Gamma distribution (with Erlang connection) WP 70/WhP 20
51 Chi-squared (Pearson) and noncentral chi-squared distribution 40
52 Student distribution WP 90/WhP 20
53 Fisher-Snedecor distribution WP 60/WhP 20
54 General folded distribution and half-normal distribution WP 50/WhP 20
55 Benford distribution WP 40/WhP 20
56 Population and sample Skewness and Kurtosis (shape parameters) WP 50/WhP 10
57 Heavy-tailed, fat-tailed and thin-tailed distribution WP 20/WhP 10
58 Markov's inequality WP 25/WhP 15
59 Bienaymé-Tchebychev's inequality WP 25/WhP 15
60 Weak law of large numbers (fundamental theorem of Monte Carlo) WP 50/WhP 15
61 Characteristic function WP 180/WhP 30
62 Central limit theorem WP 420/WhP 15
63 Normal approximations WP 60/WhP 15
64 Biased and non-biased location and dispersion measures WP 180/WhP 30
65 Variance estimation for sample quantiles WP 40/WhP 10
66 Propagation of simple absolute/relative and statistical errors WP 50/WhP 25
Good to know: This seminar is very useful to understand how to analyze and use important theoretical models in advanced
finance, engineering, quality control and to avoid some typical errors of analysis in complex business simulations. Depending
on the country and university or engineering school, this seminar outline corresponds to a Bachelor or Master level.

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IDTT03: Parametric inferential statistics (hypothesis testing)
AIM AND OBJECTIVE
The aim of this seminar is to understand: when and
how parametric hypothesis testing is used, the
general concept of comparing a test statistic vs. an
acceptable risk value, the role the p-value takes in
the decision process, how parametric hypothesis
testing relates to practical problems and solutions,
how  and  risks relate to hypothesis testing. The
objective is to be able to understand how and when
to apply the power of hypothesis testing on a daily
business basis.
TARGET AUDIENCE
Anyone who wants to learn how to apply
fundamentals of parametric test hypothesis from
scratch or people with a (E)MBA, CFA, FRM,
CAIA, CII, CAPM/PMP or 6 Master Black
certificate who wants to go much deeper in statistics
or refresh their knowledge.
SUGGESTED DURATION
(open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
SPSS, R, Oracle or any other spreadsheet/stat like
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: statistics, test hypothesis, confidence interval, adjustment test, survey analysis, seminar, course, training

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01 Introduction 30
04 About ISO standards for statistics (ISO 10017:2003, ISO 3534:2006, ...) 15
05 Importance of NHST models assumptions 10
06 Some words on statistical tests types
(Distribution/Adequation tests, Location tests, Dispersion test, Correlation tests, Concordance tests, Interaction tests,
Equivalence tests, univariate or multivariate tests)
30
07 Fluctuation vs Confidence vs Tolerance vs Prediction vs Credibility Interval 10
08 p-value + large sample size issues and fallacies related to the power of tests 10
09 One sided or two-sided omnibus tests and post-hoc tests 15
10 Null and alternative hypothesis and p-value hacking 20
11 Type I (false positive)/Type II (false negative) errors (with MCS examples) 45
12 Power of a test ("a priori" and "observed power") 30
13 Hypothesis tests for the mean with known variance (Z test) and power test WP 40/WhP 25
14 Hypothesis tests for the mean with unknown variance (t test) and power test WP 40/WhP 25
15 Population size for mean confidence interval (power test @ 50%) 5
16 Hypothesis test for the difference of means with known/unknown variance WP 50/WhP 30
17 Hypothesis test for the ratio of two means (Fieller Theorem) WP 60/WhP 10
18 Hypothesis test for the standard deviation with known/unknown mean
(chi-square variance test)
WP 100/WhP 40
19 Effect sizes and equivalence tests (TOST test) WP 30/WhP 10
20 Poisson hypothesis tests for rare events (Poisson's test) WP 120/WhP 30
21 Binomial exact test WP 25/WhP 15
22 Hypothesis tests for a proportion/frequency (p-test, also called A/B testing) WP 35/WhP 15
23 Population size for proportion (power for p-test) WP 20/WhP 10
24 Test of equality of two proportions (two samples p-test)/Risk Difference and
Number Need to Treat
WP 25/WhP 15
25 Non-parametric bootstrapping inference technique (bagging) 40
26 Chi-squared test for goodness of fit WP 55/WhP 15
27 Chi-squared test for independence (Pearson's independence test) WP 40/WhP 15
28 Likelihood ratio test WP 40/WhP 10
29 Fisher's exact test WP 50/WhP 15
30 McNemar's test WP 50/WhP 25
31 Fisher's test for equality of variances WP 40/WhP 15
32 Independent homoscedastic/heteroscedastic two sample t-test (+Welch's t test) WP 50/WhP 30
33 Paired t-test WP 40/Whp 15
34 Balanced one-way fixed factor ANOVA (CBD: Complete Block Design) WP 120/WhP 30
35 Interactions and variance within/between (and intraclass correlation) 40
36 Balanced two-way fixed factors ANOVA with replication (Randomized CBD) WP 90/WhP 30

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37 Balanced fixed factors multifactorial ANOVA 20
38 Type I, II or III ANOVAs WP 60/WhP 20
39 Balanced one-way blocked ANOVA 20
40 Balanced fixed factor hierarchical (nested) ANOVA WP 70/WhP 30
41 Bonferroni and Fisher's correction for multiple tests (Inflation of the Type I
Error)
WP 40/WhP 15
42 Fisher's LSD, Tukey's and SNK ANOVA post-hoc test (honestly significant
difference tests)
WP 90/WhP 15
43 Latin Square ANOVA without repetitions WP 90/WhP 20
44 Greaco-Latin Square ANOVA without repetitions WP 110/WhP 20
45 Shapiro-Wilk Normality test (Ryan-Joiner approach) WP 50/WhP 20
46 Dixon's Q-test & Grubb's test outliers detection (Monte Carlo) 40
47 Cochran-C test for variance outliers detection WP 35/WhP 15
48 Test for periodicity (statistical description of Fourier coefficients) WP 390/WhP 30
Good to know: Some thirty years ago, it was only necessary to know about a dozen statistical tests in order to be a practicing
business analyst or R&D engineer. In recent years the number of tests has grown tremendously and, while modern books and
softwares carry the more common tests, it is often quite difficult for the end-user (manager, engineer) to know the assumptions
and interpretation practices of existing advanced statistical parametric tests. Depending on the country and university or
engineering school, this seminar outline corresponds to a undergraduate or Bachelor level

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IDTT04: Non-parametric statistics
AIM AND OBJECTIVE
The aim of this seminar is to understand non-
parametric statistics where no assumption is made
about the probability distribution of the population
under study. While most sample tests assume that
the parent population of the sample data is normally
distributed, the statistical methods of nonparametric
statistics are valid for any probability distribution
that the population may have. The objective is to be
able to understand how and when to apply the power
of bachelor level non parametric statistics and non-
parametric hypothesis testing on a daily business
basis in comparison with parametric techniques.
TARGET AUDIENCE
fundamentals of non-parametric statistics hypothesis
from scratch or people with a (E)MBA, CFA,
CAPM/PMP or 6 Master Black Belt certificate
who wants to go much deeper in statistics.
SUGGESTED DURATION
(open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
SPSS, R, Oracle or any other spreadsheet/stat like
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
Master (Level 4/6)/Evaluations (Level 6/6)
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: non-parametric statistics, non-parametric test hypothesis, non-parametric adjustment test, survey analysis

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01 Introduction 30
05 Parametric vs Non-parametric (distribution-free) statistics and common
misconceptions on non-parametric tests
15
06 Fundamentals of robust statistics moments (L-estimators, M-estimators) 30
07 Ranks distribution law WP 45/WhP 10
07 Distribution free confidence interval for percentiles WP 30/WhP 10
07 Spearman's rho correlation coefficient WP 75/WhP 20
08 Exact/Approximate Wilcoxon sum rank test for two independent equal size
samples
WP 140/WhP 20
09 Exact/Approximate Mann-Withney U sum rank test for two independent non
equal size samples
WP 90/WhP 25
10 Wilcoxon signed-rank test for one sample WP 40/WhP 20
11 Wilcoxon signed-rank test for comparing paired samples WP 30/WhP 20
12 Sign test WP 30/WhP 15
13 Mood's test WP 40/WhP 15
14 Wald–Wolfowitz runs test WP 120/WhP 10
15 One/Two sample Kolmogorov-Smirnov (Lilliefors approach) and Cramér-von
Mises goodness of fit tests
WP 95/WhP 25
16 Anderson-Darling goodness of fit test WP 85/WhP 25
17 Kernel density estimation (KDE) vs Histogram WP 80/WhP 20
18 Kernel regression WP 25/WhP 10
19 Bonferroni and Fisher's correction for multiple tests (Inflation of the Type I
Error)
WP 40/WhP 15
20 Levene's test or Brown-Forsythe test for equality (homogeneity) of variances 60
21 Kruskal-Wallis ANOVA post-hoc test WP 60/WhP 15
22 Friedman test (Friedman's ANOVA by ranks) WP 70/WhP 15
23 Extreme value theory (Hartley Constant) WP 50/WhP 15
24 Factorial correspondence analysis (FCA) 50
25 Simple non-parametric principal component analysis (PCA) WP 150/WhP 25
Good to know: Non-parametric statistic is a must have for complex analysis where the data are not necessarily Normal
distributed or symmetric. Depending on the country and university or engineering school, this seminar outline corresponds to a
Master or PhD level in finance, social or medical sciences.

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IDTT05: Quantitative Forecasting and Time series analysis
AIM AND OBJECTIVE
The aim of this seminar is to enhance the
understanding of business forecasting from an
applied perspective and how forecasts are actually
developed and utilized at bachelor level,
emphasizing modern statistical methods and
quantitative forecasting techniques. Specific
applications to business include forecasting sales,
production, inventory, macroeconomic factors such
as interest rates and exchange rates, and other
aspects of both short- and long-term business
planning.
TARGET AUDIENCE
fundamentals of forecasting bachelor level
techniques from scratch or people with a (E)MBA,
CFA, CAPM/PMP or 6 Master Black Belt
certificate who wants to go much more in business
behavior simulation.
SUGGESTED DURATION
(open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
MS Office Excel, Open Calc, Minitab, SPSS, R,
Python, Microsoft Power BI or any other
spreadsheet/stat like software. Laptops or
computers with VirtualPC or VMware player are
strongly recommended.
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
Analyst, Financial Reporting Officer, Engineer,
Project Manager/Analyst, Clinician, Team Leader,
Dpt. Leader, Quality Manager/Analyst, Marketing
Manager, CEO, CFO, CRO, Human Resource
Manager, Engineer, Students, etc.
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: time series, regression, gml, logistic, exponential smoothing, moving average, fourier transform

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01 Introduction 30
04 Definition of common errors indicators in deterministic time series analysis 20
05 Time series composition/decomposition (trend, seasonality, cyclicity, noise) 60
06 Autocorrelation coefficient and autocorrelograms WP 25/WhP 10
07 Deterministic vs Stochastic models 20
08 Simple moving average WP 20/WhP 15
09 Weighted moving average WP 20/WhP 15
10 Linear regression model with a single regressor (least squares method) WP 40/WhP 15
11 The Durbin-Watson NHST test for autocorrelation detection WP 30/WhP 10
12 Forward, Backward, Best subset (hierarchical) linear regression and sensitivity 30
13 Linear regression model with a single regressor forced to the origin (OLS) WP 20/WhP 10
14 Regression models with Z-scores (centered variables) for sensitivity analysis 30
15 Linear regression model with a single regressor (Gaussian approach) WP 280/WhP 45
16 Pearson correlation coefficient confidence interval and hypothesis test WP 65/WhP 20
17 Linear regression model with multiple regressors (ordinary least squares),
NNLS (non-negative least squares) and CLS (constrained least squares)
WP 130/WhP 30
18 Outlier vs influential points in regression and leverage score 30
19 ANOVA for simple and multiple linear regression (omnibus F-test and
variable importance)
WP 80/WhP 20
20 Fisher's lack-of-fit test WP 20/WhP 5
21 Type of residuals (normal, standardized, semistudentized, studentized, …) 30
22 DFIT (DifFerence In Fit) and Cook's distance (influential points) 30
23 Multicollinearity analysis with Variance Inflation Factor (VIF) WP 90/WhP 20
24 Linear regression with binary or dummy variables w/without interactions 30
25 Heuristic linear regression model with seasonal adjustment 40
26 Hierarchical, moderated multiple regression analysis WP 30/WhP 15
27 Non-linear regression by linearization or Taylor series expansion WP 260/WhP 80
28 Weighted Least Square regression (WLS) WP 60/WhP 15
29 Polynomial regression WP 40/WhP 20
30 Nonlinear regression (Gauss-Newton) WP 150/WhP 20
31 Binary logistic regression with scoring (propensity score) and also Lift/ROC
Curves and Sensitivity, Sensibility scores, F1 score, Log-Loss, relative
variable importance
WP 90/WhP 30
32 Multinomial logistic regression WP 60/WhP 15
33 Non censored least absolute deviation quantile regression WP 30/WhP 10
34 Generalized Linear Model: Normal Gaussian WP 60/WhP 20
35 Generalized Linear Model: Poisson WP 50/WhP 20
36 Generalized Linear Model: Binomial WP 50/WhP 20
37 Generalized Linear Model: Negative Binomial NB-2/NB-C WP 80/WhP 20

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38 Generalized Linear Model: Gamma WP 50/WhP 20
39 Measures of forecast accuracy 30
40 Models selection criteria (AIC, BIC, MSE, Mallow's Cp) WP 240/WhP 30
41 Exponential moving average (EWMA) ARIMA(0,1,1) WP 40/WhP 25
42 Brown's double exponential smoothing (BDES) WP 70/WhP 25
43 Holt's double exponential smoothing ARIMA(0,2,2) (additive model) WP 60/WhP 25
44 Holt's and Winter triple exponential smoothing (multiplicative model) WP 40/WhP 25
45 Principles of forecasting using Linear Minimal Mean Square Estimation
(LMMSE)
WP 30/WhP 5
46 Coston, Syntetos and Boylan intermittent demand forecasting models 30
47 About ETS (Error, Trend Seasonality) models 30
48 Simulate univariate Brownian motions (AR(1) or ARIMA(1,0,0)) 10
49 Univariate seasonal additive ARIMA: SARIMA WP 40/WhP 10
50 ARFIMA and SARFIMA fractional processes 20
51 Univariate ARCH-GARCH process WP 100/WhP 30
52 Vector Autoregressive Model (VAR) WP 85/ WhP 15
53 Fast Fourier transform for spectral analysis WP 330/WhP 35
54 Recurrent one-layer neural networks and Restricted Boltzmann machine WP 150/WhP 40
55 Use ex post forecast performance for back testing 10
56 Analyze forecast errors based on control charts 10
Good to know: Even if forecasting technics are subject to numerous conflicts in scientific papers, most C.E.O and C.F.O. of
Fortune 500 companies request their business managers to provide advanced statistical forecasts of the main corporate K.P.I.
Forecasting technics are also used a lot in quantitative finance for pricing and hedging. For these reasons this seminar provides
the basics that every advanced business manager, financial analyst or risk consultant has to know in the 21st
century.
Depending on the country and university or engineering school, this seminar outline corresponds to a Master or PhD level in
finance or supply chain.

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IDTT06: Quantitative Quality control (industrial statistics)
AIM AND OBJECTIVE
Many companies fail in quality management
practices because of missing quant skills. The aim of
this seminar is to understand how quantitative
quality control techniques can help organizations to
meet quality requirements, improve processes and
solve or anticipate performance problems. The
objective is to learn common bachelor level
operational techniques and tools needed to verify
requirements of quality.
TARGET AUDIENCE
Quality management seminars attract a diverse
audience, including quality control analysts
(certified quality engineer or not), industrial
production managers, lean engineers and operations
research analysts. Other potential attendees include
production engineers and product quality auditors or
anyone with an intellectual curiosity for quality
management.
degree or global equivalent to the content of
IDTT03+IDTT04 if the seminar is requested with
mathematical proofs.
SUGGESTED DURATION
(open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
MS Office Excel, Open Calc, Minitab, SPSS, R or
any other spreadsheet/stat like software. Laptops or
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
Business Analyst, Engineer, Clinician, Project
Manager/Analyst, Laboratory Assistant, Team
Leader, Dpt. Leader, Quality Manager/Analyst,
Students, etc.
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: gage r&r, capability, acceptance sampling, control charts, average run length, operating curve, upper control limit,
lower control limit, seminar, course, training

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01 Introduction 30
02 About cost of quality 10
06 Statistical thinking 20
07 How to communicate statistics 10
08 Defects per unit opportunity (DPO) 10
09 Defects per million opportunities (DPMO) 10
10 Rolled troughput yield with hypergeometric, Poisson and Normal distributions WP 30/WhP 15
11 Upper and Lower specification limits (USL/LSL) 10
12 Capability analysis under Gaussian distribution assumption (Cpk, Ppk, etc.) 15
13 Gauge capabilities (Cg, Cgk) 15
14 Short (instantaneous) vs Long (global) dispersion 20
15 Short term process capability and short-term deviation 5
16 Long term process capability and short-term deviation 5
17 Process target 10
18 Process capability index (within) and position bias WP 15/WhP 10
19 Upper and lower capability index (CPU/LPU) WP 20/WhP 5
20 Short term non centered capability WP 20/WhP 5
21 Defect Metrics PPM WP 35/WhP 20
22 Six Sigma quality level WP 60/WhP 40
23 Gage linearity and biased study (repeatability & reliability) WP 50/WhP 30
24 Gage R&R study (crossed) for continuous variables WP 70/WhP 40
25 Cronbach's alpha reliability WP 20/WhP 40
26 Orthogonal/Deming regression WP 60/WhP 20
27 Attribute gage study (analytical method) 50
28 Cohen's Kappa 40
29 Taguchi loss of quality function with target criteria WP 40/WhP 25
30 Control charts presentations 20
31 Control chart vs Run chart 5
32 Shewhart and WECO Rule 15
33 About USL/LSL, UCL/LCL, CL/T, ARL (type I error) and OC (type II error) 30
34 Identify thanks to ARL suspicious over quality indicators 15
35 Attribute control charts P/NP+Laney P WP 100/WhP 35
36 Attribute control charts C/U+Laney U WP 60/WhP 40
37 Variable control chart for individual values with specified limits 20
38 Variable control chart for individual values with mean and short standard dev. 20
39 Variable control chart with means and standard error WP 40/WhP 20
40 Variable control charts Sbar-S/Xbar-S WP 115/WhP 65

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41 Levey-Jennings control charts WP 30/WhP 10
42 Variable control charts Rbar-R/Xbar-R WP 90/WhP 30
43 Autocorrelated control charts I-MR X-bar (MR-(2) control chart) WP 70/WhP 30
44 Autocorrelated control charts I-MR MR WP 70/WhP 30
45 Autocorrelated control charts MA WP 50/WhP 30
46 Autocorrelated control charts CUSUM with V-Mask (Page-Hinkley charts) WP 70/WhP 30
47 Autocorrelated control charts Xbar-EWMA-R/Xbar-MA-EWMA WP 130/WhP 60
48 Frequency control charts FP WP 90/WhP 40
49 Frequency control charts G (rare events) WP 90/WhP 30
50 Frequency control charts T (rare events) WP 90/WhP 30
51 T2
Hotelling multivariate control chart (chi-2 approach) with error ellipse WP 120/WhP 30
52 Efficiency curve (operating characteristic curve) for X-bar and P control
charts
20
53 Statistical sampling 20
54 Simple, double or sequential acceptance sampling 15
55 Provider and customer risk or acceptance quality level (AQL) 20
56 Acceptance sampling by measure for a single tolerance with known variance WP 80/WhP 20
57 Parameters calculation based on AF-X06-023 20
58 Acceptance sampling by attribute based on hypergeometric and binomial distr. WP 130/WhP 40
59 Parameters calculation based on ISO 2859-1 20
60 Efficiency curve (operating characteristic curve) for sampling 20
61 Average Outgoing Quality (AOQL) 20
Good to know: The techniques that are studied in this seminar are especially useful if you are responsible in R&D for very
complicated machines whose failures are a risk for people life as for the company reputation (the N.A.S.A. and U.S. army use
these techniques!) or in the production on hundreds of millions of devices who require a high level of reliability. Depending on
the country and university or engineering school this seminar outline corresponds to a Master or PhD level in engineering.

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IDTT07: Quantitative Finance
AIM AND OBJECTIVE
You need to stay on top of economic and financial
tools and integrate them into your day-to-day
operations? Choose among financial alternatives for
a large investment project and deal with the risks
facing your company? In this seminar we will
examine the most useful financial bachelor level
concepts and review best-practice use of classical
finance techniques.
TARGET AUDIENCE
This program is suitable for people in Investment
banking, Project management, Business planning &
strategy, Private equity funds or commercial
banking. It is also ideal for CA, CFA, FRM, CAIA,
CIIA, MBA Finance and Commerce Graduates.
Attendees must have at least a graduate degree and a
good knowledge of linear algebra, differential
calculus, advanced statistics and Fourier transform if
seminar is requested with mathematical proofs.
SUGGESTED DURATION
(open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
MS Office Excel, Open Calc, @Risk, Tanagra,
SPSS, R, MATLAB, Python, Microsoft Power BI
or any other spreadsheet/stat like software. Laptops
or computers with VirtualPC or VMware player are
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
Business Analyst, Financial Analyst, Financial
Reporting Officer, Project Manager/Analyst, CEO,
CFO, CRO, Students, etc.
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: annuities, loans, depreciation, corporate finance, obligations, bonds, derivatives, value at risk, sharpe, markowitz,
brownian motion, fintech, capm, cml, sml, mwrr, twrr, dv01, dd, npv, enpv, irr, var, real estate, business valuation

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01 Introduction 30
04 Worldwide standards (CFA, FRM, CAIA, CIIA, Basel, RiskMetrics,
CreditRisk, ISO 10962, etc.)
20
05 Time and dates calculations (Civil, German, US, European systems) WP 50/WhP 30
06 Simple interest WP 15/WhP 10
07 Simple interest rate equivalence (rate of composed interest) and discount rate WP 15/WhP 10
08 Composed interest (future value vs actualized value) WP 20/WhP 10
09 Composed interest rate equivalence
(Compound Annual Growth Rate - CAGR)
WP 15/WhP 10
10 Geometric mean rate and Harmonic mean prices and rates WP 50/WhP 40
11 Effective, nominal and real interest rate WP 15/WhP 10
12 Continuous (instantaneous) interests/Period log Returns in discrete time WP 75/WhP 30
13 Post and praenumerando annuities WP 100/WhP 50
14 Indivis loan with deadline 20
15 Loan with constant payback WP 30/WhP 20
16 Indivis loan with fixed annuities WP 50/WhP 20
17 Global effective nominal rate 30
18 Cobb-Douglas model WP 50/WhP 20
19 Straight-line depreciation 20
20 Accelerated arithmetic depreciation (Sum-of-Years Digits) WP 40/WhP 20
21 Accelerated geometric depreciation (Declining Balance) WP 35/WhP 20
22 Return on investment (ROI) and Net present value & future value (NPV/NFV) WP 50/WhP 20
23 Internal rate of return (IRR) and Modified Internal rate of return (MIRR) 45
24 eNPV, eIRR (Monte Carlo) 40
25 Payback time 5
26 About modern portfolio theory 20
27 Principle of no arbitrage WP 30/WhP 10
28 Stock exchange tools and mechanism (ask, bid, spread, volatility, yield) 20
29 Shares, bonds, T-Bill, forwards, futures, contingent claim, options, stock-
options (definitions, yield curve, pricing, hedging, Cox-Ingersoll-Ross equivalence, ...)
WP 300/WhP 210
30 Bootstrapping and stripping a yield curve with bonds WP 50/WhP 20
31 Macauley's Duration and Modified Duration (DV01, DD, DVBP/PVBP, D*) WP 50/WhP 20
32 Durand's and Gordon-Shapiro's models (one stage DDM firm pricing) WP 50/WhP 20
33 Bonds loan with constant or non-constant rates and periods WP 40/WhP 20
34 Money weighted rate of return (MWRR) and Hardy's Formula WP 50/WhP 30
35 Time weighted rate of return (TWRR) 20
36 Markowitz efficient set portfolio diversification and frontier model
(Global Minimum Variance Portfolio (GMVP), Tangent Portfolio (TP) and Equally-weighted risk contribution
Portofolio (1/N))
WP 180/WhP 120
37 Sharpe efficient set portfolio diversification model WP 180/WhP 120

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38 Beta and alpha of a portfolio and portfolio risk alteration WP 40/WhP 20
39 Equal risk contribution portfolio (ie risk parity portfolio) WP 30/WhP 10
40 Black-Literman portfolio WP 50/WhP 20
41 Sharpe ratio (SR), Diversification ratio (DR), Tracking error (TE), CALMAR
ratio (with maximum drawdown) and corresponding optimized portfolios
WP 110/WhP 60
42 Capital Asset Pricing Model (CAPM) vs Fama-French three-factor Model 45
43 Fama-French and Carhart Multifactorial Asset Pricing Models 20
44 Capital Market Line (CML) WP 150/WhP 30
45 Security Market Line (SML) WP 80/WhP 20
46 Portfolio covariance and correlation analysis 30
47 Treynor-Black active portfolio management model WP 70/WhP 20
48 Brynson portfolio performance model analysis 40
49 Bachelier stochastic process model (basics of walk theory) WP 120/WhP 20
50 Wiener process and geometric Brownian motion WP 90/WhP 30
51 Brownian bridge WP 50/WhP 30
52 Fundamental option pricing equation 40
53 Itō drift-diffusion processes and Itō–Doeblin theorem with geometric Brownian WP 160/WhP 40
54 Option (Calls and Puts) pricing following Black & Scholes model introduction 20
55 Call-Put parity equation WP 35/WhP 25
56 Black & Scholes vanilla option pricing equation for non-dividend-paying or
paying-dividend underlying asset
WP 230/WhP 50
57 Binomia pricing model for vanilla options and Cox-Ross-Rubinstein limit WP 80/WhP 10
58 The "Greeks" for non-dividend-paying underlying asset WP 40/WhP 20
59 Fokker-Planck equation (Kolmogorov Forward) WP 60/WhP 15
60 Implied volatility vs Local volatility (Dupire model) vs Observed volatility WP 70/WhP 15
61 VIX volatility index WP 80/WhP 20
62 Black's model (76) for the pricing of options on futures 45
63 Parametric and non-parametric scaling or GARCH Value at Risk 30
64 Relative Value at Risk with or without Basel multiplier (BT inequality) WP 60/WhP 20
65 Bond based modified duration Value at Risk (delta VaR + delta gamma VaR) WP 20/WhP 5
66 Absolute Value at Risk WP 40/WhP 20
67 Historical Value at Risk 10
68 Variance-Covariance Value at Risk 15
69 Operational Value at Risk and Surplus Value at Risk 30
70 Credit Value at Risk 10
71 Standard & Poor's Credit Risk and Moody's VaR Equity Coverage table applications WP 40/WhP 20
72 Expected conditional Value at Risk shortfall for Gaussian loss distribution WP 40/WhP 10
73 Portfolio marginal Value at Risk WP 30/WhP 10
74 Non-parametric and parametric bootstrapping inference technique 40
75 Using bivariate Gaussian Copulas with or without Non-Gaussian Margins WP 170/WhP 80

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76 Roll's liquidity (1984) measure WP 60/WhP 20
77 Real estate (SC, CC, II, DR, MR, ... methods) and business valuation (KMV-
model)
WP 500/WhP 230
78 Uncertainty/Sensitivity analysis and tornado charts 40
Good to know: This seminar is especially interesting for people that want to understand the basics of how financial institutions
use theoretical models to build financial instruments that are supposed to cover risk investments or that are used to assess their
institution conforming to governmental financial risk standards (reserve requirements). You won't see in this training non-
mathematical investment strategies (or hard to formalized strategies). We will thus mainly focus on pricing, volatility, hedging
and investment strategies. Depending on the country and university or engineering school this seminar outline corresponds to a
Master or PhD level in Finance.

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IDTT08: Quantitative Decisioneering
AIM AND OBJECTIVE
The aim of this seminar is to be able to apply break-
even analysis, using both the graphic and algebraic
approaches, to evaluate new products, services and
decision alternatives using bachelor level heuristic-
based techniques. The objective is to provide advice
and guidance in analyzing information and risks and
to explain how choice-engineering can facilitate
decision-making and encourage everyone to follow
the right procedures and work collaboratively.
TARGET AUDIENCE
Analysts and business decision makers seeking
competency in the area of quantitative management
decisioneering.
Attendees must have at least a graduate degree and
an excellent knowledge of differential calculus and
statistics (IDTT01+02) if seminar is requested with
SUGGESTED DURATION
with or without proofs. It can be customized on
needs (available in minutes next to each module
conforming to AFNOR NF X50 756) including or
not an assessment test (open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
needs and ~95% is practical. The attendees may
bring (recommended) their professional data and
issues to work on.
TRAINER(S)
TOOLS
MS Office Excel, Open Calc, @Risk, TreeAge,
MakeItRational, Super Decisions or any other
decision tool like software. Laptops or computers
with VirtualPC or VMware player are strongly
recommended.
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
Business Analyst, Financial Analyst, Engineer,
Project Manager/Analyst, Marketing Manager,
Team Leader, Dpt. Leader, CEO, CFO, CRO,
Students, etc.
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: what-if, break-even, nash, pareto, cournot, laplace, markov, decision trees, seminar, course, training, analytical
management

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01 Introduction 30
04 About ISO decisioneering standards (ISO 31000:2009) 15
05 The role of models and sources of error in human decision making (behavior
bias, sunk costs, wisdom of crowds)
60
06 Deterministic what-if analysis 25
07 Condorcet's paradox in voting systems 20
08 Deterministic break-even analysis 25
09 Stochastic what-if analysis 60
10 Stochastic break-even analysis 30
11 Sensitivity analysis 30
12 Simple and multiple Analytical Hierarchical Process (AHP)
(multi-attribute Decision Analysis)
WP 120/WhP 40
13 Game theory vs Decision theory 10
14 Coordination game in extensive (tree) and matrix (normal) form 40
15 Decision in extensive (decision tree) deterministic form with Bayes probabilities 20
16 With or without (perfect or non-perfect) information decisions (EMV) 50
17 Cooperative vs Non-cooperative situations 10
18 Security level prudent tactic 10
19 Zero-sum (strictly competitive) and non-zero-sum (non-competitive) situations 20
20 Situations with Nash equilibrium and Pareto-optimum 20
21 Decision in extensive (tree) stochastic form 60
22 Maximin criterion and minimax (Wald) regret criterion 20
23 Hurwitz and Laplace criteria 50
24 Data envelopment analysis WP 50/WhP 20
25 Evolutionary stable strategies (Hawk-Dove game) 20
26 Basics of Cournot equilibrium 30
27 Markov chain behavior modeling WP 120/WhP 90
28 Gage R&R (repeatability & reliability) analysis WP 70/WhP 40
29 Cohen's Kappa 40
30 TURF (Total Unduplicated Reach and Frequency) analysis WP 40/WhP 10
Good to know: This seminar is especially interesting for people that want to deeply understand the various tools discusses in
the ISO 31000 Risk management norm and also other risk/assessment tools that are used a lot in R&D departments. Depending
on the country and university or engineering school this seminar outline corresponds to a Bachelor Master level in
management studies.

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IDTT09: Quantitative Data analysis (data mining)
AIM AND OBJECTIVE
The aim of this seminar is to provide a gentle
introduction to data mining (aka: machine
learning/advanced business intelligence or even Big
Data analysis) for professionals who need to analyze
data themselves, interpret results obtained using data
mining techniques, or give guidance to data analysts.
The goal is to introduce the basic principles,
techniques and methodologies of data mining and
provides the attendees with an overview of the
bachelor level data mining techniques.
TARGET AUDIENCE
The target audience of this seminar consists of
professionals (business analysts or opportunity
analysts) who experience a need for a better
understanding of data mining: what tasks can be
solved, what techniques can be used, what are their
strengths and weaknesses.
Attendees must have at least a graduate degree in
science or global equivalent to the content of
SUGGESTED DURATION
(open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
Tanagra, RapidMiner, R, MATLAB, Python, Power
BI and Minitab data mining softwares will be used for
the seminar. Laptops or computers with VirtualPC or
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
Business Analyst, Financial Analyst, Marketing
Manager, CDO, Students, etc.
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: data mining, data scientist, clustering, exploration, correlation, statistics, seminar, course, training

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01 Introduction 30
04 Importance of big data analysis 15
05 Data Mining vs Machine Learning and Supervised vs Unsupervised learning 20
06 Models selection criterias (AIC, BIC, MSE, Mallow's Cp,) and cross-
validation methods and metrics (MSE, OCV, GCV)
WP 450/WhP 120
07 Text mining basics 40
08 Zero rule (ZeroR) and one rule (OneR) and Classifiers WP 55/WhP 20
09 Classification and Regression Trees (CART) with quantitative or qualitative
variables and variable importance (+random forests)
WP 80/WhP 20
10 Dendrogram Clustering WP 35/WhP 15
11 Affinity Analysis (AA) 40
12 K-Means, K-Medoids Clustering WP 65/WhP 20
13 Mean-Shift Clustering WP 60/WhP 20
14 Gaussian Mixture Clustering WP 65/WhP 20
15 K Nearest Neighbors (K-NN) Clustering with Minkowski, Euclidean,
Manhattan (city-block), correlation, khi-2 or HEOM distance
WP 35/WhP 20
16 Iterative Dichotomiser Clustering (ID3) WP 75/WhP 10
17 Hierarchical Ascendant Clustering (HAC) WP 40/WhP 10
18 Ensemble Learning methods (Bagging vs Boosting) and Gradient boosting 90
19 Similarity analysis based on Multidimensional Scaling (MDS) WP 70/WhP 40
20 Prior Naive Bayes Classifier (Binomial and Gaussian) WP 50/WhP 15
21 Bayes Networks for prior Clustering WP 90/WhP 60
22 Linear Discriminant Analysis using "Fisher Discriminant" (posterior
likelihood method) or eigenvector projection method
WP 170/WhP 50
23 Z-score regression 30
24 Binomial and Multinomial logistic regression with confusion matrix, scoring
(propensity score), Lift/ROC Curve, F1 score
WP 135/WhP 40
25 Correlation and quality measures of binary (two-class) classifications
(Cramér'sV and phi association coefficients, Pearson's phi association
coefficient, Matthews correlation coefficient)
WP 120/WhP 30
26 Odds Ratio (OR)/Relative Risk (RR) + OR and RR confidence interval WP 110/WhP 30
27 Principal component analysis (PCA) WP 150/WhP 25
28 Principal Factor analysis without rotation (PFA) WP 60/WhP 15
29 PFC with VariMax and OrthoMax gamma rotation 15
30 (Factorial) Correspondence analysis (FCA/COA) WP 90/WhP 20
31 Multiple (Factorial) Correspondence analysis (MFCA/MCOA) WP 90/WhP 20
32 Ridge, LASSO, ElasticNet and Isotonic regularized regressions WP 420/WhP 210
33 Neural Networks (FF, LSTM, RNN, DNN) WP 840/WhP 240

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Good to know: This seminar will especially be interesting for people working at high level in marketing departments or for
analysts working in the domain of social sciences. People working also as community managers could be interested to the
topics to better focus their communications and get a higher effective lift. Depending on the country and university or
engineering school this seminar outline corresponds to a Master or PhD level in scientific data analysis.

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IDTT10: Quantitative Failure Modes and Effects Analysis (FMEA)
AIM AND OBJECTIVE
The aim of this seminar is to provide the attendees
the critical and powerful tools to quantify the
quality, reliability, failure indicators of designed
products and internal process, conforming to legal
obligations, standards and customers communication
respect (risk engineering).
TARGET AUDIENCE
This class is designed for those individuals who
work on various aspects of product development and
manufacturing and who already certified reliability
engineer (CRE) or not. It is assumed they come from
many different backgrounds, disciplines, education
levels and work on a variety of products and
processes areas across many departments of a
company.
A four-hour admission test with a one hour
science if seminar is requested with mathematical
proofs.
SUGGESTED DURATION
(open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
MS Office Excel/Visio, Open Calc, @Risk, Maple
or any other tool like software. Laptops or
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
Business Analyst, Engineer, Project
Manager/Analyst, Laboratory Assistant, Students,
Quality Manager/Analyst, etc.
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: fmea, failure, reliability, pareto, kaplan-meier, mtbf, mup, mdt, fault tree, seminar, training

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Detailed seminar program=
01 Introduction 30
04 Worldwide quality norms and standards 15
05 Failure rate by time interval (hazard ratio) 15
06 Discrete failure and reliability density and distribution functions 30
07 Instantaneous failure and reliability density and distribution functions WP 40/WhP 20
08 Definition and calculation of FMEA indicators (TBM, MOTBF, MTBF, etc.) 60
09 Linear instantaneous failure rate WP 20/WhP 10
10 Exponential instantaneous failure rate and main properties WP 60/WhP 20
11 Weibull instantaneous failure rate distribution and main properties WP 110/WhP 50
12 FMEA indicators based on linear, exponential and Weibull distributions WP 70/WhP 40
13 ABC/XYZ and Pareto based distribution analysis WP 120/WhP 40
14 Reliability block diagram (serial, parallel, k/n, parallel+serial, bridged) WP 80/WhP 40
15 Reliability block diagram (RBD) decomposition 30
16 Maximum likelihood reliability estimation (exponential, Weibull) 20
17 Fault tree analysis (AND/OR, Voting OR gates) 30
18 Reliability block diagram based on Monte Carlo simulation 40
19 Kaplan-Meier right censored lifetime analysis (survival analysis) WP 70/WhP 20
20 Cox proportional-hazards linear regression model for uncensored and
ungrouped/grouped data and time independent covariates
WP 120/WhP 30
21 Markov chain model for predicting reliability WP 180/WhP 20
22 Exponential-Chi demonstration test Design for MTTF for accumulated test
time required
WP 70/WhP 20
23 Non-Parametric Binomial reliability demonstration test design sample size WP 30/WhP 10
24 Bayesian beta-binomial reliability demonstration test design for sample size WP 70/WhP 20
25 Weibull right censored parametric reliability density function estimation WP 70/WhP 20
Good to know: This seminar focus on tools and techniques used typically by aerospace, airline, medical or nuclear engineers
who have to guarantee and analyze the reliability of their products and services at a high level because of life impacts or
social/economic nation/worldwide catastrophes in case of failure. Depending on the country and university or engineering
school this seminar outline corresponds to a Master or PhD level in reliability engineering.

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IDTT11: Quantitative Project Management (QPM)
AIM AND OBJECTIVE
Many organizations fail in project management
practices because of missing quant skills. The aim of
this seminar is to provide project managers who
already know qualitative process-oriented
methodologies (PMI, IPMA, PRINCE2, ITIL, 6,
EFQM, Agile, Hermes, etc.) the advanced scientific
project management techniques (applied managerial
statistics) and tools to simulate projects planning and
costs in a in a rigorous way. In other words: do
Evidence Based Management!
TARGET AUDIENCE
This seminar is designed for professional project
managers or engineers who desire to increase their
project management skills and apply a scientific
approach to project management.
science or global equivalent to the content of
SUGGESTED DURATION
(open book exam).
ORGANIZATION
ATTENDEES
CERTIFICATION
PEDAGOGICAL METHOD
and paper readings.
TRAINER(S)
TOOLS
MS Office Excel, @Risk, MS Project or any other
project management tool like software. Laptops or
BOOK
ISBN: 978-2-8399-0932-7 (7,276 pages PDF)
CONTACT
FUNCTIONAL LEVEL
Business Analyst, Financial Analyst, Engineer,
Project Manager/Analyst, Team Leader, Students,
etc.
EXAM / TEST
and performance.
PRICE / DATES
Dates on demand
Keywords: rty, pnet, what-if, estimate, monte carlo, latin hypercube, tv@r, fv@r, course, training

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Detailed seminar program=
01 Introduction 30
04 Complete graph theory for first step communication optimization WP 20/WhP 10
05 Business process rolled throughput yield (RTY) WP 15/WhP 10
06 Business process topologies (serial, parallel, k/n, parallel+serial, bridged) WP 80/WhP 40
07 Gantt chart as connected valuated oriented graph 10
08 PERT chart for critical path analysis (free lag, total lag, constraint path) 20
09 Deterministic time and cost scenarios (three-point estimates) 20
10 PMI Triangular and Beta probabilistic approach for simulation WP 240/WhP 90
11 Critical Chain Method for simulation 30
12 Time/Cost project management capability analysis WP 200/WhP 20
13 Use of past projects for new projects simulation (parametric estimation) WP 120/WhP 80
14 Chi-square and Kolmogorov-Smirnov adequation test WP 130/WhP 40
15 Mathematical reserve estimation 10
16 Regression modeling under statistical process control WP 360/WhP 70
17 How to communicate project time and costs estimations 60
18 Pareto/ABC and XYZ analysis with/without Lorenz charts (gain charts) and
Gini index
WP 120/WhP 40
19 Non-parametric bootstrapping inference technique 40
20 Monte Carlo and Latin hypercube simulation 100
21 Inverse Transform Sampling and Probability Integral Theorem 20
22 Sensitivity analysis and tornado charts 40
23 Value at risk models for time and costs (tV@R, fV@R) WP 80/WhP 40
Good to know: If you work on very large projects or strategic business plans (more than a few hundred million dollars) you
can't estimate costs and time execution correctly with subjective non-scientific methods. This seminar will be useful if you are
interesting to apply techniques to minimize volatility and mitigate risks. The techniques presented in this seminar can be
correctly applied if and only if you have a 100% quantitative project manager position (forget this seminar if you also have
various tasks that have nothing to do directly with quantitative project management). Depending on the country and university
or engineering school this seminar outline corresponds to a Bachelor or Master level in project management.

Scientific Evolution LLS Services Catalog v5.0 (2020)

Scientific Evolution LLS Services Catalog v5.0 (2020)

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Scientific Evolution LLS Services Catalog v5.0 (2020)