The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
Chapter 1
1. Quote of the Day
Oh, people can come up with statistics to
prove anything. 14% of people know
that. ---Homer Simpson
What are Statistics?
2. Chapter 1:The Nature of
Probability and Statistics
Section 1:
Descriptive and Inferential
Statistics
3. Stats in Daily Life
Of the people in the US, 14% said they feel
happiest in June, and 14% said they feel
happiest in December.
The average in-state college tuition and fees
for 4-year pubic college is $5,836.
Every day in the US about 120 golfers claim
that they made a hole-in-one.
4 out of 5 doctors leaves one doctor.- Chevy
Chase
4. What is Statistics?
The science of conducting studies to
collect, organize, summarize, analyze
and draw conclusions from data.
5. What is Data?
The values that the variables can
assume.
A collection of values forms a Data
Set
Each Value in the data set is called:
Data Value or
Datum
6. What is a variable?
A characteristic or attribute that can
assume different values.
7. Types of Statistics
1. Descriptive Statistics
Consists of the collection, organization,
summarization, and presentation of data
Ex: Government Census
Taken every ten years
Describes average income, family size, etc..
What does this mean?
Basically used to describe a situation.
8. Types of Statistics
2. Inferential Statistics
Consists of generalizing from samples
to populations, performing estimations
and hypothesis tests, determining
relationships among variables, and
making predictions.
Ex: Winning the lottery
1 in a million
What does this mean ?
Used to predict the outcome of an event.
9. What is the difference between a
Population and a Sample?
Population- consists of all subjects
that are being studied.
Sample- is a group selected from a
population.
12. Section 2: Types of Variables
Qualitative Variables:
Variables that can be placed into distinct
categories, according to some
characteristic or attribute.
Ex: Gender, Eye color, Geographic
Location
13. 2 Types of Variables
Quantitative Variables:
Variables that are numerical and can be
ordered or ranked.
Ex: Age, height, weight, body temp
Classified by two groups
Discrete Variables
Continuous Variables
15. Discrete Variables
Assume values that can be counted
Assigned numbers such as 0,1,2,3,…
Ex:
# of children
# of students
16. Continuous Variables
Can assume an infinite number of
values between any two specific values.
Obtained by measuring
Often include fractions and decimals.
Ex:
Temperature
Time
Length
18. Measurement Scale
Used to categorize, count, or measure
variables.
Types:
Nominal
Ordinal
Interval
Ratio
19. Nominal Level of Measurement
Classifies data into mutually exclusive,
exhausting categories in which no order
or ranking can be imposed on the data.
Ex:
Male/Female
Single/Married/Divorced/Widowed/Separated
Democratic/Republican
20. Ordinal Level of Measurement
Classifies data into categories that can
be ranked; however, precise differences
between the ranks do not exist.
Ex:
Letter Grades (A, B, C, D, F)
1st, 2nd, 3rd, etc
Small, Medium, Large
Freshman, Sophomores, Juniors, Seniors
21. Interval Level of Measurement
Ranks data, and precise differences
between units of measures do exist:
however, there is no meaningful zero.
Ex:
Temperature: 72°F and 73°F, difference of
1°F, but 0°F does not mean no heat
present
IQ: 109 and 110, difference of 1 point, but
0 does not mean there is no intelligence.
22. Ratio Level of Measurement
Possesses all the characteristics of interval
measurements, and there exists a true zero.
In addition, true ratios exists when the same
variables is measured on two different
members of the population.
Ex:
Salary
Time
Age
24. Section 3: Data Collection and
Sampling Techniques.
Types:
Random
Systematic
Stratified
Cluster
25. Random Sampling
Selection based on chance or random
numbers.
Procedure:
Assign number to each subject in
population
Select numbers at random from “hat”
29. Stratified Sampling
Procedures:
Population divided into groups called:
Strata
Groups have common characteristic
needed for study.
Samples randomly selected from each
strata
31. Cluster Sampling
Population is divided into groups called:
Clusters
Select some clusters
Survey every member of the cluster for
sample
Used with large populations
33. Other sampling methods
Convenience sampling
Use subjects that are convent
Ex: asking people as they enter the mall
Sequential sampling
Double sampling
Multistage sampling
36. Section 4: 2 Types of Studies
Observational Study
Researchers merely observe what is
happening or what has happened in the
past
Try to draw conclusions based on these
observations.
Ex: studying creatures in the wild
“Meerkat Manor”
37. Section 4: 2 Types of Studies
Experimental study
Researchers manipulate one of the
variables
Tries to determine how to the manipulation
influences other variables.
Ex: New medication and placebos
39. Statistical Studies include….
Independent variables
In an experimental study is the one that is
being manipulated by the researcher.
Also called: Explanatory variable
Dependent variables
Resultant variable
Also called: Outcome variable
40. Misuses of Statistics
Suspect Samples
Too small
Convenience
Volunteers
Changing the subject
Increase of 3%
Increase of $600,000
41. Misuses of Statistics
Detached Statistics- no comparison
“Works 5 times faster”
“1/3 fewer calories”
Implied Connection
“Eating fish may help you achieve better in
school”
42. Misuses of Statistics
Misleading Graphs- Chapter 2
Faulty Survey Questions
“Do you feel there should be a 4 day
school week?”
“Do you feel there should be a 4 day
school week from 4 am to midnight?”