The document discusses key concepts in statistics for managers, including defining populations and samples, descriptive versus inferential statistics, different sampling methods, types of data and measurement scales, and sources of error in surveys. It aims to explain why understanding statistics is important for managers to properly analyze and present information, make decisions based on data, and improve processes. The chapter goals are to introduce fundamental statistical concepts and methods in data collection.

1. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-1
Statistics for Managers
Bahan Kuliah Pra MM
3 Oktober 2010
Kuliah Pertama
Introduction and Data Collection
Dr. Syuhada Sufian, MSIE

2. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-2
Chapter Goals
After completing this chapter, you should be
able to:
 Explain key definitions:
♦ Population vs. Sample ♦ Primary vs. Secondary Data
♦ Parameter vs. Statistic ♦ Descriptive vs. Inferential Statistics
 Describe key data collection methods
 Describe different sampling methods
 Probability Samples vs. Nonprobability Samples
 Select a random sample using a random numbers table
 Identify types of data and levels of measurement
 Describe the different types of survey error

3. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-3
Why a Manager Needs to
Know about Statistics
To know how to:
 properly present information
 draw conclusions about populations based
on sample information
 improve processes decession
 obtain reliable forecasts

4. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-4
Key Definitions
 A population (universe) is the collection of all
items or things under consideration
 A sample is a portion of the population
selected for analysis
 A parameter is a summary measure that
describes a characteristic of the population
 A statistic is a summary measure computed
from a sample to describe a characteristic of
the population

5. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-5
Population vs. Sample
a b c d
ef gh i jk l m n
o p q rs t u v w
x y z
Population Sample
b c
g i n
o r u
y
Measures used to describe
the population are called
parameters
Measures computed from
sample data are called
statistics

6. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-6
Two Branches of Statistics
 Descriptive statistics
 Collecting, summarizing, and describing data
 Inferential statistics
 Drawing conclusions and/or making decisions
concerning a population based only on sample
data

7. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-7
Descriptive Statistics
 Collect data
 e.g., Survey
 Present data
 e.g., Tables and graphs
 Characterize data
 e.g., Sample mean =
iX
n
∑

8. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-8
Inferential Statistics
 Estimation
 e.g., Estimate the population
mean weight using the sample
mean weight
 Hypothesis testing
 e.g., Test the claim that the
population mean weight is 120
pounds
Drawing conclusions and/or making decisions
concerning a population based on sample results.

9. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-9
Why We Need Data
 To provide input to survey
 To provide input to study
 To measure performance of service or
production process
 To evaluate conformance to standards
 To assist in formulating alternative courses of
action
 To satisfy curiosity (keunikan)

10. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-10
Data Sources
Secondary
Data Compilation
Observation
Experimentation
Print or Electronic
Survey
Primary
Data Collection

11. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-11
Reasons for Drawing a Sample
 Less time consuming than a census
 Less costly to administer than a census
 Less cumbersome and more practical to
administer than a census of the targeted
population

12. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-12
 Non – probability Sample
 Items included are chosen without regard to
their probability of occurrence
 Probability Sample
 Items in the sample are chosen on the basis
of known probabilities
Types of Samples Used

13. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-13
Types of Samples Used
Quota
Samples
Non-Probability
Samples
Judgement Chunk
Probability Samples
Simple
Random
Systematic
Stratified
Cluster
Convenience
(continued)

14. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-14
Probability Sampling
 Items in the sample are chosen based on
known probabilities
Probability Samples
Simple
Random Systematic Stratified Cluster

15. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-15
Simple Random Samples
 Every individual or item from the frame has an
equal chance of being selected
 Selection may be with replacement or without
replacement
 Samples obtained from table of random
numbers or computer random number
generators

16. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-16
 Decide on sample size: n
 Divide frame of N individuals into groups of k
individuals: k=N/n
 Randomly select one individual from the 1st
group
 Select every kth
individual thereafter
Systematic Samples
N = 64
n = 8
k = 8
First Group

17. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-17
Stratified Samples
 Divide population into two or more subgroups (called
strata) according to some common characteristic
 A simple random sample is selected from each subgroup,
with sample sizes proportional to strata sizes
 Samples from subgroups are combined into one
Population
Divided
into 4
strata
Sample

18. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-18
Cluster Samples
 Population is divided into several “clusters,”
each representative of the population
 A simple random sample of clusters is selected
 All items in the selected clusters can be used, or items can be
chosen from a cluster using another probability sampling
technique
Population
divided into
16 clusters. Randomly selected
clusters for sample

19. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-19
Advantages and Disadvantages
 Simple random sample and systematic sample
 Simple to use
 May not be a good representation of the population’s
underlying characteristics
 Stratified sample
 Ensures representation of individuals across the
entire population
 Cluster sample
 More cost effective
 Less efficient (need larger sample to acquire the
same level of precision)

20. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-20
Types of Data
Data
Categorical Numerical
Discrete Continuous
Examples:
 Marital Status
 Political Party
 Eye Color
(Defined categories)
Examples:
 Number of Children
 Defects per hour
(Counted items)
Examples:
 Weight
 Voltage
(Measured characteristics)

21. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Levels of Measurement
and Measurement Scales
Interval Data
Ordinal Data
Nominal Data
Highest Level
Strongest forms of
measurement
Higher Level
Lowest Level
Weakest form of
measurement
Categories (no
ordering or direction)
Ordered Categories
(rankings, order, or
scaling)
Differences between
measurements but no
true zero
Ratio Data
Differences between
measurements, true
zero exists

22. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-22
Evaluating Survey Worthiness
 What is the purpose of the survey?
 Is the survey based on a probability sample?
 Coverage error – appropriate frame?
 Nonresponse error – follow up
 Measurement error – good questions elicit good
responses
 Sampling error – always exists

23. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-23
Types of Survey Errors
 Coverage error or selection bias
 Exists if some groups are excluded from the frame and
have no chance of being selected
 Non response error or bias
 People who do not respond may be different from those
who do respond
 Sampling error
 Variation from sample to sample will always exist
 Measurement error
 Due to weaknesses in question design, respondent
error, and interviewer’s effects on the respondent

24. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-24
Types of Survey Errors
 Coverage error
 Non response error
 Sampling error
 Measurement error
Excluded from
frame
Follow up on
nonresponses
Random
differences from
sample to sample
Bad or leading
question
(continued)

25. Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-25
Chapter Summary
 Reviewed why a manager needs to know statistics
 Introduced key definitions:
♦ Population vs. Sample ♦ Primary vs. Secondary data types
♦ Qualitative vs. Qualitative data ♦ Time Series vs. Cross-Sectional data
 Examined descriptive vs. inferential statistics
 Described different types of samples
 Reviewed data types and measurement levels
 Examined survey worthiness and types of survey
errors