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Statistics for Managers
Using Microsoft® Excel
4th Edition
Chapter 1
Introduction and Data Collection
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-1
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-2
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

obtain reliable forecasts
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-3
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-4
Population vs. Sample
Population
a b
Sample
cd
b
ef gh i jk l m n
o p q rs t u v w
x y
z
Measures used to describe
the population are called
parameters
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
c
gi
o
n
r
u
y
Measures computed from
sample data are called
statistics
Chap 1-5
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-6
Descriptive Statistics

Collect data


Present data


e.g., Survey
e.g., Tables and graphs
Characterize data

X

e.g., Sample mean =
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
i
n
Chap 1-7
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.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-8
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-9
Data Sources
Primary
Secondary
Data Collection
Data Compilation
Print or Electronic
Observation
Survey
Experimentation
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-10
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-11
Types of Samples Used

Nonprobability 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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-12
Types of Samples Used
(continued)
Samples
Non-Probability
Samples
Judgement
Quota
Chunk
Convenience
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Probability Samples
Simple
Random
Stratified
Systematic
Cluster
Chap 1-13
Probability Sampling

Items in the sample are chosen based on
known probabilities
Probability Samples
Simple
Random
Systematic
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Stratified
Cluster
Chap 1-14
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-15
Systematic Samples

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
N = 64
n=8
First Group
k=8
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-16
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-17
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-18
Advantages and Disadvantages

Simple random sample and systematic sample



Stratified sample


Simple to use
May not be a good representation of the population’s
underlying characteristics
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)
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-19
Types of Data
Data
Categorical
Numerical
Examples:



Marital Status
Political Party
Eye Color
(Defined categories)
Discrete
Examples:


Number of Children
Defects per hour
(Counted items)
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Continuous
Examples:


Weight
Voltage
(Measured characteristics)
Chap 1-20
Levels of Measurement
and Measurement Scales
Differences between
measurements, true
zero exists
Ratio Data
Differences between
measurements but no
true zero
Interval Data
Ordered Categories
(rankings, order, or
scaling)
Ordinal Data
Categories (no
ordering or direction)
Nominal Data
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Highest Level
Strongest forms of
measurement
Higher Level
Lowest Level
Weakest form of
measurement
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-22
Types of Survey Errors

Coverage error or selection bias


Non response error or bias


People who do not respond may be different from those
who do respond
Sampling error


Exists if some groups are excluded from the frame and
have no chance of being selected
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
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-23
Types of Survey Errors
(continued)

Coverage error
Excluded from
frame

Non response error
Follow up on
nonresponses

Sampling error
Random
differences from
sample to sample

Measurement error
Bad or leading
question
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-24
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

Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc.
Chap 1-25