Lecture Marketing research - Chapter 12: Data Processing, fundamental data analysis, and statistical testing of differences

CHAPTER Twelve

Learning Objectives

Data
Processing,
Fundamental
Data Analysis,
and Statistical
Testing of
Differences
Copyright © 2004
John Wiley & Sons, Inc.


Learning Objectives
Learning Objectives
1. To develop an understanding of the importance and
nature of quality control checks.

2. To understand the data entry process and data
entry alternatives.
3. To learn how surveys are tabulated and crosstabulated.
4. To understand the concept of hypothesis
development and how to text hypotheses.


Learning Objectives
The Data Analysis
Procedure

To get an overview of the data
analysis procedure.

Five Step Procedure for Data Analysis:
Step One: Validation and editing (quality control)
Step Two: Coding
Step Three: Data Entry
Step Four: Machine Cleaning of Data
Step Five: Tabulation and Statistical Analysis


Learning Objectives

Validation and Editing

To understand the importance and
nature of quality control checks.

Validation
The process of ascertaining that interviews actually were
conducted as specified.
Editing
Checking for interviewer mistakes
1. Did the interviewer ask or record answers for certain
questions?
2. Questionnaires are checked to make sure Skip patterns
are followed.
3. Responses to open-ended responses are checked.

Learning Objectives

Data Entry

To understand the data-entry process
and data-entry alternatives.

Intelligent Data Entry
The checking of information being entered for internal
logic by either that data entry device or another device
connected to it.
The Data Entry Process
The mechanics of the process.
The validated, edited, and coded questionnaires are
given to a data entry operator.
The process of going directly from the questionnaire to
the data entry device and storage medium is more
accurate and efficient.


Learning Objectives

Tabulation of
Survey Results

To learn how surveys are tabulated.

One Way Frequency Tables
A table showing the number of responses to each
answer.

Base for Percentages
1. Total respondents
2. Number of people asked the question
3. Number of people answering the question
Selecting the Base for One-Way Frequency Tables
Showing Results from Multiple-Choice Questions


Learning Objectives

Tabulation of
Survey Results

To learn how to set up and
interpret crosstabulations.

Cross-Tabulations
Examination of the responses of one question relative to
responses to one or more other questions.
Provides a powerful and easily understood approach to the
summarization and analysis of survey research results.


Learning Objectives

Graphic Representations
of Data

To comprehend the basic
techniques of statistical analysis.

Line Charts
The simplest form of graphs.
Pie Charts
Appropriate for displaying marketing research results in a
wide range of situations.
Bar Charts
1. Plain bar chart
2. Clustered bar charts
3. Stacked bar charts
4. Multiple row, three-dimensional bar charts


Learning Objectives
To comprehend the basic
techniques of statistical analysis.

Descriptive Statistics

Measures of Central Tendency
• Mean
h

fiXi
X
where

=

I=1

n

fi = the frequency of the ith class
Xi = the midpoint of that class
h = the number of classes
n = the total number of observations


Learning Objectives

Descriptive Statistics

To comprehend the basic
techniques of statistical analysis.

• Mean
The sum of the values for all observation of a variable
divided by the number of observations
• Median
The observation below which 50 percent of the
observations fall.
• Mode
The value that occurs most frequently


Learning Objectives

Descriptive Statistics

To comprehend the basic
techniques of statistical analysis.

Measures of Dispersion
Variance
The sums of the squared deviations from the mean
divided by the number of observations minus one.
The same formula as standard deviation with the
square-root sign removed.
Range
The maximum value for a variable minus the minimum
value for that variable


Learning Objectives

Descriptive Statistics

To comprehend the basic
techniques of statistical analysis.

Measures of Dispersion
Standard deviation
Calculated by:
• subtracting the mean of a series from each value in a
series
• squaring each result
• summing them
• dividing by the number of items minus 1
• and taking the square root of this value.

Learning Objectives
To comprehend the basic
techniques of statistical analysis.

Descriptive Statistics

Measures of Dispersion
Standard deviation (continued)

S =
where

√

n

(Xi - X) 2
I=1

n-1
S = sample standard deviation
Xi = the value of the ith observation
X = the sample mean
n = the sample size


Learning Objectives

Descriptive Statistics

To comprehend the basic
techniques of statistical analysis.

Percentages and Statistical Tests
Whether to use measures of central tendency or
percentages.
Responses are either categorical or take the form of
continuous variables
Variables such as age can be continuous or categorical.
If categories are used, one-way frequency distributions and
crosstabulations are the most obvious choices.
Continuous data can be put into categories.


Learning Objectives

Differences and Changes

To become aware of the nature
of statistical differences.

Are certain measures different from one another?
For example:
Did top-of-mind awareness really increase?
Did customer satisfaction really increase?


Learning Objectives

Statistical Significance

To become aware of the nature
of statistical differences.

It is possible for numbers to be different in a mathematical
sense but not statistically different in a statistical sense.
• Mathematical differences
• Statistical significance
• Managerially important differences


Hypothesis Testing

Learning Objectives
To understand the concept of
hypothesis development and how to
test hypotheses.

Hypothesis
An assumption that a researcher makes about some
characteristic of the population under study.
Steps in Hypothesis Testing
Step One: Stating the Hypothesis
Null hypothesis: Ho
Alternative hypothesis: Ha
Step Two: Choosing the Appropriate Test Statistic

Hypothesis Testing

Learning Objectives
To understand the concept of
hypothesis development and how to
test hypotheses.

Step Three: Developing a Decision Rule
Step Four: Calculating the Value of the Test Statistic
• Use the appropriate formula
• Compare calculated value to the critical value.
• State the result in terms of:
• rejecting the null hypothesis
• failing to reject the null hypothesis
Step Five: Stating the Conclusion


Other issues

Learning Objectives
To understand the differences
between Type I and Type II errors.

Types of Errors in Hypothesis Testing
Type I Error
Rejection of the null hypothesis when, in fact, it is true.
Type II Error
Acceptance of the null hypothesis when, in fact, it is
false.
Accepting Ho or Failing to Reject Ho?

One-Tailed Test or Two-Tailed Test?


Table 12.13

Learning Objectives

Type I and Type II Errors
Actual State of the
Null Hypothesis

Fail to Reject Ho

Reject Ho

Ho is true

Correct (1- )
no error

Type I error ( )

Ho is false

Type II error ( )

Correct (1- )
no error

Commonly Used
Statistical Hypothesis Tests

Learning Objectives
To understand the concept
of hypothesis development
and testing a hypothesis.

Independent Versus Related Samples
Independent samples
Measurement of a variable in one population has
no effect on the measurement of the other variable
Related Samples
Measurement of a variable in one population may
influence the measurement of the other variable.
Degrees of Freedom
The number of observations minus the number of
constraints.


Learning Objectives

SUMMARY

• Validation and Editing
• Data Entry
• Optical Scanning
• Machine Cleaning of Data
• Tabulation of Survey Results
• Graphic Representations of Data

• Descriptive Statistics


Learning Objectives

SUMMARY

• Differences and Changes
• Statistical Significance
• Hypothesis Testing


Learning Objectives

The End

Copyright © 2004 John Wiley & Sons, Inc.