Download Chapter 13

Chapter Thirteen
Coding, Editing and Presenting
Data, and Preliminary data
Analysis
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-1
Learning Objectives
 Illustrate the process of preparing the
data for analysis.
 Demonstrate the procedure for assuring
data validation.
 Illustrate the process of editing and
coding data obtained through survey
methods.
 Acquaint the user with data entry
procedures.
 Illustrate the process for detecting
errors in data entry.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-2
Learning Objectives
 Discuss techniques used for data
tabulation.
 Understand the mean, median and
mode as measures of central
tendency.
 Understand the range and
standard deviation of a frequency
distribution as measures of
dispersion.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-3
Introduction
 Data preparation is the process of
taking data and preparing it for
conversion into information.
 Data validation is the process of
determining whether a survey’s
interviews or observations were
conducted correctly and are free of
fraud or bias.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-4
The Essentials of Data
Validation
 Data, when ‘validated’ by a
research team covers the
following five areas of concern:
1.
2.
3.
4.
5.
Fraud;
Screening;
Procedure;
Completeness;
Courtesy.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-5
Data Editing
Data editing is the process of
checking the data for mistakes
made by the interviewer or the
respondent.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-6
Data Editing
 Need to check:
1.
2.
3.
4.
Asking of questions
Recording of answers
Screening of respondents
Recording and coding of open
ended questions.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-7
Data Coding
Data coding is the process of grouping
and assigning value to the responses
from the survey instrument.
 Incorporate coding into questionnaire design
where possible.
 Use numeric codes.
 Assign codes to missing data.
 Open ended questions need to be coded for
data entry.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-8
The Master Code Form—Example
FAST-FOOD OPINION SURVEY
This questionnaire pertains to a project being conducted by a marketing research class at
The University of Memphis. The purpose of this project is to better understand the
attitudes and opinions of consumers towards fast-food restaurants. The questionnaire will
take only 10–15 minutes to complete, and all responses will remain strictly confidential.
Thank you for your help on this project.
1. Below is a listing of various fast-food restaurants. How many of these restaurants would you
say you visited in the past two months? Check as many as may apply.
Taco Bell
01
Church’s Fried Chicken
08
Hardee’s
02
McDonald’s
09
Kentucky Fried Chicken
03
Burger King
10
Wendy’s
04
Back Yard Burgers
11
Rally’s
05
Arby’s
12
Popeye’s Chicken
06
Sonic
13
Krystal’s
07
Other, please specify
Have not visited any of
these establishments
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
See code sheet
20
13-9
How to Handle Open-Ended
Questions
 There are four stages to coding openend questions:
1. Brainstorm a list of possible responses
and create a list. Assign a value to each of
the responses.
2. Consolidate the responses into response
categories which exhibit shared meaning.
3. Assign values to data which has been
captured by the survey instrument, as well
as data which has been omitted by the
respondent.
4. Assign a coded value to each response.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-10
Data Entry
Data entry is the process of the direct
input of the coded data into some
package to analyse, manipulate and
transform the data into useful
information.
 Can be entered directly into the computer
 Entered manually
 Scanned
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-11
Error Detection
 Error detection is the process of
ensuring that the data is error-free.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-12
Data Description
 Data description is the process of
describing the data sample so that
general patterns of responses and
respondent profiles are revealed.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-13
Data Tabulation: One-Way
Tabulation
 The process of counting the
number of observations/cases
that analysts classify into certain
categories.
 When a research team performs a
‘one-way’ tabulation they focus
on a single variable operating in
the research study.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-14
Frequency Distribution—An
Example
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-15
Data Tabulation:
Cross-tabulation
 A ‘cross-tabulation’ focuses on
two or more variables contained
in questions in the research
study.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-16
Cross-tabulation—Example
Brand use most often * Gender Crosstabulation
Brand
us e most
often
LG
MOTOROLA
NOKIA
SAMSUNG
SONY ERICKSON
Total
Count
% within Gender
Count
% within Gender
Count
% within Gender
Count
% within Gender
Count
% within Gender
Count
% within Gender
Gender
Male
Female
8
18
7.7%
24.3%
13
19
12.5%
25.7%
51
26
49.0%
35.1%
12
9
11.5%
12.2%
20
2
19.2%
2.7%
104
74
100.0%
100.0%
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
Total
26
14.6%
32
18.0%
77
43.3%
21
11.8%
22
12.4%
178
100.0%
13-17
Measures of Central
Tendency
 There are three primary
measures of central
tendency:
1. The Mean
2. The Mode
3. The Median
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-18
Desired Measures of Central
Tendency and Dispersion

Measures of Central Tendency:
1. Mean is the arithmetic average of all the
data responses in the sample.
2. Mode is the most common value in the
set of responses to a question.
3. Median occurs where half of the data is
above the statistic value and half is
below. This is the middle value of a rank
ordered distribution.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-19
Measures of Dispersion
 There are two primary measures
of dispersion:
1. The Range
2. The Standard Deviation
 The variance is the average
squared deviation about the
mean.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-20
Desired Measures of
Dispersion
 Measures of Dispersion
 Frequency distribution is a summary of how
many times each raw response was
recorded.
 Range is the spread of the data.
 Estimated sample standard deviations
specify the degree of variation in the data
responses.
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-21
It is important to note the following:
If a nominal scale is used
 analysis of data can only be done using modes
and frequency distributions.
If ordinal scales are used
 analysis of data can be done using medians and
ranges (plus modes and frequency distributions).
If interval or ratio scales are used
 analysis of data can be done through the use of
sample means and estimated standard deviations
as the sample statistic (plus the above).
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-22
Analysis of Data
Programs such as SPSS can
be used to analyse data.
Frequencies. Cross tabs,
measures of dispersion
And more…
Copyright  2007 McGraw-Hill Pty Ltd
PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau
Slides prepared by Judy Rex
13-23