Marketing Research 8

Hello,

Advance assistance required with the attached assignment. I have attached as much information as possible. Should you run into any issues please notify me asap. Thank you

Don't use plagiarized sources. Get Your Custom Essay on

Just from $13/Page

Order Essay

Unit8 [MT355]

Page 1 of3

Unit 8 Assignment: Data Analysis and Interpretation

In this Assignment you will be assessed based on the following outcome:

MT355-4: Prepare a business solution based on data analysis and interpretation.

Business leaders rely on the work of marketing researchers to make decisions that will impact revenue
generation and the profitability of the company. The data analysis and interpretation phase of a marketing

research project is a critical process that is highly scrutinized for accuracy and validity. Marketing
researchers must take great care in analyzing data that will be interpreted and turned into information for
the purpose of solving the research problem, or capitalizing on an opportunity that was under study.

Acting as a marketing research professional in this Assignment, you will demonstrate the following
competencies in relation to the tasks you are required to execute:

 Obtain and process information

 Prepare researched solution for client situation

Developing an ability to obtain and process information for decision making as a marketing researcher will

be a valuable addition to your business tool belt.

Directions for completing this Assignment

Using the Random Scenario Generator (RSG), select a scenario in which you will provide a business
solution for a specific type of businesses within an industry and region. (Reminder: The RSG will prompt

you to select 1 of the 3 options for each of the variables. Once you have selected from each variable
category, the resulting scenario is to be the basis for your work on this Assignment. Each student’s
scenario will be documented.)

Your paper should be a minimum 1,500-words report (6-pages, in addition to the title and appendix

pages.

Exception: include your references in the appendix.), using APA 6th edition style and format, in 12-pt font,

and double-spaced.

Use the following format for your Assignment paper:
(Only use the headings and not the instructions in parenthesis)

Title Page

Table of Contents

1. Executive Summary

(To be completed after paper is completed and conclusions are made.)

2. Overview of Situation

(RSG presented situation- provide the business problem statement that businesses would need to
research.)

https://kapextmediassl-a.akamaihd.net/business/Media/MT355/MT355_1904C/RSG/story.html

Unit 8 [MT355]

Page 2 of3

3. Industry Research

(Evaluation of legitimate industry data related to the business problem from the RSG. Search in the PG
Library or other sources for secondary information including research studies related to the RSG
situation.)

4. Credibility of Research

(Explain the credibility of research that will be applied towards the decision on possible solutions.)

5. Potential Solutions

(Describe using inductive or deductive reasoning, a minimum of two alternative solution options for
businesses within the RSG industry based on the evaluation of researched information.)

6. Preferred solution for the industry businesses within the geographic region

7. Conclusions and future research needed to support business decisions

Appendix A: Referenced Documents (In APA format)

Appendix B: Other Documents as needed

Review this tutorial on Searching for Information in the Library.

Directions for Submitting Your Assignment

Review the grading rubric below before beginning this Assignment. For additional help with APA 6th
edition formatting, please visit the Writing Resources accessed through the Academic Success Center

within the Academic Tools area of the course. Compose your Assignment as a Microsoft® Word®
document and save it with your first name initial and last name (Example: JDeem-MT355 Assignment-Unit
8 x). Submit your file by selecting the Unit 8 Assignment Dropbox by the end of the unit.

Unit 8 Assignment: Data Analysis and Interpretation Possible

Points

Earned

Points

Content, Focus, Use of Text/Outside Sources

Executive Summary: Briefly explains the essence of the paper. 5

Overview: Clearly established overview of the business problem. 5

Quality, prior researched, industry data is presented for analysis. 10

Credibility of data is presented. 10

Minimum of two effective potential solutions are presented. 10

Preferred solution is presented using inductive or deductive reasoning. 5

https://library.purdueglobal.edu/infolit_searchingexploration

Unit 8 [MT355]

Page 3 of3

Unit 8 Assignment: Data Analysis and Interpretation Possible
Points
Earned
Points

Conclusions and future research for business decisions are provided.

References from the study are included in Appendix. 5

Minimum of 1,500-words (6-pages), not including the title, and appendix

pages.
5

Clarity / Organization
You are expected to meet the following requirements with ease in a 300
level course. Penalties will be calculated as a percentage up to 50% of the
grade and will apply if the following criteria are not met.

Applied expository writing style. Writing style, grammar, and APA 6th edition
formatting.

Applied proper APA 6th edition formatting style; including in-text citations,
title page, and reference page.

No spelling and grammatical mistakes.

Used appropriate language related to the strategy theories, concepts, and
principles learned.

Professional use of abbreviations and acronyms.

Total Gross Assignment Score: 60

Late Penalty (-10% 1 week late, -20% for over one week. Prior approval
for any projects later than 2 weeks.)

Total

Chapter 10

Preparing Data for

Quantitative Analysis

Learning Objectives

• Describe the process for data preparation and
analysis

• Discuss validation, editing, and coding of
survey data

• Explain data entry procedures and how to
detect errors

• Describe data tabulation and analysis
approaches

Value of Preparing Data for Analysis

• Data preparation process – Converting data
from a source into usable code for data
analysis

– Important in:

• Assessing and controlling data integrity

• Ensuring data quality by detecting potential response
and nonresponse biases created by interviewer or
respondent errors

• Dealing with inconsistent data from different sources

• Converting data in multiple formats to a single format
that can be analyzed

Exhibit 10.1 – Overview of Data
Preparation and Analysis

Validation

• Determines whether a survey’s interviews or
observations were conducted correctly and
are free of fraud or bias

– Curbstoning: Cheating or falsification in the data
collection process

Areas Covered by Validation

Fraud Screening Procedure

Completeness Courtesy

Editing

• Raw data is checked for mistakes made by
either the interviewer or the respondent

• By reviewing completed interviews from
primary research, the researcher can check
several areas of concern

– Asking proper questions and recording answers
accurately

– Correct screening of respondents and complete
and accurate recording of open-ended questions

Coding

• Grouping and assigning values to various
responses from survey instruments

– Codes are numerical

– Gets tedious if certain issues are not addressed
prior to collecting the data

• Well-planned and constructed questionnaire reduces
the time spent on coding

Coding (continued)

• Four-step process to develop codes for
responses

– Generate a list of as many potential responses as
possible

– Consolidate responses

– Assign a numerical value as a code

– Assign a coded value to each response

Data Entry

• Tasks involved with the direct input of the
coded data into some specified software
package

– Allows the research analyst to manipulate and
transform the raw data into useful information

• Involves:

– Error detection

– Missing data

– Organizing data

Error Detection

• Identifies errors from data entry or other
sources

• Approaches

– Determine if the software used will perform error
edit routines

– Review a printed representation of the entered
data

– Run a tabulation of all survey questions to
examine the responses for completeness and
accuracy

Missing Data

• Situation in which respondents do not provide
an answer to a question

• Counter approaches

– Replace missing value with a value from a similar
respondent

– Use the answers to other similar questions as a
guide in determining the replacement value

Missing Data (continued)

– Use mean of a subsample of the respondents with
similar characteristics that answered the question
to determine a replacement value

– Use mean of the entire sample that answered the
question as a replacement value

• Not recommended as it reduces overall variance in the
question

Data Tabulation

• Counting the number of observations or cases
that are classified into certain categories

• Forms

– One-way tabulation: Categorization of single
variables existing in a study

– Cross-tabulation: Simultaneously treating two or
more variables in a study

• Categorizes the number of respondents who have
answered two or more questions

One-Way Tabulation

• Purposes

– Determine the amount of nonresponse to
individual questions

– Locate mistakes in data entry

– Communicate the results of a research project

• Illustrated by constructing a one-way
frequency table

One-Way Tabulation (continued)

• In reviewing the output, look for:

– Indications of missing data

– Determining valid percentages

– Summary statistics

Descriptive Statistics

• Used to summarize and describe the data
obtained from a sample of respondents

• Measures used to describe data

– Central tendency

– Dispersion

Graphical Illustration of Data

• Next step following development of frequency
tables is to translate them into graphical
illustrations

• Powerful for communicating key research
results generated from preliminary data
analysis

Marketing Research in Action
Deli Depot

• Should the Deli Depot questionnaire have
screening questions?

• Run a frequency count on variable X3–
Competent Employees

– Do the customers perceive employees to be
competent?

Marketing Research in Action
Deli Depot (continued)

• Consider the guidelines on questionnaire
design

– How would you improve the Deli Depot
questionnaire?

Chapter 12

Examining
Relationships in

Quantitative Research

Learning Objectives

• Understand and evaluate the types of
relationships between variables

• Explain the concepts of association and co-
variation

• Discuss the differences between Pearson
correlation and Spearman correlation

Learning Objectives

(continued)

• Explain the concept of statistical significance
versus practical significance

• Understand when and how to use regression
analysis

Examining Relationships between
Variables

• Concepts used

– Presence

– Direction

– Strength of association

– Type

• Linear relationship: Association between two variables
whereby the strength and nature of the relationship
remains the same over the range of both variables

• Curvilinear relationship: Relationship between two
variables whereby the strength and/or direction of the
relationship changes over the range of both variables

Covariation and Variable Relationships

• Covariation: Amount of change in one
variable that is consistently related to the
change in another variable of interest

• Scatter diagram: Graphic plot of the relative
position of two variables using a horizontal
and a vertical axis to represent their values

– Possible relationships – Positive, negative,
curvilinear, and non-existent

Correlation Analysis

• Pearson correlation coefficient: Statistical
measure of the strength of a linear
relationship between two metric variables

– Varies between – 1.00 and 1.00

• 0 – No association between two variables

• – 1.00 or 1.00 – Perfect link between two variables

• Correlation coefficient can be either positive or
negative, depending on the direction of the
relationship

Exhibit 12.5 – Rules of Thumb about the
Strength of Correlation

Coefficients

Range of Coefficient Description of Strength

±.81 to ±1.00 Very Strong

±.61 to ±.80 Strong

±.41 to ±.60 Moderate

±.21 to ±.40 Weak

±.00 to ±.20 Weak to No Relationship

Assumptions Involved in Calculating
Pearson’s Correlation Coefficient

• Variables are to be measured using interval- or
ratio-scaled measures

• Nature of the relationship to be measured is
linear

– Straight line describes the relationship between
the variables of interest

• Variables to be analyzed have a normally
distributed population

Exhibit 12.6 – SPSS Pearson Correlation
Example for Santa Fe Grill Customers

Descriptive Statistics

Mean Std. Deviation N

X22– Satisfaction 4.54 1.002 253

X24– Likely to

Recommend

3.61 .960 253

Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education.
Exhibit 12.6 – SPSS Pearson Correlation
Example for Santa Fe Grill Customers
(continued)

Correlations

X22 — Satisfaction
X24 — Likely to

Recommend

X22 — Satisfaction Pearson Correlation 1 .776**

Sig. (2-tailed) .000

N 253 253

X24– Likely to

Recommend
Pearson Correlation .776** 1

Sig. (2-tailed) .000
N 253 253

**. Correlation is significant at the 0.01 level (2-tailed).

Substantive Significance of the
Correlation Coefficient

• Coefficient of determination (r2): Number
measuring the proportion of variation in one
variable accounted for by another

– Can be represented as a percentage

– Ranges from 0.0 to 1.00

– Larger the size of the coefficient of determination,
stronger the linear relationship between the two
variables being examined

Influence of Measurement Scales on
Correlation Analysis

• Spearman rank order correlation coefficient:
Statistical measure of the linear association
between two variables where both have been
measured using ordinal (rank order) scales

Exhibit 12.7 – SPSS Spearman Rank
Order Correlation

Correlations

X27– Food Quality X29– Service

Spearman’s rho X27 — Food Quality Correlation Coefficient 1.000 -.130**

Sig. (2-tailed) .009

N 405 405

X29 — Service Correlation Coefficient -.130** 1.000

Sig. (2-tailed) .009
N 405 405

** Correlation is significant at the 0.01 level (2-tailed).

Regression Analysis

• Bivariate regression analysis

– Statistical technique

– Analyzes the linear relationship between two
variables by estimating coefficients for an
equation for a straight line

• One variable is designated as a dependent variable

• Other variable is called an independent or predictor
variable

Assumptions Behind Regression
Analysis

• Linear relationship

– Describes the relationship between two variables

• Dependent and independent variables

– Labeling does not infer that one variable
influences the behavior of another

Assumptions Behind Regression
Analysis (continued)

• Use of a simple regression model assumes
that:

– Variables of interest are measured on interval or
ratio scales

– Variables come from a normal population

– Error terms associated with making predictions
are normally and independently distributed

Exhibit 12.9 – The Straight Line
Relationship in Regression

Fundamentals of Regression Analysis

• General formula for a straight line

Y = a + bX + ei
– Where,

• Y – Dependent variable

• a – Intercept (point where the straight line intersects
the Y-axis when X = 0)

• b – Slope (the change in Y for every 1 unit change in X)

• X – Independent variable used to predict Y

• ei – Error for the prediction

Fundamentals of Regression Analysis
(continued)

Least squares procedure

• Determines the best-fitting line by minimizing the vertical
distances of all the points from the line

Unexplained variance

• Amount of variation in the dependent variable that cannot
be accounted for by the combination of independent
variables

Exhibit 12.10 – Fitting the Regression Line
Using the Least Squares Procedure

Developing and Estimating the
Regression Coefficients

Ordinary least squares

• Estimates regression equation coefficients that produce the
lowest sum of squared differences between the actual and
predicted values of the dependent variable

Regression coefficient

• Indicator of the importance of an independent variable in
predicting a dependent variable

• Large coefficients are good predictors, and small coefficients
are weak predictors

Exhibit 12.11 – SPSS Results for
Bivariate Regression

Model summary

Model R R Square Adjusted R Square Std. Error of

the Estimate

1 .479a .230 .227 .881

a. Predictors: (Constant), X16 — Reasonable Prices

Exhibit 12.11 – SPSS Results for
Bivariate Regression (continued 1)

ANOVAb

Model Model Sum of Squares df Mean Square F Sig.

1 Regression 58.127 1 58.127 74.939

.000a

Residual 194.688 251 .776

Total 252.814 252

a. Predictors: (Constant), X16 — Reasonable

Prices

b. Dependent Variable: X22 — Satisfaction

Exhibit 12.11 – SPSS Results for
Bivariate Regression (continued 2)

Coefficientsa

Model Model

Unstandardized

Coefficients
Unstandardized
Coefficients

Standardized

Coefficients

t Sig.

Model Model B Std. Error Beta t Sig.

1 (Constant) 2.991 .188 15.951 .000

X16 —

Reasonable

Prices

.347 .040 .479 8.657 .000

a. Dependent Variable: X22 — Satisfaction

Significance of Regression
Coefficients

• Regression coefficients help addressing
questions regarding relationships

– Is there a relationship between the dependent
and independent variable?

• How strong is the relationship?

Multiple Regression Analysis

• Analyzes the linear relationship between a
dependent variable and multiple independent
variables

• Beta coefficient: Estimated regression
coefficient recalculated to have a mean of 0
and a standard deviation of 1

– Enables independent variables with different
measurement units to be directly compared on
the association with the dependent variable

Examining the Statistical Significance
of Each Coefficient

• Each regression coefficient is divided by its
standard error to produce a t statistic

– t statistic is compared against the critical value to
determine whether the null hypothesis can be
rejected

• Model F statistic: Compares the amount of
variation in the dependent measure
associated with the independent variables to
the error variance

Substantive Significance

• The multiple r2 describes the strength of the
relationship between all the independent
variables and the dependent variable

• Evaluating the results of a regression analysis

– Assess the statistical significance of the overall
regression model using the F statistic

– Evaluate the obtained r2

– Examine the individual regression coefficients and
their t statistics

– Examine the beta coefficients

Multiple Regression Assumptions

• Linear relationship

• Homoskedasticity: Pattern of the covariation
is constant around the regression line

• Normal distribution

Multiple Regression Assumptions
(continued)

• Heteroskedasticity: Pattern of covariation
around the regression line is not constant

– Indicates that the shape of variable distribution is
equal both above and below the mean

• Normal curve: Indicates the shape of the
distribution of a variable is equal both above
and below the mean

Exhibit 12.14 – SPSS Results for
Multiple Regression

Model Summary

Model R R Square Adjusted R

Square

Std. Error of

the Estimate

1 .646a .417 .410 .770

a. Predictors: (Constant), X20 — Proper Food Temperature, X15 — Fresh Food,

X18 — Excellent Food Taste

Exhibit 12.14 – SPSS Results for
Multiple Regression (continued 1)

ANOVAb
Model Model Sum of Squares df Mean Square F Sig.

1 Regression 105.342 3 35.114 59.28

8
.000a

Residual 147.472 249 .592

Total 252.814 252

a. Predictors: (Constant), X20 — Proper Food Temperature, X15 — Fresh Food, X18 -Excellent

Food Taste

b. DependentVariable:X22- Satisfaction

Exhibit 12.14 – SPSS Results for
Multiple Regression (continued 2)

Coefficients3

Model Model Unstandardized

Coefficients
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
Model Model B Std. Error Beta t Sig.

1 (Constant) 2.144 .269 7.984 .000

X15–Fresh Food .660 .068 .767 9.642 .000

X18 — Excelent

Food Taste

-.304 .095 -.267 -3.202 .002

X20– Proper Food

Temperature

.090 .069 .096 1.312 .191

a. Dependent Variable: X22– Satisfaction

Multicollinearity

• Several independent variables are highly
correlated

– May result in difficulty in estimating independent
regression coefficients for the correlated variables

Marketing Research in Action
Developing a Customer Satisfaction Program

• Will the results of this regression model be
useful to the QualKote plant manager? How?

• Which independent variables are helpful in
predicting A36–Customer Satisfaction?

• How would the manager interpret the mean
values for the variables reported in Exhibit
12.16?

• What other regression models might be
examined with the questions from the survey?

Chapter 1

Basic Data Analysis
for Quantitative

Research

Learning Objectives

• Explain measures of central tendency and
dispersion

• Describe how to test hypotheses using
univariate and bivariate statistics

• Apply and interpret analysis of variance
(ANOVA)

• Utilize perceptual mapping to present
research findings

Value of Statistical Analysis

• Helps researchers understand responses

– Summary statistics – Used to identify important
information present in large amounts of data

• Basic statistics

• Descriptive analysis

Measures of Central Tendency

Mean

• Arithmetic average of a sample

Median

• Middle value of a rank-ordered distribution

Mode

• Most common value in the set of responses to a question

Measures of Dispersion

Range

• Distance between the smallest and largest values in a set of
responses

Standard deviation

• Average distance of the distribution values from the mean

Variance

• Average squared deviation about the mean of a distribution of
values

How to Develop and Test Hypotheses

• Review research objectives and background
information

• Develop null and alternative hypotheses

• Determine the sampling distribution, and
select an appropriate sampling test

• Determine the level of statistical significance

• Determine if differences are statistically
significant and meaningful

• Accept or reject the null hypothesis

Analyzing Relationships of Sample
Data

• Sample statistics – Used to make inferences
regarding a population’s parameters

– Population parameters – Variable or quantified
characteristics of the entire population

• Factors influencing the choice of an
appropriate statistical technique

– Number of variables

– Scale of measurement

– Parametric versus nonparametric statistics

Univariate Statistical Tests

• Used to test hypotheses with propositions
about sample characteristics against given
standards

– Propositions are translated to null hypotheses

• Test one variable at a time

Bivariate Statistical Tests

• Test hypotheses that compare the
characteristics of two variables

• Types

– Chi-square

– t-test

– Analysis of variance

Cross-Tabulation

• Used in examining relationships and reporting
the findings for two variables

• Purpose – To determine if differences exist
between subgroups of the total sample

• Frequency distribution of responses on two or
more sets of variables

Chi-Square Analysis

• Assesses how closely the observed
frequencies fit the pattern of the expected
frequencies
– Referred to as a goodness-of-fit test

• Where,
– n – Number of cells

– i – Cell number

Comparing Means

• Independent samples: Two or more groups of
responses that are tested as though they may
come from different populations

• Related samples: Two or more groups of
responses from the sample population

Using the t-Test to Compare Two
Means

• t-test: Utilizes t distribution

– Used when the sample size is smaller than 30, and
the standard deviation is unknown

• Formula to calculate the value of t

– Where,

1 2

– Mean of sample 1

– Mean of sample 2

– Standard error of the difference between the two means

S X X

Analysis of Variance (ANOVA)

• ANOVA: Determines whether three or more
means are statistically different from one
another

– Null hypothesis

µ1 = µ2 = µ3

• F-test: Statistically evaluates the differences
between the group means in ANOVA

Analysis of Variance (ANOVA) (continued)

• Follow-up test: Flags the means that are
statistically different from each other

– Performed after an ANOVA determines that there
are differences between means

• n-way ANOVA: Analyzes several independent
variables at the same time

– Interaction effect: Multiple independent variables
in an ANOVA acting together to affect dependent
variable means

Figure 11.16 – n-Way ANOVA Means
Result

Descriptive Statistics

Dependent Variable:X24 — Likely to Recommend

x30 — Distance Driven… X32– Gender Mean Std. Deviation N

Less than 1 mile Male 4.39 .569 74

Female 3.67 .888 12

Total 4.29 .666 86

1 — 5 miles Male 3.78 .850 45

Female 3.68 1.077 31

Total 3.74 .943 76

More than 5 miles Male 3.00 .463 57

Female 2.65 .812 34

Total 2.87 .636 91

Total Male 3.78 .861 176

Female 3.22 1.059 77

Total 3.61 .960 253

Figure 11.16 – n-Way ANOVA Means
Result (continued)

Pairwise Comparisons

Dependent Variable:X24 — Likely to Recommend

(I) x30 — Distance

Driven to Restaurant

(J) x30 — Distance

Driven to Restaurant

Mean Difference

(l-J)

Std. Error Sig.-a

95% Confidence

Interval for

Difference*

95% Confidence
Interval for
Difference*
(I) x30 — Distance
Driven to Restaurant
(J) x30 — Distance
Driven to Restaurant
Mean Difference
(l-J)

Std. Error Sig.-a Lower Bound Upper Bound

Less than l mile 1 — 5 miles .302* .143 .035 .021 .582

More than 5 miles 1.206* .139 .000 .932 1.479

1 — 5 miles Less than 1 mile -.302* .143 .035 -.582 -.021

More than 5 miles .904* .117 .000 .674 1.134

More than 5 miles Less than 1 mile -1.206* .139 .000 -1.479 -.932

1 — 5 miles -.904* .117 .000 -1.134 -.674

Based on estimated marginal means

* The mean difference is significant at the .05 level.

a. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).

Perceptual Mapping

• Used to develop maps that illustrate the
perceptions of respondents

– Map – Two-dimensional visual representation

• Applications in marketing research

– New-product development

– Image measurement

– Advertising

– Distribution

Exhibit 11.18 – Perceptual Map of
Six Fast-Food Restaurants

Marketing Research in Action
Examining Restaurant Image Positions

• What are other areas of improvement for
Remington’s?

• Run post-hoc ANOVA tests between the
competitor groups

– What additional problems or challenges did this
reveal?

• What new marketing strategies can be
suggested?

Chapter 9

Qualitative Data
Analysis

Learning Objectives

• Contrast qualitative and quantitative data
analyses

• Explain the steps in qualitative data analysis

• Describe the processes of categorizing and
coding data and developing theory

• Clarify how credibility is established in
qualitative data analysis

• Discuss the steps involved in writing a
qualitative research report

Nature of Qualitative Data Analysis

• Accuracy of qualitative analysis is based on
the rigor of the process followed while
collecting and analyzing data

• Qualitative research is useful in providing
knowledge for decision makers

– Benefits research that aims to understand
psychoanalytical or cultural phenomena

Qualitative Versus Quantitative
Analyses

Qualitative data

• Textual and visual

• Goal – Increase
understanding

• Ongoing and iterative

• Employs member checking
– Member checking: Asking key

informants to read a
researcher’s report to verify
that the analysis is accurate

• Inductive in nature

Quantitative data

• Numerical

• Goal – Quantify the
magnitude of variables and
relationships

• Guided entirely by
researchers

• Describes categories,
themes, and patterns prior
to data collection

Exhibit 9.1 – Components of Data Analysis –
An Interactive Model

Data Reduction

• Categorization and coding of data

– Part of the theory development process in
qualitative data analysis

• Consists of interrelated processes

– Categorization and coding

– Theory building

– Iteration and negative case analysis

Steps in Data Reduction

• Categorization: Placing portions of transcripts
into similar groups based on their content

– Categories may be coded

• Code sheet: Document containing the themes or
categories of a particular study

• Codes: Labels or numbers used to track categories in a
qualitative study

• Comparison: Developing and refining theory
and constructs by analyzing differences and
similarities in themes or types of participants

Steps in Data Reduction

(continued 1)

• Integration: Process of moving from the
identification of themes and categories to the
development of a theory

– Recursive: Relationship in which a variable can
both cause and be caused by the same variable

– Selective coding: Building a storyline around a
core category

• Other categories are related or subsumed

Steps in Data Reduction

(continued 2)

• Iteration: Working through the data several
times to modify early ideas

– Memoing: Writing down thoughts as soon as
possible after each interview, focus group, or site
visit

• Negative case analysis

– Deliberately looking for cases and instances that
contradict the ideas and theories that researchers
have been developing

Role of Tabulation

• Use in qualitative analyses is controversial

– Tabulation of data may mislead readers

• Helps quantify themes that occur repeatedly

• Promotes honest research

Data Display

• Common types

– Table that explains central themes in a study

– Diagram that suggests relationships between
variables

– Matrix that includes quotes for various themes
from representative informants

Drawing Conclusions and Verifying
Results

• Data analysis is considered credible when the
results are valid and reliable

– Emic validity: Affirms that key members within a
culture or subculture agree with the findings of a
research report

– Cross-researcher reliability: Degree of similarity in
the coding of the same data by different
researchers

Drawing Conclusions and Verifying
Results (continued 1)

• Credibility: Degree of rigor, believability, and
trustworthiness established by qualitative
research

– Triangulation: Addressing the analysis from
multiple perspectives

• Multiple data collection and analysis methods

• Multiple data sets, researchers, and time periods

• Different kinds of relevant research informants

Drawing Conclusions and Verifying
Results (continued 2)

• Peer review: External qualitative methodology
or topic area specialists are asked to review a
research analysis

Exhibit 9.9 – Threats to Drawing Credible
Conclusions in Qualitative Analysis

• Salience of first impressions or of observations of highly concrete or

dramatic incidents.

• Selectivity which leads to overconfidence in some data, especially

when trying to confirm a key finding.

• Co-occurrences taken as correlations or even as causal

relationships.

• Extrapolating the rate of instances in the population from those

observed.

• Not taking account of the fact that information from some sources

may be unreliable.

Source: Adapted from Matthew B. Miles and A. Michael Huberman, Handbook of

Qualitative Research, An Expanded Sourcebook (Thousand Oaks, CA: Sage

Publications, 1994), p. 438.

Writing the Report

• Sections

– Introduction

• Research objectives

• Research questions

• Description of research methods

– Analysis of the data or findings

• Literature review and relevant secondary data

• Data displays

• Interpretation and summary of the findings

– Conclusions and recommendations

Writing the Report (continued 1)

• Components of the methodology section of a
qualitative report

– Topics covered and materials used in questioning

– Locations, dates, times, and context of
observation

– Number of researchers involved and degree of
involvement

– Procedure for choosing informants

– Number of informants and informant
characteristics

Writing the Report (continued 2)

– Number of focus groups, interviews, or transcripts

– Total number of pages, pictures, videos, and
researcher memos

– Procedures used to ensure systematic data
collection and analysis

– Procedures used for negative case analyses

– Limitations of methods

Writing the Report (continued 3)

• Analysis of the data or findings

– Sequence of reported findings is written in a
logical and persuasive manner

– Data displays that summarize, clarify, or provide
evidence for assertions are included with the
report

– Verbatims are used in textual reports and data
displays

• Verbatims: Quotes from research participants that are
used in research reports

Conclusions and
Recommendations

• Contain information that is relevant to the
research problem articulated by the client

• Some clients highly value the magnitude of
consumer response

– Researchers submit findings and suggest follow-up
research

Exhibit 9.10 – Making Recommendations Based on
Qualitative Research When Magnitude Matters

• “The qualitative findings give reason for optimism about market

interest in the new product concept… We therefore recommend that

the concept be further developed and formal executions be tested.”

• “While actual market demand may not necessarily meet the test of

profitability, the data reported here suggest that there is widespread

interest in the new device.”

• “The results of this study suggest that ad version #3 is most

promising because it elicited more enthusiastic responses and

because it appears to describe situations under which consumers

actually expect to use the product.“

Source: Alfred E. Goldman and Susan Schwartz McDonald. The Group Depth

Interview (Englewood Cliffs. N J: Prentice Hall, 1987). p. 176.

Marketing Research in Action
Understanding Product Dissatisfaction

• Write a two-page summary about a recent
unsatisfactory purchase experience

– Ten dissatisfaction summaries will be solicited
with the assistance of the instructor

• Analyze three product dissatisfaction
summaries as a group

– Identify categories, allot codes, and create a code
sheet

– Remaining seven summaries will be divided
among individuals in the group

Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education.
Marketing Research in Action
Understanding Product Dissatisfaction
(continued 1)

• Identify the similarities and differences in the
narratives

• Create a data display that summarizes the
findings

• Create an overarching concept by integrating
all themes

• Identify the techniques that help ensure
credibility, and explain how they achieve it

• Based on the group’s analysis, create a
presentation

– Include slides that address:

• Methodology

• Findings (including relevant verbatims and data
displays)

• Research limitations

• Conclusions and recommendations

What Will You Get?

We provide professional writing services to help you score straight A’s by submitting custom written assignments that mirror your guidelines.

Premium Quality

Get result-oriented writing and never worry about grades anymore. We follow the highest quality standards to make sure that you get perfect assignments.

Experienced Writers

Our writers have experience in dealing with papers of every educational level. You can surely rely on the expertise of our qualified professionals.

On-Time Delivery

Your deadline is our threshold for success and we take it very seriously. We make sure you receive your papers before your predefined time.

24/7 Customer Support

Someone from our customer support team is always here to respond to your questions. So, hit us up if you have got any ambiguity or concern.

Complete Confidentiality

Sit back and relax while we help you out with writing your papers. We have an ultimate policy for keeping your personal and order-related details a secret.

Authentic Sources

We assure you that your document will be thoroughly checked for plagiarism and grammatical errors as we use highly authentic and licit sources.

Moneyback Guarantee

Still reluctant about placing an order? Our 100% Moneyback Guarantee backs you up on rare occasions where you aren’t satisfied with the writing.

Order Tracking

You don’t have to wait for an update for hours; you can track the progress of your order any time you want. We share the status after each step.

Order Now Talk to Us

Areas of Expertise

Although you can leverage our expertise for any writing task, we have a knack for creating flawless papers for the following document types.

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Areas of Expertise

Although you can leverage our expertise for any writing task, we have a knack for creating flawless papers for the following document types.

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Trusted Partner of 9650+ Students for Writing

From brainstorming your paper's outline to perfecting its grammar, we perform every step carefully to make your paper worthy of A grade.

Preferred Writer

Hire your preferred writer anytime. Simply specify if you want your preferred expert to write your paper and we’ll make that happen.

Grammar Check Report

Get an elaborate and authentic grammar check report with your work to have the grammar goodness sealed in your document.

One Page Summary

You can purchase this feature if you want our writers to sum up your paper in the form of a concise and well-articulated summary.

Plagiarism Report

You don’t have to worry about plagiarism anymore. Get a plagiarism report to certify the uniqueness of your work.

Free Features $66FREE

Most Qualified Writer $10FREE
Plagiarism Scan Report $10FREE
Unlimited Revisions $08FREE
Paper Formatting $05FREE
Cover Page $05FREE
Referencing & Bibliography $10FREE
Dedicated User Area $08FREE
24/7 Order Tracking $05FREE
Periodic Email Alerts $05FREE

Our Services

Join us for the best experience while seeking writing assistance in your college life. A good grade is all you need to boost up your academic excellence and we are all about it.

On-time Delivery
24/7 Order Tracking
Access to Authentic Sources

Academic Writing

We create perfect papers according to the guidelines.

Professional Editing

We seamlessly edit out errors from your papers.

Thorough Proofreading

We thoroughly read your final draft to identify errors.

Thorough Proofreading

We thoroughly read your final draft to identify errors.

Delegate Your Challenging Writing Tasks to Experienced Professionals

Work with ultimate peace of mind because we ensure that your academic work is our responsibility and your grades are a top concern for us!

Check Out Our Sample Work

Dedication. Quality. Commitment. Punctuality

It May Not Be Much, but It’s Honest Work!

Here is what we have achieved so far. These numbers are evidence that we go the extra mile to make your college journey successful.

0+

Happy Clients

0+

Words Written This Week

0+

Ongoing Orders

0%

Customer Satisfaction Rate

Process as Fine as Brewed Coffee

We have the most intuitive and minimalistic process so that you can easily place an order. Just follow a few steps to unlock success.

Call Us +1 (877) 657-8180 Discuss Order Details Now

See How We Helped 9000+ Students Achieve Success

We Analyze Your Problem and Offer Customized Writing

We understand your guidelines first before delivering any writing service. You can discuss your writing needs and we will have them evaluated by our dedicated team.

Clear elicitation of your requirements.
Customized writing as per your needs.

We Mirror Your Guidelines to Deliver Quality Services

We write your papers in a standardized way. We complete your work in such a way that it turns out to be a perfect description of your guidelines.

Proactive analysis of your writing.
Active communication to understand requirements.

We Handle Your Writing Tasks to Ensure Excellent Grades

We promise you excellent grades and academic excellence that you always longed for. Our writers stay in touch with you via email.

Thorough research and analysis for every order.
Deliverance of reliable writing service to improve your grades.

Place an Order Start Chat Now

Marketing Research 8

What Will You Get?

Premium Quality

Experienced Writers

On-Time Delivery

24/7 Customer Support

Complete Confidentiality

Authentic Sources

Moneyback Guarantee

Order Tracking

Areas of Expertise

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Areas of Expertise

Essay

Thesis

Presentation

Dissertation

Term Paper

Research Paper

Book Review

Assignment

Report

Case Study

Letter

Article

Coursework

Speech

Q & A

Critical Thinking

Trusted Partner of 9650+ Students for Writing

Preferred Writer

Grammar Check Report

One Page Summary

Plagiarism Report

Free Features $66FREE

Our Services

Academic Writing

Professional Editing

Thorough Proofreading

Thorough Proofreading

Delegate Your Challenging Writing Tasks to Experienced Professionals

Check Out Our Sample Work

It May Not Be Much, but It’s Honest Work!

0+

Happy Clients

0+

Words Written This Week

0+

Ongoing Orders

0%

Customer Satisfaction Rate

Process as Fine as Brewed Coffee

Share Your Requirements

Place Order & Deposit Funds

Release Payment to Your Writer

See How We Helped 9000+ Students Achieve Success

We Analyze Your Problem and Offer Customized Writing

We Mirror Your Guidelines to Deliver Quality Services

We Handle Your Writing Tasks to Ensure Excellent Grades