Mr Final

Front 1

Name the 6 Characteristics of Qualitative Data Analysis.

Back 1

1) Data is textual/visual (not numerical)
2) Goal is understanding
3) Analyses are on-going and iterative
4) Member checking is used
5) Approach is inductive
6) Need to establish credibility

Front 2

Define Member Checking.

Back 2

Asking key people to read the researcher’s report to verify that the analyses are right.

Front 3

Define Thick Description.

Back 3

An ethnographic research report that related behavior within a culture or subculture.
-Explain consumer behavior better than other methods because it connects behaviors to social contexts.

Front 4

Name the 4 Steps of Data Analysis

Back 4

1) Data Collection
2) Data Display
3) Data Reduction
4) Conclusion Drawing

Front 5

What does Data Reduction Involve?

Back 5

Involves:
-Categorization and coding of data
-Theory development
-Iteration and negative case analysis

Front 6

Name 4 Ways of Data Reduction

Back 6

-Categorization
-Coding
-Comparison
-Tabulation

Front 7

Define Categorization.

Back 7

Putting parts of transcripts into similar groups based on content.

Front 8

Define Code Sheet.

Back 8

List of the different themes or categories for a study.

Front 9

Define Codes.

Back 9

Labels or numbers that are used to track categories in a study.

Front 10

Define Comparison.

Back 10

Process of developing and refining theory and constructs by analyzing the differences and similarities in passages, themes or participants.

Front 11

Define Integration.

Back 11

The process of moving from identifying themes and categories to developing a theory.

Front 12

Define Recursive.

Back 12

Relationship where a variable can both cause and be caused by the same variable.

Front 13

Define Selective Coding.

Back 13

Building a report around one main category or theme; the other categories will be related to this central category.

Front 14

Define Iteration.

Back 14

Going over the data many times in order to modify early ideas and to be informed by later analyses.

Front 15

Define Memoing.

Back 15

Writing down thoughts asap after each interview, etc

Front 16

Define Negative Case Analysis.

Back 16

Intentionally looking for cases and instances that contradict the ideas and theories that researchers have been developing.

Front 17

Define Emic Validity

Back 17

Verifies that the key members within a culture agree with the findings of a research report.

Front 18

Define Cross-Researcher Reliability

Back 18

The degree of similarity in the coding of the same data by different researchers.

Front 19

Define Triangulation.

Back 19

-Multiple methods of data collection and analysis
-Multiple data sets
-Multiple researchers analyzing data
-Data collection in multiple time periods
-Providing selective breadth in informants

Front 20

Name the 3 Major Parts of Writing a Report

Back 20

1) Introduction
-Objectives
-Questions
-Description of methods
2) Analysis of data/findings
-Literature review/secondary data
-Findings displayed in tables or charts
-Interpretation and summary of findings
3) Conclusion/Recommendations

Front 21

Name the 4 Steps in the Data Preparation Process.

Back 21

1) Data Validation

2) Editing and Coding

3) Data Entry

4) Data Tabulation

Front 22

Define Data Validation.

Back 22

Process of determining whether a survey’s interviews or observations were done right and are free of fraud/bias.

Front 23

Define Curbstoning.

Back 23

Cheating or falsification in the data collection process.

Front 24

Name the 5 Primary Areas Where Validation is a Concern.

Back 24

1) Fraud

2) Screening

3) Procedure

4) Completeness

5) Courtesy

Front 25

Name 5 Factors that Aid in Error Detection.

Back 25

1) Validation

2) Editing and Coding

3) Data Entry

4) Data Tabulation

5) Data Analysis

Front 26

Define Editing.

Back 26

Checking raw data for mistakes made by the interviewer or respondent.

Front 27

Name the 4 Steps Involved with Developing Response Codes.

Back 27

1) Generate list of potential responses and assign values.

2) Consolidate responses

3) Assign numerical value as a code

4) Assign a coded value to each response

Front 28

Define Data Entry.

Back 28

Input of the coded data into software that will let the researcher transform the raw data into useful information.

Front 29

Name 3 Methods of Error Detection

Back 29

1) Software “error edit routines”
-Identify the wrong type of data

2) Scan the actual data that was entered

3) Produce a data/column list procedure for the entered data

Front 30

Define One-Way Tabulation.

Back 30

Categorization of a single variable in a study.

Front 31

How is One-Way Tabulation Used?

Back 31

Used to calculate summary statistics on questions: Averages, Standard Deviations, Percentages.

Front 32

How is One-Way Tabulation Shown?

Back 32

Show OWT by constructing a One-Way Frequency table.

Front 33

Define Cross-Tabulation.

Back 33

Categorization of respondents by 2+ variables in the study.
-Categorizing the number of respondents who have answered 2+ questions in a row.

Front 34

What is the Purpose of Cross-Tabulation?

Back 34

Determine if certain variables differ when compared among various subgroups of the total sample.
(main form of data analysis in research projects)

Front 35

Define Measures of Central Tendency.

Back 35

Mean, median and mode all describe the center of the distribution of a set of values.

Front 36

Define Mean.

Back 36

Arithmetic average. All values are added up / # of valid responses.
→Used for interval or ratio data.

Front 37

Define Mode.

Back 37

Most frequently occurring value in a distribution of values.
→Used for nominal data.

Front 38

Define Median.

Back 38

Middle value of a ordered set of values.
→Used for ordinal data

Front 39

Define Measures of Dispersions.

Back 39

Describes how close values fall to the mean or other measures of central tendency.

Front 40

Name 2 Measures of Dispersion.

Back 40

1) Range
2) Standard Deviation

Front 41

Define Range.

Back 41

Distance between the smallest and largest value in a set.

Front 42

Define Standard Deviation.

Back 42

The average distance of the distribution values from the mean.

Front 43

Define Variance.

Back 43

The standard deviation squared.

Front 44

List 3 Things to Consider When Selecting a Stat Technique.

Back 44

1) # of variables

2) Scale of measurement

3) Parametric v. non-parametric stats

Front 45

Name 2 Univariate Tests of Significance.

Back 45

1) Z-Test
2) T-Test
→Appropriate for interval or ratio data.

Front 46

What do Bivariate Statistical Tests do?

Back 46

Compare characteristics of 2 groups or 2 variables

Front 47

Define Chi-Square Analysis.

Back 47

Test for stat significance between the FDs of 2+ variables in a cross-tabulation table to determine if there is any association between the variables.

Front 48

Define Independent Samples.

Back 48

2 or more groups of responses that are tested as though they may come from different populations.

Front 49

Define Related Samples.

Back 49

2 or more groups of responses that came from the sample population.

Front 50

What is the T-Test Used For?

Back 50

Tells the difference between two means.

Used when the sample size is less than 30 and the SD is unknown.

Front 51

Define Analysis of Variance (ANOVA).

Back 51

Determines if 3+ means are statistically different from each other.

Front 52

Define F-Test.

Back 52

The test used to statistically evaluate the differences between the group means in ANOVA

Front 53

When should N-Way ANOVA be used?

Back 53

-Multiple independent variables

-Experimental designs with groups of multiple variables

Front 54

Define Perceptual Mapping.

Back 54

Process that is used develop maps showing the perceptions of respondents. The map visually represents respondent perceptions in 2 dimensions.

Front 55

Name 4 Ways to Describe the Relationship Between Variables

Back 55

1) Presence

2) Direction

3) Strength of Association

4) Type

Front 56

Define Linear Relationship.

Back 56

Association between 2 variables where the relationship remains the same over the range of both variables.

Front 57

Define Curvilinear Relationship.

Back 57

Association between 2 variables where the strength and/or direction of their relationship changes over the range of both variables.

Front 58

Define Covariation.

Back 58

Amount of change in one variable that is consistently related to the change in another variable.

Front 59

Explain What a Scatter Diagram Does.

Back 59

Graphically shows the relative position of 2 variables using a horizontal and a vertical axis to represent the variable values.

Front 60

Define Correlation Analysis/ Pearson Correlation Coefficient.

Back 60

Measure of the strength of a linear relationship between 2 variables.

Front 61

Explain Coefficient of Determination (r2).

Back 61

A number measuring the proportion of variation in one variable accounted for by another.
-Think of r2 as a percentage and varies from 0.0 to 1.00

Front 62

Define Spearman Rank Order Correlation Coefficient.

Back 62

Statistical measure of the linear association between 2 variables. Both have been measured using ordinal (rank order) scales.

Front 63

Define Regression Analysis.

Back 63

Getting more detailed answers (predictions) than can be provided by the correlation coefficient.

Front 64

Define Bivariate Regression Analysis.

Back 64

Analyzing the linear relationship between 2 variables by estimating coefficients for an equation for a straight line.
Variable (A) is designated as a dependent variable, and Variable (B) as an independent variable.

Front 65

Define Least Squares Procedure.

Back 65

Regression that determines the line of best fit by minimizing the distances between all the points on the line.

Front 66

Define Unexplained Variance.

Back 66

The amount of variation in the dependent construct that cannot be accounted for by the combination of independent variables

Front 67

Define Regression Coefficient.

Back 67

Indicated the importance of an independent variable in predicting a dependent variable. Large Coeffs are good, small coeffs are weak.

Front 68

Define Ordinary Least Squares.

Back 68

Estimating regression equation coefficients which produce the lowest sum of squared differences between the actual and predicted values of the dependent variable

Front 69

Define Multiple Regression Analysis.

Back 69

Analyzing the linear relationships between a dependent variable and multiple independent variables by estimating coefficients for the equation for a straight line.

Front 70

Define Beta Coefficient.

Back 70

Estimated regression coefficient that has been recalculated to have a mean of 0 and a standard deviation of 1.
This lets the independent variables with different units of measurement to be directly compared to the dependent variable.

Front 71

Define Multicollinearity.

Back 71

A situation in which several independent variables are highly correlated with each other. This characteristic can result in difficulty in estimating separate or independent regression coefficients for the correlated variables.

Front 72

Objectives of Marketing Research Reports

Back 72

-Communicate findings of project
-Provide interpretations of findings
-Illustrate credibility of the research project
-Serve as a future reference document for future decisions

Front 73

Major Topics to Include in Your Report

Back 73

-Research objectives
-Research questions
-Literature review
-Research methods
-Findings
-Interpretation and summary
-Conclusion and recommendations

Front 74

Name 3 Ways to Enhance Credibility

Back 74

1) Accuracy
2) Believable
3) Professionally organized

Front 75

Format for Marketing Research Reports

Back 75

1) Title page
2) Table of contents
3) Executive summary
-Research objectives
-Statement of method
-Key findings
-Conclusion/ recommendations
4) Introduction
5) Research methods and procedures
-Research design used
-Types of secondary data
-Data collection procedures
-Sampling and sampling processes
6) Data analysis and findings
7) Conclusions and recommendations
8) Limitations
9) Appendices

Front 76

Define Appendix.

Back 76

A section at the end of the final research report used to house complex, detailed, or technical information.

Front 77

Define Believability.

Back 77

Achieved by building a final report that is based on clear, logical thinking, precise expression, and accurate presentation.

Front 78

Define Credibility.

Back 78

Achieved by developing a final report that is accurate, believable, and professionally organized.

Front 79

Define Executive Summary.

Back 79

The part of the final research report that illustrates the major points of the report in a manner complete enough to provide a true representation of the entire document.

Front 80

Define Introduction.

Back 80

Contains background information that is necessary to understand the report.

Front 81

Define Limitations.

Back 81

A section of the final research report where all extra events that have certain restrictions on the report are fully communicated.

Front 82

Define Methods and Procedures.

Back 82

Communicates how the research was conducted.

Front 83

Name 5 Common Problems in Preparing Reports.

Back 83

1) Lack of data interpretation
2) Unnecessary use of multivariate statistics
3) Emphasis on packaging instead of quality
4) Lack of relevance
5) Placing too much emphasis on a few statistics