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Bmgt 311 chapter_12

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BMGT 311: Chapter 12 Using Descriptive Analysis, Performing Population Estimates, and Testing Hypotheses
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Page 1: Bmgt 311 chapter_12

BMGT 311: Chapter 12

Using Descriptive Analysis, Performing Population Estimates, and Testing Hypotheses

Page 2: Bmgt 311 chapter_12

Learning Objectives

• To learn about the concept of data analysis and the functions it provides

• To appreciate the five basic types of statistical analysis used in marketing research

• To use measures of central tendency and dispersion customarily used in describing data

• To understand the concept of statistical inference 

• To learn how to estimate a population mean or percentage

• To test a hypothesis about a population mean or percentage

Page 3: Bmgt 311 chapter_12
Page 4: Bmgt 311 chapter_12

Types of Statistical Analyses Used in Marketing Research

• Descriptive analysis

• Inferential analysis

• Differences analysis

• Associative analysis

• Predictive analysis

Page 5: Bmgt 311 chapter_12

Descriptive Analysis

• Used by marketing researchers to describe the sample dataset in such a way as to portray the “typical” respondent and to reveal the general pattern of responses

Page 6: Bmgt 311 chapter_12

Inference Analysis

• Used when marketing researchers use statistical procedures to generalize the results of the sample to the target population it represents

Page 7: Bmgt 311 chapter_12

Difference Analysis

• Used to determine the degree to which real and generalizable differences exist in the population to help the manager make an enlightened decision on which advertising theme to use

Page 8: Bmgt 311 chapter_12

Association Analysis

• Investigates if and how two variables are related

Page 9: Bmgt 311 chapter_12

Predictive Analysis

● Statistical procedures and models to help make forecasts about future events ● Big data is making this

highly accurate ● This is the future of

marketing and research

Page 10: Bmgt 311 chapter_12
Page 11: Bmgt 311 chapter_12

Understanding Data via Descriptive Analysis

• Two sets of measures are used extensively to describe the information obtained in a sample.

• Measures of central tendency or measures that describe the “typical” respondent or response

• Measures of variability or measures that describe how similar (dissimilar) respondents or responses are to (from) “typical” respondents or responses

Page 12: Bmgt 311 chapter_12

Measures of Central Tendency: Summarizing the “Typical” Respondent

• The basic data analysis goal involved in all measures of central tendency is to report a single piece of information that describes the most typical response to a question.

• Central tendency applies to any statistical measure used that somehow reflects a typical or frequent response.

Page 13: Bmgt 311 chapter_12

Measures of Central Tendency: Summarizing the “Typical” Respondent

• Measures of central tendency:

• Mode: a descriptive analysis measure defined as that value in a string of numbers that occurs most often

• Median: expresses that value whose occurrence lies in the middle of an ordered set of values

• Mean (or average):

Page 14: Bmgt 311 chapter_12

Measures of Variability: Visualizing the Diversity of Respondents

• All measures of variability are concerned with depicting the “typical” difference between the values in a set of values.

• There are three measures of variability:

• Frequency distribution

• Range

• Standard deviation

Page 15: Bmgt 311 chapter_12

Measures of Variability: Visualizing the Diversity of Respondents

• A frequency distribution is a tabulation of the number of times that each different value appears in a particular set of values.

• The conversion is accomplished simply through a quick division of the frequency for each value by the total number of observations for all values, resulting in a percent, called a percentage distribution.

Page 16: Bmgt 311 chapter_12

Measures of Variability: Visualizing the Diversity of Respondents

• Range: identifies the distance between lowest value (minimum) and the highest value (maximum) in an ordered set of values

• Standard deviation: indicates the degree of variation or diversity in the values in such a way as to be translatable into a normal or bell-shaped curve distribution

Page 17: Bmgt 311 chapter_12
Page 18: Bmgt 311 chapter_12

Coding Data and the Data Code Book

• Typical Question: How satisfied are you with the gas mileage in the Ford Fiesta

Highly Satisfied Satisfied Somewhat

Satisfied

Neither Satisfied or dissatisfied

Somewhat Dissatisfied Dissatisfied Not Satisfied

at all

Page 19: Bmgt 311 chapter_12

Coding Data and the Data Code Book

• Once the items are coded - you can build a frequency distribution table

Highly Satisfied Satisfied Satisfied

Neither Satisfied or dissatisfied

Somewhat Dissatisfied Dissatisfied Not Satisfied

at all

7 6 5 4 3 2 1

Page 20: Bmgt 311 chapter_12

Building the Frequency Distribution

Satisfaction Rating Count

7 2

6 2

5 4

4 2

3 0

2 0

1 0

Total 10

Frequency: Number of times a number (response) is in the data set

Frequency Distribution: Summary of how many times each possible response

to a question appears in the data set

Page 21: Bmgt 311 chapter_12

Building the Frequency Distribution

Satisfaction Rating Count Sum

7 2 14

6 2 12

5 4 20

4 2 8

3 0

2 0

1 0

Total 10 54

Mean 5.4

Mean: Arithmetic Average of all responses

!(7+5+6+4++6+5+7+5+4+5) = 54

!54/10 = 5.4

Page 22: Bmgt 311 chapter_12

Building the Frequency Distribution

Satisfaction Rating Count Sum Percentage

7 2 14 20%

6 2 12 20%

5 4 20 40%

4 2 8 20%

3 0 0

2 0 0

1 0 0

Total 10 54

5.4

Percentage = Frequency/total count

Page 23: Bmgt 311 chapter_12

Building the Frequency Distribution

Satisfaction Rating Count Sum Percentage Cumulative %

7 2 14 20% 20%

6 2 12 20% 40%

5 4 20 40% 80%

4 2 8 20% 100%

3 0 0

2 0 0

1 0 0

Total 10 54

5.4

Cumulative Percentage = Each individual percentage added to the

previous to get a total

Page 24: Bmgt 311 chapter_12

Building the Frequency Distribution

Median: Descriptive statistic that splits the data into a hierarchal

pattern where half the data is above the median value and half is below

!Look for 50% or what includes

50% in the cumulative %

Median = 5

Satisfaction Rating Count Sum Percentage Cumulative %

7 2 14 20% 20%

6 2 12 20% 40%

5 4 20 40% 80%

4 2 8 20% 100%

3 0 0

2 0 0

1 0 0

Total 10 54

5.4

Page 25: Bmgt 311 chapter_12

Building the Frequency Distribution

Mode: Most Frequently occurring response to a given set of questions

Satisfaction Rating Count Sum Percentage Cumulative %

7 2 14 20% 20%

6 2 12 20% 40%

5 4 20 40% 80%

4 2 8 20% 100%

3 0 0

2 0 0

1 0 0

Total 10 54

5.4

Mode = 5

Page 26: Bmgt 311 chapter_12

Building the Frequency Distribution

Range: Statistic that represents the spread of the data and the distance

between the largest and smallest values of a frequency distribution

Range = 7 - 4 = 3

Satisfaction Rating Count Sum Percentage Cumulative %

7 2 14 20% 20%

6 2 12 20% 40%

5 4 20 40% 80%

4 2 8 20% 100%

3 0 0

2 0 0

1 0 0

Total 10 54

5.4

Page 27: Bmgt 311 chapter_12

Descriptive Analysis: Building the Distribution Table from a real life example

• Example Question from a Survey:

• Question: Overall, how satisfied are you with the Real World Experience Adjunct Professors bring to the table here at Point Park University

Highly Satisfied Satisfied Somewhat

Satisfied

Neither Satisfied or dissatisfied

Somewhat Dissatisfied Dissatisfied Not Satisfied

at all

7 6 5 4 3 2 1

Page 28: Bmgt 311 chapter_12

Step 1: Collect the Raw Data

Respondent Number Satisfaction Rating

12

3

4

5

6

7

8

9

1011

Highly Satisfied Satisfied Somewhat

Satisfied

Neither Satisfied or dissatisfied

Somewhat Dissatisfied Dissatisfied Not Satisfied

at all

7 6 5 4 3 2 1

Page 29: Bmgt 311 chapter_12

Distribution Table: Fill in Data Sets

• Record the Data

• Mean =

• Mode =

• Median =

• Range =

Satisfaction Rating

Count Sum Percentage Cumulative %

7 0 0 0% 0%

6 0 0 0% 0%

5 0 0 0% 0%

4 0 0 0% 0%

3 0 0 0% 0%

2 0 0 0% 0%

1 0 0 0% 0%

Total 11 0

Mean 0.00

Page 30: Bmgt 311 chapter_12

Class Work: Try to Develop a Distribution Table from the following Data Sets

Page 31: Bmgt 311 chapter_12

• Question: Overall, how satisfied are you with the cafe food at Point Park University?

Respondent Number Satisfaction Rating

1 3

2 4

3 2

4 1

5 3

6 1

7 2

8 2

Highly Satisfied Satisfied Somewhat

Satisfied

Neither Satisfied or dissatisfied

Somewhat Dissatisfied Dissatisfied Not Satisfied

at all

7 6 5 4 3 2 1

Page 32: Bmgt 311 chapter_12

In Class Example #2

• What is the mean?

• What is the median?

• What is the mode?

• What was the range? What does this tell you?

• Overall, what do these results tell you? What would you recommend?

Page 33: Bmgt 311 chapter_12

Hypothesis Tests

• Tests of an hypothesized population parameter value:

• Test of an hypothesis about a percent

• Test of an hypothesis about a mean

• The crux of statistical hypothesis testing is the sampling distribution concept.

Page 34: Bmgt 311 chapter_12

Hypothesis Tests

Page 35: Bmgt 311 chapter_12

Hypothesis Tests: Example: Page 314 and 315

• Rex hypothesizes interns will make about $2,750 their first semester

• Sample Survey:

• n=100 (Total Students Surveyed)

• Sample Mean = $2,800

• Standard Deviation = $350

• Does his hypothesis support this?

Page 36: Bmgt 311 chapter_12

Hypothesis Tests: Example: Page 314 and 315

• z = (x - u)/standard error of the mean

• z = (2,800 - 2,750)/350/Sq Root 100

• z = 50/35 = 1.43

• Is this Hypothesis Supported? Yes. Why?

Page 37: Bmgt 311 chapter_12

Hypothesis Tests: Example: Page 314 and 315

Page 38: Bmgt 311 chapter_12

Hypothesis Tests: Example: Page 314 and 315


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