****PROTEACH**** INDV PRJT 4

Research Study

This week, you will get to put all of your research together.

Part 1: Previous Work

Part 1 of the Individual Project should be copied and pasted from your previous work along with the internal citations. Be sure to add corresponding entries to the reference list.

Part 2: Data Analysis

Students should complete the following for the rest of this assignment:

  • Using Excel, create the following demographics, charts, and tables:A pie chart for gender (add a written description below it)A chart for each of the other 2 demographics (add a written description below each)Descriptive statistics of the 4 factors (add a written description below them)
  • Add the data analysis from your previous work, as detailed in the Unit 4 IP.
  • Create 2 hypotheses that require correlation analysis and 2 hypotheses that should be tested with regression analysis. Use the small set of datathat has been collected from brand-loyal customers of stores 1 and 2 in the Unit 4 IP Template ZIP file. Include the following:Write out a null hypothesis and an alternate hypothesis.Run 2 correlations and 2 regressions to test the null hypotheses.State the decision for each of the Excel tests.Compare the results from the t-tests and the ANOVAs.

Part 2 of the Individual Project will vary in length based on the size of Excel output.

Part 3: Findings and Segmentation Applications

Using the qualitative and quantitative tools that are used to assess service quality and segmentation in the stores, answer the following question:

  • How can a marketing manager use these results to build a segmentation strategy in 1 of the target stores? 

Part 3 of the Individual Project will be 1 page.

Your assignment should contain a cover page, an abstract page, and a reference page in addition to the body. The body of the paper should be 5 pages, starting with a brief 1-paragraph introduction and ending with a short conclusion. The entire submission will be 8–10 pages.

Click on Student Expectations to view the expectations for this assignment.

Please submit your assignment as a Word document in APA format using the attached 

TEMPLATE

. Notice that the grading criteria components match up with the headings provided in the template. Do NOT change the font, page breaks, or margins. Using the template without deleting the headings ensures that you cover each segment of the assignment.

For assistance with your assignment, please use your text, Web resources, and all course materials.

Unit Materials

U4 IP.sav

MKTG420_U4IP
Unit 4 Individual Project 1

MACROBUTTON DoFieldClick Type your Name Here
American Intercontinental University

MACROBUTTON DoFieldClick Type your Paper Title
Project Type: MKTG420 Unit 4 Individual Project
MACROBUTTON DoFieldClick Date of Submission

Abstract

This is a single paragraph, no indentation is required. The next page will be an abstract; “a brief, comprehensive summary of the contents of the article; it allows the readers to survey the contents of an article quickly” (Publication Manual, 2010). The length of this abstract should be 35-50 words (2-3 sentences). NOTE: the abstract must be on page 2 and the body of the paper will begin on page 3.

MACROBUTTON DoFieldClick Type your Paper Title

Introduction

Remember to always indent the first line of a paragraph (use the tab key). The introduction should be short (2-3 sentences). The margins, font size, spacing, and font type (italics or plain) are set in APA format. While you may change the names of the headings and subheadings, do not change the font.

Store Profiles

This content is from Unit 1 IP, Part 1.

Company Research

This content is from Unit 1 IP, Part 1.

Theory-Based Research on Marketing Segmentation

This content is from Unit 1 IP, Part 2.

Cost-Benefit Analysis of Investing in Segmentation Research

This content is from Unit 1 IP, Part 2.

Results of Focus Group

This content is from Unit 2 DB Main Post.

2 SPSS Frequency Tables

This content is from Unit 2 DB Main Post.

Analysis of Focus Group

This content is from Unit 2 DB Main Post.

Web vs. Store #1

This content is from Unit 2 IP, Part 1.

Web vs. Store #2

This content is from Unit 2 IP, Part 1.

Rating System

This content is from Unit 2 IP, Part 1.

Store #1 Image and Target Market Fit

This content is from Unit 2 IP, Part 2.

Store #2 Image and Target Market Fit

This content is from Unit 2 IP, Part 2.

Most successful store with rationale

This content is from Unit 2 IP, Part 2.

Support for Improvements

This content is from Unit 2 IP, Part 3.

Three Improvements for Store #1

This content is from Unit 2 IP, Part 3.

Three Improvements for Store #2

This content is from Unit 2 IP, Part 3.

Part 1: Research on the Survey

This content is from Unit 3 IP, Part 1.

Research background on the scales

This content is from Unit 3 IP, Part 1.

SERVQUAL samples

This content is from Unit 3 IP, Part 1.

Service Quality and Segmentation

This content is from Unit 3 IP, Part 1.

Chart #1: Gender

INSERT CHART HERE

Description of chart #1: gender.

Insert your written description of the table pasted above.

Chart #2: xx

INSERT CHART HERE

Description of chart #2: xx.

Insert your written description of the table pasted above.

Chart #3: xx

INSERT CHART HERE

Description of chart #3: xx.

Insert your written description of the table pasted above.

Table #4: Factors

INSERT TABLE HERE

Description of table #4: factors.

Insert your written description of the table pasted above.

Null/Hypo, Independent Sample T-Test 1, Decision

From Unit 2 IP, Part 2

Null/Hypo, Independent Sample T-Test 2, Decision

From Unit 2 IP, Part 2

Null/Hypo, Independent Sample T-Test 3, Decision

From Unit 2 IP, Part 2

Null/Hypo, Independent Sample T-Test 4, Decision

From Unit 2 IP, Part 2

Null/Hypo, ANOVA 1, Decision

From Unit 3 IP, part 3

Null/Hypo, ANOVA 2, Decision

From Unit 3 IP, part 3

Null/Hypo, ANOVA 3, Decision

From Unit 3 IP, part 3

Null/Hypo, ANOVA 4, Decision

From Unit 3 IP, part 3

Compare ANOVA & t-test results

From Unit 3 IP, part 3

Hypothesis Test -Correlation #1

Null and alternate hypotheses.

Write out a Null & Alternate Hypothesis (alpha = .05).

The test.

Run the test and paste it in the document

The decision rule.

State the decision rule.

Hypothesis Test -Correlation #2

Null and alternate hypotheses.

Write out a Null & Alternate Hypothesis (alpha = .05).

The test.

Run the test and paste it in the document

The decision rule.

State the decision rule.

Hypothesis Test -Regression #1

Null and alternate hypotheses.

Write out a Null & Alternate Hypothesis (alpha = .05).

The test.

Run the test and paste it in the document

The decision rule.

State the decision rule.

Hypothesis Test -Regression #1

Null and alternate hypotheses.

Write out a Null & Alternate Hypothesis (alpha = .05).

The test.

Run the test and paste it in the document

The decision rule.

State the decision rule.

Compare Correlation, Regression, ANOVA and t-Test Results

From Unit 3 IP, part 3

Findings and Segmentation Applications

You now have used qualitative and quantitative tools to assess service quality and segmentation in the stores. How can a marketing manager use these results to build a segmentation strategy in one of the target stores. Part 3 of the Individual Project will be 1 page in length.

Conclusion

Add some concluding remarks-can be a sentence or two.

References

NOTE: The reference list starts on a new page after your conclusion.

U4 IP SPSS Help

Rules for Forming Hypotheses

A (alternative) hypothesis is a statement of what you believe based on deductive
reasoning. The null hypothesis, which is the opposite of the hypothesis, is tested in hopes
that it can be REJECTED, thereby implying the other hypothesis can be supported (NOTICE
we do not say true, false or proven).

In journal articles, if only one hypothesis is shown, it is usually the HYPOTHESIS. We are
really interested in the hypothesis, but the rules of statistics dictate that we test the null
hypothesis.

You only test concepts that are measured by your Surveys (the FACTORS**)

A survey is made up of questions. The questions will either measure a demographic (a label
describing a person, thing). Examples would be gender, education, age, tenure, etc.
OR
They are questions that when put together (either averaged or summed) measure an
abstract concept…we call this a scale or factor score (The individual portion of the U4 Group
Assignment).

When writing hypotheses, you do not compare on a single question, but rather a concept or
factor/scale. If you measure a single question in a hypothesis for the project, you will get
the whole question wrong. Each hypothesis must contain a comparison of one of the factors
in your scale. You can compare two different factors or a factor plus a demographic (for
example).

Wording for Correlations & Regressions:
NULL: This is no relationship (correlation) between _____________________ and gender.
HYPO: This is a relationship between (correlation) _____________________ and gender.

 With correlations and especially regressions, you can have more than one factor
compared.

WORDING FOR DECISION RULE….

These are not tests, but words to describe the Reject/Do Not Reject Status

p-VALUE approach

Given that the sig. (xx) is greater than the alpha (.xx), the NULL cannot be rejected therefore
there is no support for the HYPO that (paste HYPO here)
OR

Given that the sig. (xx) is less than the alpha (.xx), the NULL is rejected therefore there is
support for the HYPO that (paste HYPO here)

Let us NOW look for the wording of the decision rule

A TOTALLY DIFFERENT SURVEY IS BEING USED….

Given that the sig. xx is less than the alpha of .05, the NULL hypothesis is rejected and
therefore there is support for the HYPO that (insert HYPO)

Given that the sig. xx is greater than the alpha of .05, the NULL hypothesis is not rejected
and therefore there is no support for the HYPO that (insert HYPO)

Don’t get fancy and start using words like the HYPO is accepted or is true…just stay with
these simple phrases…and remember-there are no absolutes in this HYPO testing
game…that is why we use the concept of SUPPORT for a hypothesis.

CORRELATION:

“Flag Significant Correlations”- this is a great tool since it tells you when to reject!!

REGRESSION

FYI- when you run a regression, be sure to request an ANOVA table under options. This way
you know when to reject!

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