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Unit 3 Individual Project 1

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American Intercontinental University

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Project Type: MKTG420 Unit 3 Individual Project

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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.

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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.

Part 1: Research background on the scales

Introduce the concept and be sure to indent the first line of the paragraph. Provide background on each of the 4 scales (assurance, empathy, reliability and responsiveness), not limited to a simple definition but as a measurement that aids marketers. Discuss how the questions in the survey are transformed into "scales" (also called "factors"). In other studies using SERVQUAL, how many and what types of respondents were included? Part 1 of the Individual Project should be 1 page in length. Be sure to cite your resources.

Part 1: Concept of Scales/Factors

Introduce the concept and be sure to indent the first line of the paragraph.

Part 1: SERVQUAL Samples

Introduce the concept and be sure to indent the first line of the paragraph.

Part 2: (Full-Text Research) Service Quality and Segmentation

Introduce the concept and be sure to indent the first line of the paragraph. Connect information from at least 3 articles. Do not write and overview or critique of the articles. Synthesize and connect the information contained to develop a solid understanding of how service quality and segmentation are related. Part 2 of the Individual Project should be 2 pages in length and should be predominately from at least three articles in AIU's full-text databases. Be sure to cite your resources.

Part 3: Null/Hypo 1, ANOVA, Decision

Attached is a small set of data that has been collected from brand loyal customers of Store 1 and Store 2. Write out a Null hypothesis and an alternate hypothesis for each of the 4 aspects of service quality that are include in the analysis (assurance, empathy, reliability and responsiveness) to see if there is a difference between stores. Run 4 ANOVAs to test the Null hypotheses. State the decision for each of the tests.

Part 3: Null/Hypo 2, ANOVA, Decision

Write out a Null hypothesis and an alternate hypothesis for each of the 4 aspects of service quality that are include in the analysis (assurance, empathy, reliability and responsiveness) to see if there is a difference between stores. Run 4 ANOVAs to test the Null hypotheses. State the decision for each of the tests.

Part 3: Null/Hypo 3, ANOVA, Decision

Write out a Null hypothesis and an alternate hypothesis for each of the 4 aspects of service quality that are include in the analysis (assurance, empathy, reliability and responsiveness) to see if there is a difference between stores. Run 4 ANOVAs to test the Null hypotheses. State the decision for each of the tests.

Part 3: Null/Hypo 4, ANOVA, Decision

Write out a Null hypothesis and an alternate hypothesis for each of the 4 aspects of service quality that are include in the analysis (assurance, empathy, reliability and responsiveness) to see if there is a difference between stores. Run 4 ANOVAs to test the Null hypotheses. State the decision for each of the tests.

Part 3: Compare ANOVA & t-test results

Compare the results from last unit's t-tests.

Part 3: Findings

You now have two types of hypothesis tests. Analyze how your findings support or do not support what you found in the research. It is OK if your results are different than what you expected. Part 3 of the Individual Project will vary in length based on the size of the SPSS output. Be sure to cite your resources

Conclusion

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

References

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

U3 IP SPSS Help.pdf

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 ANOVAs & T-Tests: NULL: Males are the same as females with regard to ____________________. HYPO: Males are not the same as females with regard to ____________________.

Three Possible Statements of Hypotheses

HYPOTHESIS NULL HYPOTHESIS

LOWER TAIL Less than < Greater than or equal to >/=

UPPER TAIL Greater than > Less than or equal to </=

TWO TAIL Not equal to =/ Equal to =

NOTE: although in advanced statistical testing, an equality symbol may be found in either

the hypothesis or the null, it is often easier to have the equality sign in the NULL HYPOTHESIS. You may set it up either way, but the preferred manner (at this stage) is stated

in the table above.

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.

NULL: Males have the same level of Overall Job Satisfaction compared to Females. (M = F)

Males have a different level of Overall Job Satisfaction compared to Females. (M =/ F)

Looking at the mean Job Satisfaction scores for both genders shows that they are nearly equal, though the standard deviation for females is much larger, showing that the scores are less consistent for females.

Given that the sig. .688 is greater than the alpha of .05, the NULL hypothesis is not rejected and therefore there is no support for the HYPO that Males have a different level of Overall Job Satisfaction compared to Females. (M =/ F).

Group Statistics

24 2.7361 .18768 .03831

83 2.7925 .67559 .07416

Gender

Male

Female

Overall Job Satisfaction

N Mean Std. Deviat ion Std. Error Mean

Independent Samples Test

37.249 .000 -.403 105 .688 -.0564 .13986 -.33371 .22092

-.676 105.0 .501 -.0564 .08347 -.22189 .10911

Equal variances

assumed

Equal variances

not assumed

Overall Job

Satisfaction

F Sig.

Levene's Test

for Equal ity of

Variances

t df

Sig.

(2-tail

ed)

Mean

Differen

ce

Std.

Error

Differ

ence Lower Upper

95% Confidence

Interval of the

Difference

t-test for Equality of Means

We can also run an ANOVA to test this:

Given that the sig. .688 is greater than the alpha of .05, the NULL hypothesis is not rejected and therefore there is no support for the HYPO that Males have a different level of Overall Job Satisfaction compared to Females. (M =/ F).

ANOVA

Overall Job Satisfaction

.059 1 .059 .163 .688

38.237 105 .364

38.296 106

Between

Groups

Within Groups

Total

Sum of Squares df Mean Square F Sig.