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APA
Subject:
Accounting, Finance, SPSS
Type:
Coursework
Language:
English (U.S.)
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Topic:

Chi Square Analysis

Coursework Instructions:

Chi square analysis (Module 2 – TD2)

2a. Using the available SPSS dataset titled “Multiple Stores.sav”, perform a Chi-Square test of independence on any two nominal variables (Please review the background materials to understand the steps of conducting a Chi-square test via SPSS)

2b. Upload as an attachment or copy and paste your SPSS results into the discussion.

2c. Describe results for a Chi-Square for the test of independence based upon your statistical analysis.

Notes:

In this module, we will be considering a statistical test known as Chi-square analysis that compares categorical variables to determine if the groupings of the two variables influence each other. For instance, one might wonder if an urban vs. rural setting might influence whether a cell-phone company’s stores are likely to be in stand-alone buildings or part of a larger complex of buildings. If there was no independence, one would expect the ratio of stand-alone stores vs. complex facilities to be found in similar proportions in both settings but this may not be the case. One way to test this statistically is to perform a Chi-square test.

Here is a tutorial for running a Chi Square test of Independence:

https://www.youtube.com/watch?v=0LOOxxvtGv8

Make sure you only use 2 nominal (also known as categorical or grouped) variables for your Chi square test. You can use any combination of 2 of the below variables listed below. Try to find a combination that has not been used yet by other doctoral learners in the thread. If you can't, that's OK but it would be good to mix things up a bit:  

OWNERSHIP (Franchise or Corporate)

STATE (Which state the store is located out of several choices) [note: you can use this grouped variable if you'd like but it's kind of messy because there are so many states] 

FACTYPE (The type of facility stand alone or shared facility)

SETTING (Urban or Ruran)

PRODMIX (Three product mix options. A, B or C)

Include your tables and a narrative of your findings.

Here is an example of a narrative for reporting a hypothetical Chi square test of independence looking at gender and voting outcomes between two parties:

[Note: the "1" value below refers to the degrees of freedom. N is the sample size. 6.144 refers to the actual Chi Square value. These are all reported in the JASP output]:

A chi square test of independence was calculated comparing the votes for political parties by male and female voters. A significant relationship was found:

Χ2 (1, N = 174) = 6.144 , p = .013  

Hence, we reject the null hypothesis. Political voting preference appears to be dependent on gender.

References

Coursework Sample Content Preview:

Chi-Square Analysis
Name
Institution
Course
Professor
Date
Chi-Square Analysis
A Chi-Square test of independence was undertaken on two nominal variables in the dataset; ownership and product mix. The chi-square test compared the ownership (corporate or Franchise) with product mix (A, B and C). The null hypothesis formulated in this case was:
H0: The product mix options are not dependent on the ownership type
From the analysis conducted in SPSS, the results are shown are provided in tables that allow for interpretation (Martin, 2019). Table 1 below provides a summary of the distribution of ownership (Corporate & franchise) against the different product mixes (A, B & C).
Table  SEQ Table \* ARABIC 1: Cross tabulation of Ownership and Product Mix
Corporate or Franchise * Product Mix CrosstabulationProduct MixTotalABCCorporate or FranchiseCorporateCount9476125295% w...
Updated on
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