# Chi-Square Independence

Test in Excel

For Marketing

If there was one question that every single marketing manager and business owner would like an answer to, it might be this one: “What makes my customers buy more???” Anyone who has had that question on their mind will like this article. If you have been collecting data on your customers, you can use Excel to perform a statistical procedure called the Chi-Square Independence Test to find out what factors seem to have made a difference when your customers make larger purchases.

Here is a Step-By-Step Video Showing Exactly How To Find Out What Makes Your Customers Buy More With the Chi-Square Independence Test in Excel:

Here is a Step-By-Step Video Showing Exactly How To Find Out What Makes Your Customers Buy More With the Chi-Square Independence Test in Excel:

*(Is Your Sound Turned On?)*

What Is the Chi-Square Independence Test?

What Is the Chi-Square Independence Test?

**Here's How We Did Our Chi-Square Independence Test**

**The 3 Overall Steps in the Chi-Square Independence Test**

**1) Arrange the sampled data in a Contingency Table.**

2) Calculate the Chi-Square Statistic for the Sampled Data.

3) Compare the above Chi-Square Statistic with the Critical Chi-Square Statistic.If the Chi-Square Statistic is greater than the Critical Chi-Square Statistic, we can state that the two attributes of the object are related (are not independent).

2) Calculate the Chi-Square Statistic for the Sampled Data.

3) Compare the above Chi-Square Statistic with the Critical Chi-Square Statistic.

**Step1) Arrange the Sampled Data in a Contingency Table**

**Click On Image To See Enlarged View**

**Click On Image To See Enlarged View**

**Click On Image To See Enlarged View****Here are both the Actual and Expected Contingency Tables:**

**Click On Image To See Enlarged View****Step 2) Calculate the Chi-Square Statistic for the Sampled Data**

**f0i**(that is,

**f01**,

**f02**,

**f03**,…,

**f09**). We will label data from each of the 9 cells of the Expected Value Contingency Matrix as

**fti**(that is,

**ft1**,

**ft2**,

**ft3**,…,

**ft9**).

**Click On Image To See Enlarged View****f0i**-

**fti**) /

**fti**as

**i**goes from 1 to 9. Once again, the video provide a clear picture of this calculation. The Chi-Square Statistic for the sampled data in the test we are performing equals 794.3.

**Click On Image To See Enlarged View**We now have:

**Step 3) Compare the above Chi-Square Statistic with the Critical Chi-Square Statistic**

**Click On Image To See Enlarged View****If You Like This, Then Share It...**

**Excel Master Series Blog Directory**

Statistical Topics and Articles In Each Topic

- Histograms in Excel
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- Combinations & Permutations in Excel
- Normal Distribution in Excel
- Overview of the Normal Distribution
- Normal Distribution’s PDF (Probability Density Function) in Excel 2010 and Excel 2013
- Normal Distribution’s CDF (Cumulative Distribution Function) in Excel 2010 and Excel 2013
- Solving Normal Distribution Problems in Excel 2010 and Excel 2013
- Overview of the Standard Normal Distribution in Excel 2010 and Excel 2013
- An Important Difference Between the t and Normal Distribution Graphs
- The Empirical Rule and Chebyshev’s Theorem in Excel – Calculating How Much Data Is a Certain Distance From the Mean
- Demonstrating the Central Limit Theorem In Excel 2010 and Excel 2013 In An Easy-To-Understand Way

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- Binomial Distribution in Excel
- z-Tests in Excel
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- Overview of t-Tests: Hypothesis Tests that Use the t-Distribution
- 1-Sample t-Tests in Excel
- Overview of the 1-Sample t-Test in Excel 2010 and Excel 2013
- Excel Normality Testing For the 1-Sample t-Test in Excel 2010 and Excel 2013
- 1-Sample t-Test – Effect Size in Excel 2010 and Excel 2013
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- Excel Normality Tests Kolmogorov-Smirnov, Anderson-Darling, and Shapiro-Wilk For 2-Sample Unpooled t-Test
- 2-Sample Unpooled t-Test Excel Calculations, Formulas, and Tools
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- Test Power of a 2-Independent Sample Unpooled t-Test With G-Power Utility

- Paired (2-Sample Dependent) t-Tests in Excel
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- Excel Normality Testing of Paired t-Test Data
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- Brown-Forsythe F-Test in Excel Substitute For Single-Factor ANOVA When Sample Variances Are Not Similar

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- Shapiro-Wilk Normality Test in Excel For 2-Factor ANOVA With Replication
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- Excel Post Hoc Tukey’s HSD Test For 2-Factor ANOVA With Replication
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- Two-Factor ANOVA Without Replication in Excel
- Creating Interactive Graphs of Statistical Distributions in Excel
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- Interactive Graph of the Chi-Square Distribution in Excel 2010 and Excel 2013
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- Interactive Graph of the Binomial Distribution in Excel 2010 and Excel 2013
- Interactive Graph of the Exponential Distribution in Excel 2010 and Excel 2013
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Found a typo:

ReplyDeleteOriginal:

We require a 99% Degree of Certainty. Alpha is therefore equal to 0.001.

Corrected:

We require a 99% Degree of Certainty. Alpha is therefore equal to 0.01.