This article describes chi square test of association and hypothesis testing.

What is the Chi Square Test of Association Method of Hypothesis Testing?

It is used to determine whether there is a statistically significant association between the two categorical variables. This technique is used to determine if the relationship exists between any two business parameters that are of categorical data type. One might use this technique to determine whether gender is related to a voting preference or whether the two data points are independent and unrelated. An enterprise might also use Chi Square to determine if there is a relationship between the region in which a product is purchased, and the product or category of product that is purchased.

Let’s conduct the Chi square test of independence using two variables: Gender and Product category.

Let’s conduct the Chi square test of independence using two variables: Gender and Product category

At 95% confidence level (5% chance of error) – As p-value = 0.041 which is less than 0.05, there is a statistically significant association between gender and product category purchased. So, Gender has an influence on the type of product being purchased.

At 98 % confidence level (2% chance of error) – As p-value = 0.041 which is greater than 0.02, there is no statistically significant association between gender and product category purchased, so Gender has no influence on the type of product being purchased.

chi square statistics

This analytical technique can be used for numerous purposes.

Marketing / Market Research – To determine if certain types of products sell better in certain geographic locations than others, and to verify if gender has an influence on purchasing decisions. It might be used to identify if there is an association between income level of consumers and their choice of brand. To determine If customer age has an influence on product/service subscription (assuming age is converted into age buckets such as 18 to 25, 26 – 35 etc). This technique is helpful in finding a relationship between any demographic characteristic of consumers or research respondents for education, location, gender etc. and various preferences/perspective/behavioral attributes such as entrepreneurial characteristics, product/service preferences, career preference, income level, political party preference etc.

Finance – An organization might use this technique to Identify if demographic factors influence banking channel/product/service preference or selection of a type of term plan of an insurance etc.

How Can the Chi Square Test of Association Be Used for Business Analysis?

Let’s look at a few use cases that depict the value of the Chi Square Test of Association.

Use Case – 1

Business Problem: A retail store marketing manager wants to know if there is a significant association between the geography of a customer and his/her brand preferences.

Business Benefit: Once the test is completed, p-value is generated which indicates whether there is significant association between geography and brand preference. Based on this value, a retail store marketing manager can design the ongoing marketing campaigns for different brands to address different geographical customers/prospect preferences.

Use Case – 2

Business Problem: A marketing researcher wants to know if gender has an influence on political party preference.

Business Benefit: Once the test is completed, p-value is generated which indicates whether there is significant association between gender and political party preference. If significant association is found, then both males and females can be targeted with different political campaigns to turn their votes in preference of a political client.

The Chi Square Test of Association Method of Hypothesis Testing allows businesses to test theories regarding the relationship of one or more data points to another data point to determine possible influencing factors for product purchases, or other outcomes.

About Smarten

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist. Smarten Augmented Analytics tools include assisted predictive modelingsmart data visualizationself-serve data preparation and clickless analytics with natural language processing (NLP) for search analytics. All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists.

The Smarten approach to data discovery is powered by ElegantJ BI Business Intelligence Solutions, a representative vendor in multiple Gartner reports including the Gartner Research Market Guide to Self-Service Data Preparation, as a Niche BI and Analytics Vendor in the Gartner Report, Competitive Landscape in the BI Platforms and Analytics Software, Asia/Pacific, as a Representative Vendor in the Gartner Market Guide for Enterprise-Reporting-Based Platforms, and a Listed Vendor in the Other Vendors to Consider for Modern BI and Analytics, Gartner Report.

Original Post: What is the Chi Square Test of Association and How Can it be Used for Analysis?

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