Reasearch Question

A private all-girls elementary school has developed two different uniform designs: Design A and Design B. They are hoping at least one of the designs will be preferred by both mothers and fathers. Analyze the data to determine if there is a relationship between uniform design and parent.

Research Summary

A Chi-Square Test of Independence was conducted to examine the association between parent type (mother, father) and preferred design (A, B) among 100 participants. The results indicated that there was not a statistically significant association between parent type and preferred design, χ²(1, N = 100) = 3.25, p = .072. Because the result was not statistically significant, an effect size (Cramér’s V) was not calculated.

Hypothesis

H0: There is no association between parent type (mother/father) and preferred design (A/B).

H1: There is an association between parent type (mother/father) and preferred design (A/B)

Chi-Square Test of Independence

This report examines whether there is an association between Parent Type (Mother, Father) and Preferred Design(A, B) using a Chi-Square Test of Independence.

Step 1: Load Packages

library(readxl)

Step 2: Import the Dataset

Load the Excel file into R.

dataset <- read_excel("C:/Users/rohit/Downloads/RQ2.xlsx")

Step 3: View the Contingency Table

contingencytable <- table(dataset$Parent, dataset$Preferred_Design)
contingencytable
##         
##           A  B
##   Father 21 29
##   Mother 31 19

Step 4: Run the Chi-Square Test of Independence

chisq_indep <- chisq.test(contingencytable)
chisq_indep
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  contingencytable
## X-squared = 3.2452, df = 1, p-value = 0.07163

Step 5: Determine Statistical Significance

Because the p-value is greater than .05, the result is not statistically significant, so an effect size (Cramer’s V) is not calculated.