Short Answer 
The analysis concludes that there is no significant difference in online shopping proportions between two regions, as indicated by a test statistic of Z‚ÄöCA = -1.42134 and a p-value of 0.1573, which is greater than the significance level of 0.05. Thus, the null hypothesis is not rejected.
Step 1: Define Hypotheses
Begin by establishing the null and alternative hypotheses for the study. The null hypothesis (H‚CA) posits that the population proportions of online shoppers in the two regions are equal: p‚CA = p‚CC. Conversely, the alternative hypothesis (H‚CA) asserts that there is a difference: p‚CA ‚a† p‚CC. This step lays the foundation for the statistical analysis that follows.
Step 2: Calculate the Test Statistic
Next, compute the test statistic using the formula: Z‚ÄöCA = (p‚ÄöCA – p‚ÄöCC) / ‚Äöao((p‚ÄöCAq‚ÄöCA/n‚ÄöCA) + (p‚ÄöCCq‚ÄöCC/n‚ÄöCC)). In this context:
- p‚ÄöCA = 16% (0.16)
- p‚ÄöCC = 24% (0.24)
- n‚ÄöCA = 100
- n‚ÄöCC = 100
- q = 1 – p
By substituting these values into the formula, you calculate the test statistic, resulting in Z‚ÄöCA = -1.42134.
Step 3: Interpret the Results
Finally, assess the computed Z-value against the significance level (α) of 0.05. In this case, the probability associated with Z = -1.42 is found to be 0.1573. Since this p-value is greater than α, we fail to reject the null hypothesis, indicating no significant difference in the online shopping proportions between the two regions based on the statistical evidence.