SPSS for DATA ANALYSIS - Part 5

SPSS for DATA ANALYSIS – PART 5

In this section of SPSS for DATA ANALYSIS, the Independent Samples Test will be carried out on the “Offer Acceptance” to further scrutinize the trend in the campaigns offer acceptance. Independent samples test falls under the “Compare means” analysis and it is used to study the mean difference between independent measurements. In this case, the offer acceptance by customers per campaign differ. So, we want to see futher if there is significant difference in the mean of the columns.

This is to further evaluate the results obtained in Part 4 of this series.

Independent Samples Test

To do Independent samples test, “Test variable(s)” and “Grouping variable(s)” are required. The test variables in this data are the “Offer Acceptance” in the first campaign to the fifth campaign. They are categorical data: 1 and 0. While the testing variable is the “Response” which is also categorical.

In Figure 35, follow the numbering to navigate in SPSS for how to perform independent samples test. We are doing “Independent” because there are five different (independent) campaigns. If they are dpenedent then “Paired-Samples T Test” would be appropriate. When you click on “Independent-Samples T Test…” then Figure 36 displays.

In the “Grouping Variable” you have to define the groups (as shown in Figure 37) and in this case, “1” (Accepted) and “0” (Rejected) as those are the categories that the “Offer Variables” have.

After you click “Continue” then Figure 38 displays. Then click “OK” to see the results.

Figure 39 shows the group statistics of the offer acceptance.

Null hypothesis (H0): There is no significant difference between the campaign offers’ acceptance.

Alternative hypothesis (H1): There is significant difference between the campaign offers’ acceptance.

From Table 2, it can be seen that the p-value is greater than 0.05 then the null hypothesis is accepted while the alternative hypothesis is rejected. In other words, there is no significant difference between the campaign offers’ acceptance. The customers response to offers in the first campaign seems to be similar in the other campaigns. Additionally, the confidence interval also revealed the similar fact as none of the values passes through zero.

Conclusion

Independent Samples T Test has been carried out on the “Marketing Campaign” data. It was used to evaluate the trend in the offer acceptance of the customers. The p-value revealed that there is no significant difference in the mean of the offer acceptance in the campaigns.

Check the next blog here (Variable Transformation).