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It looks like the data we need is all contained within

`Sheet1`

of the Excel file, and the other sheets are empty. The data includes enrolment numbers by discipline, level (PGD, Masters, Ph.D.), and ownership (Federal, State, Private).Next, we'll clean up the data in

`Sheet1`

to focus on the ownership columns and then plot the enrolment numbers based on ownership.Show code

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We've already created a bar chart showing postgraduate enrollment by ownership. It displays the number of enrollments for Federal, State, and Private ownership categories.

To test the hypothesis that there is no significant difference in enrollment among different programs, we can perform an ANOVA test (Analysis of Variance). This test is suitable if we have three or more independent groups and want to compare their means to see if at least one of them is significantly different from the others.

First, we need to prepare our data for the ANOVA test. We'll extract enrollment numbers for each program type (PGD, Masters, Ph.D.) across all ownership types (Federal, State, Private). Then, we'll conduct the ANOVA test.

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**Test Used**: ANOVA (Analysis of Variance)**Purpose**: To test if there's a significant difference in enrollment among PGD, Masters, and Ph.D. programs.**Result**: The ANOVA test resulted in a`p-value`

of`0.185`

, which is greater than the common alpha level of`0.05`

.**Conclusion**: With a`p-value`

greater than`0.05`

, we fail to reject the null hypothesis. This suggests that there are no significant differences in enrollment among the PGD, Masters, and Ph.D. programs.

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