https://file.aiquickdraw.com/mathbot/file/1727311180278r253mos8.pdf

The table provided contains the following dataThe table provided contains the following 

| No | Class Interval | Midpoint (Nilai Tengah) | Frequency (F) |
|----|----------------|-------------------------|---------------|
| 1  | 34 – 48        | 41                      | 0             |
| 2  | 49 – 63        | 56                      | 0             |
| 3  | 64 – 78        | 71                      | 1             |
| 4  | 79 – 93        | 86                      | 31            |
| 5  | 94 – 108       | 101                     | 32            |
| 6  | 109 – 123      | 116                     | 3             |
| 7  | 124 – 136      | 130                     | 0             |

To determine if the data follows a normal distribution at a significance level (α) of 5%, a statistical test such as the **Chi-Square Goodness of Fit test** or the **Kolmogorov-Smirnov test** would typically be used. Here's how it can be approached:

### Steps:
1. **Compute the sample mean** and **standard deviation**.
2. **Calculate expected frequencies** for each interval assuming the data is normally distributed.
3. **Perform the Chi-Square test** to compare observed and expected frequencies.
4. **Compare the calculated Chi-Square value** with the critical value from the Chi-Square distribution for the given degrees of freedom at α = 0.05.

Would you like to proceed with this analysis, or need assistance with a specific part of this process?

Here are 5 related questions to deepen your understanding:
1. How do you calculate expected frequencies for a Chi-Square test?
2. What is the importance of the standard deviation in normal distribution?
3. How can we use the Kolmogorov-Smirnov test to check for normality?
4. How does the choice of α (5%) affect the results of hypothesis testing?
5. What is the difference between skewness and normality in distribution?

**Tip**: For better accuracy, it's essential to have a reasonable number of classes and sufficient frequency in each interval when conducting Chi-Square tests.

Apakah data di atas berdistribusi normal? α = 5%

This problem explores the normality of data using class intervals and frequencies. Key steps include computing sample mean, standard deviation, and applying the Chi-Square test at a 5% significance level. Suitable for undergraduate statistics students.

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