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.