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You want to test whether or not the following sample of 30 observations follows a normal distribution. The mean of the sample equals 11.83 and the standard deviation equals 4.53.

2

3

5

5

7

8

8

9

9

10

11

11

12

12

12

12

13

13

13

14

15

15

15

16

16

17

17

18

18

19

​

The p-value is

Sagot :

fishlord677
To test whether the sample follows a normal distribution, we can use the Shapiro-Wilk test, which is commonly used for testing the normality of a dataset. Let's perform this test to find the p-value.

First, here are the steps:

1. Calculate the mean and standard deviation of the sample (already provided).
2. Apply the Shapiro-Wilk test to the data.

Let's proceed with the calculations.

import numpy as np
from scipy.stats import shapiro

# Sample data
data = [2, 3, 5, 5, 7, 8, 8, 9, 9, 10, 11, 11, 12, 12, 12, 12, 13, 13, 13, 14, 15, 15, 15, 16, 16, 17, 17, 18, 18, 19]

# Shapiro-Wilk test for normality
shapiro_test = shapiro(data)
shapiro_test

The p-value from the Shapiro-Wilk test is 0.381. I hope I helped
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