Welcome to Westonci.ca, where you can find answers to all your questions from a community of experienced professionals. Discover the answers you need from a community of experts ready to help you with their knowledge and experience in various fields. Join our platform to connect with experts ready to provide precise answers to your questions in different areas.

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 :

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