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This article is to share with you what is the knowledge of hypothesis testing in excel data analysis. The editor thinks it is very practical, so I share it with you to learn. I hope you can get something after reading this article.

What I want to share with you today is excel data analysis-hypothesis testing!

A total of 5 knowledge points about hypothesis testing will be covered:

Z-test: double sample mean difference test

The distribution of case data is as follows:

XRV OBSs "30 minutes" 15 minutes STDstores 5

Yazuo OBS 30 minutes 20 minutes STD 5

Call up the data analysis tool library, open the Z-test: double-sample mean difference test menu, and set up the parameters

At the significance level of 0.05, both double-tailed and single-tailed tests reject the original hypothesis (the mean difference is equal to 0), indicating that there is a significant difference between the two samples at 0.05 level.

T-test: paired two-sample test of the average value:

It is mainly used to compare the measured values of an object before and after.

The original hypothesis was rejected (mean difference = 0), which indicated that the difference was significant at 0.05 significant level.

Because X is a random number between 80 and 90 generated, Y is a random number between 85 and 95 generated.

T-test: double-sample equivariance hypothesis

The original hypothesis is still the mean difference of 0, from the output results, the X mean is less than the Y mean, the unit test and double-tailed test both eliminate the original hypothesis, indicating that there is a significant difference between X and Y (α = 0.05).

T-test: double sample heteroscedasticity hypothesis

Assuming that the variances of the two samples are different, test whether there is a significant difference between the two population averages (significance level α = 0.05).

Judging from the output result, the double-tailed truncated P value is 0.016.

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