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# Hypothesis Testing and Linear Regression Analysis

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1) Explain the difference between the null and alternative hypothesis. Which one can be proven in a statistical sense?
2) Explain why it is always necessary to specify a fixed null value in the one-sample hypothesis test, while such specifications are generally not necessary for the two-sample hypothesis test.
3) Define the significance level of a test, and the two kinds of errors associated with testing.
4) What is simple linear regression? How does one find the best fitting regression line?
5) Explain why the prediction interval is necessarily wider than the corresponding confidence interval.

https://brainmass.com/statistics/linear-regression/hypothesis-testing-linear-regression-analysis-514655

#### Solution Preview

1) Explain the difference between the null and alternative hypothesis. Which one can be proven in a statistical sense?
Solution:
The null hypothesis is a statistical hypothesis test that states that there is no distinction between a parameter and a specific value. In other words, the null hypothesis says that there is no difference between two parameters. The alternative hypothesis on the other hand is a complete alternative to null hypothesis. It states that there is a difference between a parameter and a specific value. In a statistical sense, the null hypothesis can be proven.

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