In order to reject the null hypothesis used in linear regression, the p-value of βi should be Less than 0.05.

Here's why:

1. The null hypothesis in linear regression is typically that there is no relationship between the predictor variables and the response variable. In other words, the null hypothesis is that the coefficient βi equals zero.

2. The p-value is a measure of the probability that an observed difference could have occurred just by random chance.

3. A smaller p-value suggests that the observed relationship is highly unlikely to have occurred by chance, thus providing stronger evidence against the null hypothesis.

4. The threshold of 0.05 is commonly used in hypothesis testing. If the p-value is less than 0.05, it is usually considered strong evidence against the null hypothesis, and the null hypothesis is rejected.

5. Therefore, in order to reject the null hypothesis in linear regression, the p-value of βi should be less than 0.05.

Question

In order to reject the null hypothesis used in linear regression, the p-value of βi should be Less than 0.05.

Here's why:

1. The null hypothesis in linear regression is typically that there is no relationship between the predictor variables and the response variable. In other words, the null hypothesis is that the coefficient βi equals zero.

2. The p-value is a measure of the probability that an observed difference could have occurred just by random chance.

3. A smaller p-value suggests that the observed relationship is highly unlikely to have occurred by chance, thus providing stronger evidence against the null hypothesis.

4. The threshold of 0.05 is commonly used in hypothesis testing. If the p-value is less than 0.05, it is usually considered strong evidence against the null hypothesis, and the null hypothesis is rejected.

5. Therefore, in order to reject the null hypothesis in linear regression, the p-value of βi should be less than 0.05.

Knowee AI · Accepted Answer

In order to reject the null hypothesis used in linear regression, the p-value of βi should be Less than 0.05.

Here's why:

1. The null hypothesis in linear regression is typically that there is no relationship between the predictor variables and the response variable. In other words, the null hypothesis is that the coefficient βi equals zero.

2. The p-value is a measure of the probability that an observed difference could have occurred just by random chance.

3. A smaller p-value suggests that the observed relationship is highly unlikely to have occurred by chance, thus providing stronger evidence against the null hypothesis.

4. The threshold of 0.05 is commonly used in hypothesis testing. If the p-value is less than 0.05, it is usually considered strong evidence against the null hypothesis, and the null hypothesis is rejected.

5. Therefore, in order to reject the null hypothesis in linear regression, the p-value of βi should be less than 0.05.

n order to reject the null hypothesis used in linear regression, the p-value of βi should be?Greater than 0.05Less than 0.05Equal to 0.05

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