It seems like your question got cut off. However, I can tell you that when the p-value is less than the significance level (usually 0.05), it means that we reject the null hypothesis. This is because the p-value is the probability of obtaining the observed data given that the null hypothesis is true. If this probability is less than the significance level, it means that the observed data is unlikely under the null hypothesis, so we reject it.

Here are the steps:

1. Perform your statistical test and get the p-value.
2. Compare the p-value to your significance level (usually 0.05).
3. If the p-value is less than the significance level, reject the null hypothesis.
4. If the p-value is greater than the significance level, do not reject the null hypothesis.

Remember, rejecting the null hypothesis does not prove the alternative hypothesis. It simply means that the data you have does not support the null hypothesis.

Question

It seems like your question got cut off. However, I can tell you that when the p-value is less than the significance level (usually 0.05), it means that we reject the null hypothesis. This is because the p-value is the probability of obtaining the observed data given that the null hypothesis is true. If this probability is less than the significance level, it means that the observed data is unlikely under the null hypothesis, so we reject it.

Here are the steps:

1. Perform your statistical test and get the p-value.
2. Compare the p-value to your significance level (usually 0.05).
3. If the p-value is less than the significance level, reject the null hypothesis.
4. If the p-value is greater than the significance level, do not reject the null hypothesis.

Remember, rejecting the null hypothesis does not prove the alternative hypothesis. It simply means that the data you have does not support the null hypothesis.

Knowee AI · Accepted Answer

It seems like your question got cut off. However, I can tell you that when the p-value is less than the significance level (usually 0.05), it means that we reject the null hypothesis. This is because the p-value is the probability of obtaining the observed data given that the null hypothesis is true. If this probability is less than the significance level, it means that the observed data is unlikely under the null hypothesis, so we reject it.

Here are the steps:

1. Perform your statistical test and get the p-value.
2. Compare the p-value to your significance level (usually 0.05).
3. If the p-value is less than the significance level, reject the null hypothesis.
4. If the p-value is greater than the significance level, do not reject the null hypothesis.

Remember, rejecting the null hypothesis does not prove the alternative hypothesis. It simply means that the data you have does not support the null hypothesis.

When the p-value is less than the significance level (

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