Do you reject if p-value is less than alpha?

Coefficients having p values less than alpha are significant. For example, if you chose alpha to be 0.05, coefficients having a p value of 0.05 or less would be statistically significant (i.e., you can reject the null hypothesis and say that the coefficient is significantly different from 0).
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Do you reject if p is less than alpha?

If the p-value is greater than alpha, you accept the null hypothesis. If it is less than alpha, you reject the null hypothesis.
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What if the p-value is less than the significance level α?

If your P value is less than the chosen significance level then you reject the null hypothesis i.e. accept that your sample gives reasonable evidence to support the alternative hypothesis.
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What does it mean if p is greater than alpha?

The p-value is greater than alpha. In this case, we fail to reject the null hypothesis. When this happens, we say that the result is not statistically significant. In other words, we are reasonably sure that our observed data can be explained by chance alone.
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What if probability is less than alpha?

If the probability (i.e., p-value) is less than alpha that we would obtain a sample mean this large or larger from the null population, we reject the null hypothesis and conclude that that our sample was drawn from a different population with a sample mean larger than the null mean.
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Statistical Significance, the Null Hypothesis and P-Values Defined & Explained in One Minute

What if p is lower than alpha?

If your p-value is less than your selected alpha level (typically 0.05), you reject the null hypothesis in favor of the alternative hypothesis. If the p-value is above your alpha value, you fail to reject the null hypothesis.
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How to reject null hypothesis with p-value?

A p-value less than 0.05 is typically considered to be statistically significant, in which case the null hypothesis should be rejected. A p-value greater than 0.05 means that deviation from the null hypothesis is not statistically significant, and the null hypothesis is not rejected.
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How to know when to reject the null hypothesis?

You can reject a null hypothesis when a p-value is less than or equal to your significance level. The p-value represents the measure of the probability that a certain event would have occurred by random chance. You can calculate p-values based on your data by using the assumption that the null hypothesis is true.
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When the p-value is less than α then the results are statistically significant?

In statistical hypothesis testing, you reject the null hypothesis when the p-value is less than or equal to the significance level (α) you set before conducting your test. The significance level is the probability of rejecting the null hypothesis when it is true.
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Should the null hypothesis be rejected when the p-value is less than α?

In any null hypothesis significance test, when the p-value associated with a test statistic is less than the alpha level in the study, the null hypothesis should be rejected. This is equivalent to the case when the test statistic falls inside the rejection region.
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Why do we say fail to reject the null hypothesis?

Consequently, we fail to reject it. Failing to reject the null indicates that our sample did not provide sufficient evidence to conclude that the effect exists. However, at the same time, that lack of evidence doesn't prove that the effect does not exist.
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What happens if the p-value is less than alpha the level of significance in a two tailed test?

The smaller (closer to 0) the p-value, the stronger is the evidence against the null hypothesis. If the p-value is less than or equal to the specified significance level α, the null hypothesis is rejected. Otherwise, the null hypothesis is not rejected.
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Is p-value 0.05 the same as 95 confidence interval?

In accordance with the conventional acceptance of statistical significance at a P-value of 0.05 or 5%, CI are frequently calculated at a confidence level of 95%. In general, if an observed result is statistically significant at a P-value of 0.05, then the null hypothesis should not fall within the 95% CI.
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When to use 0.01 and 0.05 level of significance?

And this is exactly it: When we put it that way, saying that we want the probability (of the null hypothesis being true) — called a p-value — to be less than 5%, we have essentially set the level of significance at 0.05. If we want the probability to be less than 1%, we have set the level of significance at 0.01.
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What if the p-value is less than the alpha value?

A study is statistically significant if the P value is less than the pre-specified alpha. Stated succinctly: A P value less than a predetermined alpha is considered a statistically significant result. A P value greater than or equal to alpha is not a statistically significant result.
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What does it mean if the p-value is less than the alpha value for research data in which the results are statistically significant?

The p-value only tells you how likely the data you have observed is to have occurred under the null hypothesis. If the p-value is below your threshold of significance (typically p < 0.05), then you can reject the null hypothesis, but this does not necessarily mean that your alternative hypothesis is true.
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What does it mean if the p-value is greater than alpha?

A p-value greater than alpha means the “tail” region is greater than that given by alpha, so the test stat ISN'T in the critical region.
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Do we reject the null when p is big or small?

The smaller the p-value, the more likely it is that you would reject the null hypothesis. A P-Value < or = 0.05 is considered statistically significant. It denotes strong evidence against the null hypothesis, since there is below 5% probability of the null being correct.
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When to reject null hypothesis in ANOVA?

After cleaning the data, the researcher must test the assumptions of ANOVA. They must then calculate the F-ratio and the associated probability value (p-value). In general, if the p-value associated with the F is smaller than . 05, then the null hypothesis is rejected and the alternative hypothesis is supported.
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When to reject null hypothesis confidence intervals?

Remember that the decision to reject the null hypothesis (H 0) or fail to reject it can be based on the p-value and your chosen significance level (also called α). If the p-value is less than or equal to α, you reject H 0; if it is greater than α, you fail to reject H 0.
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What to do if p is less than alpha?

It will not change no matter how many times you run the test. That is the beauty of the p-value. It leads to a straight-forward decision rule: If p-value is less than alpha, reject the null hypothesis.
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How do I know if I should reject the null hypothesis?

Rejecting or failing to reject the null hypothesis

If our statistical analysis shows that the significance level is below the cut-off value we have set (e.g., either 0.05 or 0.01), we reject the null hypothesis and accept the alternative hypothesis.
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Do you reject the null if the p-value is low?

We reject the null hypothesis when the p-value is less than the significance level (commonly denoted as α, such as 0.05) because this indicates that the observed data is unlikely to have occurred under the assumption that the null hypothesis is true.
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What does p-value 0.99 mean?

A p-value of 0.99 means that practically there is no effect, no association, no correlation between two variables and the situation is so simply straight forward that one would not even have to go for any test.
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What does less than alpha mean?

Alpha is also known as the level of significance. This represents the probability of obtaining your results due to chance. The smaller this value is, the more “unusual” the results, indicating that the sample is from a different population than it's being compared to, for example.
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