How to determine to reject a null hypothesis?

Traditionally, the cut-off value to reject the null hypothesis is 0.05, which means that when no difference exists, such an extreme value for the test statistic is expected less than 5% of the time.
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Do you reject the null hypothesis at the 0.05 significance level?

Similarly, if the value of the significance level is set to 0.05 and the calculated significance probability value is 0.03, the set null hypothesis will be rejected, but if the value of the significance level is set to 0.01, the null hypothesis cannot be rejected.
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How to know when to reject the null hypothesis using critical value?

The critical value approach

The null hypothesis is rejected if the test statistic is more extreme than the critical value. The null hypothesis is not rejected if the test statistic is not as extreme as the critical value.
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When 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 chi square test?

If the Chi-Square value does not exceed the critical value (e.g. p=0.05 ) then the null hypothesis will be accepted i.e. the data does follow the hypothetical pattern. If it does exceed the critical value, the null hypothesis must be rejected.
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Reject or Fail to Reject - Intro to Inferential Statistics

How do you determine if a null hypothesis should be rejected?

Reject the null hypothesis when the p-value is less than or equal to your significance level. Your sample data favor the alternative hypothesis, which suggests that the effect exists in the population.
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How to determine the decision rule for rejecting the null hypothesis h0?

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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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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Is 0.001 statistically significant?

Most authors refer to statistically significant as P < 0.05 and statistically highly significant as P < 0.001 (less than one in a thousand chance of being wrong).
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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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When to reject null hypothesis two sample t test?

Therefore any t score beyond the critical value in either direction is in the most extreme 5% of t scores when the null hypothesis is true and has a p value less than . 05. Thus if the t score we compute is beyond the critical value in either direction, then we reject the null hypothesis.
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How to determine rejection region in hypothesis testing?

The rejection region is the region where, if our test statistic falls, then we have enough evidence to reject the null hypothesis. If we consider the right-tailed test, for example, the rejection region is any value greater than c 1 − α , where c 1 − α is the critical value.
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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 a null hypothesis using critical value?

The critical value approach

If the test statistic is more extreme than the critical value, the null hypothesis is rejected. If the test statistic is not as extreme as the critical value, the null hypothesis is not rejected.
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Do we reject H0 if the p-value is alpha?

Left-tailed Test H0 : µ = k H1 : µ<k P-value = P(z<z¯) This is the probability of getting a test statistic as low as or lower than z¯ If P-value  α, we reject H0 and say the data are statistically significant at the level α. If P-value > α, we do not reject H0.
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Can a null hypothesis be rejected at the 5% significance level?

In null hypothesis testing, this criterion is called α (alpha) and is almost always set to . 05. If there is less than a 5% chance of a result as extreme as the sample result if the null hypothesis were true, then the null hypothesis is rejected. When this happens, the result is said to be statistically significant.
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How to reject a 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 to reject null hypothesis p-value?

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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Is .0005 statistically significant?

If the p-value is under . 01, results are considered statistically significant and if it's below . 005 they are considered highly statistically significant.
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Is .01 or .05 more significant?

Setting a significance level allows you to control the likelihood of incorrectly rejecting a true null hypothesis. This makes your results more reliable. 0.05: Indicates a 5% risk of concluding a difference exists when there isn't one. 0.01: Indicates a 1% risk, making it more stringent.
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Is p-value 0.01 significant?

The degree of statistical significance generally varies depending on the level of significance. For example, a p-value that is more than 0.05 is considered statistically significant while a figure that is less than 0.01 is viewed as highly statistically significant.
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Why choose the 0.05 level of significance?

For decades, 0.05 (5%, i.e., 1 of 20) has been conventionally accepted as the threshold to discriminate significant from non-significant results, inappropriately translated into existing from not existing differences or phenomena.
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How to know if the null hypothesis is rejected or accepted?

If the P-value is less than or equal to the significance level, we reject the null hypothesis and accept the alternative hypothesis instead. If the P-value is greater than the significance level, we say we “fail to reject” the null hypothesis. We never say that we “accept” the null hypothesis.
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What is the correct rejection of the null hypothesis?

In signal detection theory, an instance of failing to detect a signal when the signal is in fact absent. Also called a correct reject.
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How to decide null hypothesis?

The null hypothesis is the claim that there's no effect in the population. If the sample provides enough evidence against the claim that there's no effect in the population (p ≤ α), then we can reject the null hypothesis. Otherwise, we fail to reject the null hypothesis.
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