Statistical significance refers to the claim that a result from ** data generated by testing or experimentation is not likely to occur randomly or by chance but is instead likely to be attributable to a specific cause ** .

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## When the results of a study are statistically significant it means that quizlet?

Statistical significance means that the result observed in a sample ** is unusual when the null hypothesis is assumed to be true ** . When testing a hypothesis using the P-value Approach, if the P-value is large, reject the null hypothesis. You just studied 5 terms!

## What does it mean if the results of a study are statistically significant?

A result of an experiment is said to have ** statistical significance ** , or be statistically significant, if it is likely not caused by chance for a given statistical significance level. ... It also means that there is a 5% chance that you could be wrong.

## What does statistically significant tell?

If a result is statistically significant, that means ** it’s unlikely to be explained solely by chance or random factors ** . In other words, a statistically significant result has a very low chance of occurring if there were no true effect in a research study.

## What does a statistically significant result mean psychology?

Statistical significance is the term used by research psychologists to indicate ** whether or not the difference between groups can be attributed to chance or if the difference is likely the result of experimental influences ** .

## What does significant mean in statistics?

What is statistical significance? “Statistical significance helps quantify whether a result is likely due to chance or to some factor of interest,” says Redman. When a finding is significant, it simply means ** you can feel confident that’s it real ** , not that you just got lucky (or unlucky) in choosing the sample.

## What does it mean if the result of your study is not statistically significant?

This means that the results are considered to be „statistically non-significant‟ if ** the analysis shows that differences as large as (or larger than) the observed difference would be expected to occur by chance more than one out of twenty times ** (p > 0.05).

## How do you know if a result is statistically significant?

The level at which one can accept whether an event is statistically significant is known as the significance level. Researchers use a test statistic known as the p-value to determine statistical significance: ** if the p-value falls below the significance level ** , then the result is statistically significant.

## What is the meaning of significant difference in statistics?

A statistically significant difference is ** simply one where the measurement system (including sample size, measurement scale, etc.) was capable of detecting a difference (with a defined level of reliability) ** . Just because a difference is detectable, doesn’t make it important, or unlikely.

## What is the meaning of significant findings?

This means that a “ ** statistically significant” finding is one in which it is likely the finding is real, reliable, and not due to chance ** . To evaluate whether a finding is statistically significant, researchers engage in a process known as null hypothesis significance testing.

## How do you know if a difference is significant?

To determine whether the observed difference is statistically significant, we look at two outputs of our statistical test: ** P-value ** : The primary output of statistical tests is the p-value (probability value). It indicates the probability of observing the difference if no difference exists.

## How do you test statistical significance?

- State the Research Hypothesis.
- State the Null Hypothesis.
- Select a probability of error level (alpha level)
- Select and compute the test for statistical significance.
- Interpret the results.

## How can you be statistically significant?

Start by looking at the left side of your degrees of freedom and find your variance. Then, go upward to see the p-values. Compare the p-value to the significance level or rather, the alpha. Remember that ** a p-value less than 0.05 is considered statistically significant ** .

## What would a chi-square significance value of P 0.05 suggest?

What is a significant p value for chi squared? The likelihood chi-square statistic is 11.816 and the p-value = 0.019. Therefore, at a significance level of 0.05, you can conclude that ** the association between the variables is statistically significant ** .

## Why do we use 0.05 level of significance?

The significance level, also denoted as alpha or α, is the probability of rejecting the null hypothesis when it is true. For example, a significance level of 0.05 indicates ** a 5% risk of concluding that a difference exists when there is no actual difference ** .

## How does sample size affect determinations of statistical significance?

How does sample size affect determinations of statistical significance? ... c) ** The larger the sample size ** , the more accurate the stimulation of the true population value d) The smaller the sample size, the more confident one can be in one’s decision to reject or retain the null hypothesis.