Is a p-value of 0.05 or lower considered statistically significant?

Statistics is used to differentiate true causal associations from chance-mediated pseudo-causalities. Therefore, a p-value of <0.05 connotes accuracy. Whether the association is significant (relevant), it depends on the description of the numerical difference or the association measures of categorical outcomes.
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What is p ≤ 0.05 was considered statistically significant?

1 minus the P value is the probability that the alternative hypothesis is true. A statistically significant test result (P ≤ 0.05) means that the test hypothesis is false or should be rejected. A P value greater than 0.05 means that no effect was observed.
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Is the p-value of 0.03 significant?

The p-value obtained from the data is judged against the alpha. If alpha=0.05 and p=0.03, then statistical significance is achieved. If alpha=0.01, and p=0.03, statistical significance is not achieved.
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Is p 0.06 significant?

It is inappropriate to interpret a p value of, say, 0.06, as a trend towards a difference. A p value of 0.06 means that there is a probability of 6% of obtaining that result by chance when the treatment has no real effect. Because we set the significance level at 5%, the null hypothesis should not be rejected.
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When p .05 is the difference usually regarded as statistically significant or statistically insignificant?

These are as follows: if the P value is 0.05, the null hypothesis has a 5% chance of being true; a nonsignificant P value means that (for example) there is no difference between groups; a statistically significant finding (P is below a predetermined threshold) is clinically important; studies that yield P values on ...
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Statistical Significance, the Null Hypothesis and P-Values Defined & Explained in One Minute

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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Is p-value less than 0.01 statistically significant?

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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Which is better, 0.01 or 0.05 significance level?

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 the p-value of 0.07 significant?

If the p-value is less than 0.05, it is judged as “significant,” and if the p-value is greater than 0.05, it is judged as “not significant.” However, since the significance probability is a value set by the researcher according to the circumstances of each study, it does not necessarily have to be 0.05.
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Is 0.09 a significant p-value?

But there's still no getting around the fact that a p-value of 0.09 is not a statistically significant result. The blogger does not address the question of whether the opposite situation occurs.
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What if p-value is greater than 0.05 in regression?

If the p-value were greater than 0.05, you would say that the group of independent variables does not show a statistically significant relationship with the dependent variable, or that the group of independent variables does not reliably predict the dependent variable.
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What is the difference between p-value and significance level?

The p-value represents the strength of evidence against the null hypothesis, while the significance level represents the level of evidence required to reject the null hypothesis. If the p-value is less than the significance level, the null hypothesis is rejected, and the alternative hypothesis is accepted.
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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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What if p-value equals alpha?

P-Value Vs Alpha

The p-value is less than or equal to alpha. In this case, we reject the null hypothesis. When this happens, we say that the result is statistically significant. In other words, we are reasonably sure that there is something besides chance alone that gave us an observed sample.
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Is 0.049 statistically significant?

But P values of 0.051 and 0.049 should be interpreted similarly despite the fact that the 0.051 is greater than 0.05 and is therefore not "significant" and that the 0.049 is less than 0.05 and thus is "significant." Reporting actual P values avoids this problem of interpretation.
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When 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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Is p exactly 0.05 statistically significant?

If your p-value is less than or equal to 0.05 (the significance level), you would conclude that your result is statistically significant. This means the evidence is strong enough to reject the null hypothesis in favor of the alternative hypothesis.
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Is p-value .037 significant?

The convention is that p-values less than 0.05 are statistically significant and p-values larger than 0.05 are not statistically significant. There is nothing magic about the 0.05 significance level. They are not the be-all and end-all of research.
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How to know if p-value is statistically significant?

The most common threshold is p < 0.05, which means that the data is likely to occur less than 5% of the time under the null hypothesis. When the p-value falls below the chosen alpha value, then we say the result of the test is statistically significant.
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Is p-value 0.1 acceptable?

And although 0.5 or below is generally regarded as the threshold for significant results, that doesn't always mean that a test result which falls between 0.05 and 0.1 isn't worth looking at. It just means that the evidence against the null hypothesis is weak.
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What is the difference between the .10 .05 and .01 levels of significance?

Common significance levels are 0.10 (1 chance in 10), 0.05 (1 chance in 20), and 0.01 (1 chance in 100). The result of a hypothesis test, as has been seen, is that the null hypothesis is either rejected or not. The significance level for the test is set in advance by the researcher in choosing a critical test value.
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How do you explain p-value to non-technicians?

The p-value is like the strength of the evidence against this defendant. A low p-value is similar to finding clear fingerprints at the scene — it suggests strong evidence against your hypothesis, indicating that your new feature might indeed be making a difference.
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Is p 0.07 significant?

Yes, you can describe a regression coefficient as ``marginally significant'' if the p-value is 0.07. While the conventional threshold for significance is typically set at 0.05, a p-value of 0.07 indicates that there is some evidence against the null hypothesis, suggesting a potential relationship between the variables.
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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 is the difference between 0.05 and 0.01 alpha levels?

Reducing the alpha level from 0.05 to 0.01 reduces the chance of a false positive (called a Type I error) but it also makes it harder to detect differences with a t-test. Any significant results you might obtain would therefore be more trustworthy but there would probably be less of them.
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