What does p-value equal to 0.1 mean?

The p-value is a statistical measure that helps researchers determine the strength of evidence against the null hypothesis. It quantifies the probability of observing the obtained data (or more extreme) if the null hypothesis were true. A p-value equal to 0.1 means that there is a 10% chance of observing the data, or data more extreme, under the assumption that the null hypothesis is true.

What is a p-value?

A p-value is a statistical measure that indicates the strength of evidence against the null hypothesis. It represents the probability of observing the obtained data, or more extreme data, if the null hypothesis were true.

When is a p-value significant?

Typically, a p-value of 0.05 or smaller is considered statistically significant. This means that there is less than a 5% chance of obtaining the observed data or more extreme data under the assumption that the null hypothesis is true.

What does it mean if the p-value is greater than 0.05?

If the p-value is greater than 0.05, it suggests that the observed data is not statistically significant. This means there is a relatively high chance of obtaining the observed data, or more extreme data, under the null hypothesis assumption.

What does it mean if the p-value is less than 0.05?

If the p-value is less than 0.05, it suggests that the observed data is statistically significant. This means there is a relatively low chance of obtaining the observed data, or more extreme data, under the null hypothesis assumption.

Why is a p-value of 0.1 often considered as a threshold for statistical significance in some fields?

In some fields, a p-value of 0.1 is considered a standard threshold for statistical significance. However, in most scientific disciplines, a p-value of 0.1 is not strong evidence against the null hypothesis. It is generally recommended to use a more stringent threshold (e.g., 0.05) to provide more robust inferential conclusions.

What are the limitations of relying solely on the p-value?

Relying solely on the p-value can have limitations. It does not provide information about effect size, practical significance, or the probability of the null hypothesis being true. It is important to consider other factors and context in the interpretation of statistical results.

Can a p-value be equal to zero?

No, a p-value cannot be equal to zero. It represents a probability, and probabilities are always between 0 and 1.

Can a p-value be greater than 1?

No, a p-value cannot be greater than 1. It represents a probability, and probabilities are always between 0 and 1.

What is the relationship between p-value and statistical power?

The p-value and statistical power are related inversely. A low p-value corresponds to high statistical power, meaning that the study has a high chance of detecting a true effect if it exists. Conversely, a high p-value indicates low statistical power, meaning the study may not have had enough participants or sensitivity to detect the effect.

Should I always trust the p-value?

While the p-value is a widely used statistical measure, it should not be blindly trusted. It is crucial to consider other factors such as effect size, study design, and the quality of data collection and analysis.

How does sample size affect the p-value?

Sample size affects the p-value. Generally, larger sample sizes increase statistical power, making it more likely to observe a significant result (lower p-value) if there is a true effect. However, a small effect size can still yield a non-significant p-value with a large sample size.

Is a p-value of 0.1 considered strong evidence against the null hypothesis?

No, a p-value of 0.1 is not considered strong evidence against the null hypothesis in most scientific disciplines. It suggests moderate support against the null hypothesis, but more robust evidence (e.g., p-value ≤ 0.05) is often required for confident conclusions.

Dive into the world of luxury with this video!