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How do you solve for the p value? - Answers

To solve for the p-value, you first need to conduct a statistical test (such as a t-test, chi-square test, or ANOVA) based on your data and hypothesis. This involves calculating a test statistic that reflects the difference between your observed data and the null hypothesis. Once you have the test statistic, you compare it to a reference distribution (such as the t-distribution or normal distribution) to find the probability of observing a test statistic as extreme as the one calculated, given that the null hypothesis is true. The resulting probability is the p-value, which helps determine the significance of your results.



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How do you solve for the p value? - Answers

https://math.answers.com/math-and-arithmetic/How_do_you_solve_for_the_p_value

To solve for the p-value, you first need to conduct a statistical test (such as a t-test, chi-square test, or ANOVA) based on your data and hypothesis. This involves calculating a test statistic that reflects the difference between your observed data and the null hypothesis. Once you have the test statistic, you compare it to a reference distribution (such as the t-distribution or normal distribution) to find the probability of observing a test statistic as extreme as the one calculated, given that the null hypothesis is true. The resulting probability is the p-value, which helps determine the significance of your results.



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https://math.answers.com/math-and-arithmetic/How_do_you_solve_for_the_p_value

How do you solve for the p value? - Answers

To solve for the p-value, you first need to conduct a statistical test (such as a t-test, chi-square test, or ANOVA) based on your data and hypothesis. This involves calculating a test statistic that reflects the difference between your observed data and the null hypothesis. Once you have the test statistic, you compare it to a reference distribution (such as the t-distribution or normal distribution) to find the probability of observing a test statistic as extreme as the one calculated, given that the null hypothesis is true. The resulting probability is the p-value, which helps determine the significance of your results.

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      To solve for the p-value, you first need to conduct a statistical test (such as a t-test, chi-square test, or ANOVA) based on your data and hypothesis. This involves calculating a test statistic that reflects the difference between your observed data and the null hypothesis. Once you have the test statistic, you compare it to a reference distribution (such as the t-distribution or normal distribution) to find the probability of observing a test statistic as extreme as the one calculated, given that the null hypothesis is true. The resulting probability is the p-value, which helps determine the significance of your results.

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