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    • Understanding P-Values and Statistical Significance
      • When you perform a statistical test, a p-value helps you determine the significance of your results in relation to the null hypothesis. The null hypothesis (H0) states no relationship exists between the two variables being studied (one variable does not affect the other).
      www.simplypsychology.org/p-value.html
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  2. Oct 13, 2023 · A p-value, or probability value, is a number describing how likely it is that your data would have occurred by random chance (i.e., that the null hypothesis is true). The level of statistical significance is often expressed as a p-value between 0 and 1.

    • What Is P-Value?
    • What Is P-Value Used for?
    • How Is P-Value calculated?
    • The P-Value Approach to Hypothesis Testing
    • Example of P-Value
    • The Bottom Line

    A p-value, or probability value, is a number describing the likelihood of obtaining the observed data under the null hypothesisof a statistical test. The p-value serves as an alternative to rejection points to provide the smallest level of significance at which the null hypothesis would be rejected. A smaller p-value means stronger evidence in favo...

    P-value is often used to promote credibility for studies by scientists and medical researchers as well as reports by government agencies. For example, the U.S. Census Bureau stipulates that any analysis with a p-value greater than 0.10 must be accompanied by a statement that the difference is not statistically different from zero. The Census Bureau...

    P-values are usually calculated using statistical software or p-value tables based on the assumed or known probability distributionof the specific statistic tested. While the sample size influences the reliability of the observed data, the p-value approach to hypothesis testing specifically involves calculating the p-value based on the deviation be...

    The p-value approach to hypothesis testing uses the calculated probability to determine whether there is evidence to reject the null hypothesis. This determination relies heavily on the test statistic, which summarizes the information from the sample relevant to the hypothesis being tested. The null hypothesis, also known as the conjecture, is the ...

    An investor claims that their investment portfolio’s performance is equivalent to that of the Standard & Poor’s (S&P) 500 Index. To determine this, the investor conducts a two-tailed test. The null hypothesis states that the portfolio’s returns are equivalent to the S&P 500’s returns over a specified period, while the alternative hypothesis states ...

    The p-value is used to measure the significance of observational data. When researchers identify an apparent relationship between two variables, there is always a possibility that this correlation might be a coincidence. A p-value calculation helps determine if the observed relationship could arise as a result of chance.

    • Brian Beers
    • 2 min
  3. Sep 23, 2024 · A p-value is the probability of obtaining results at least as extreme as those observed, assuming that the null hypothesis is true. In our blood pressure example, the p-value would answer the question: If the medication truly had no effect (null hypothesis), what’s the probability we would see a reduction in blood pressure as large as (or ...

  4. Apr 9, 2019 · A p-value is the probability of observing a sample statistic that is at least as extreme as your sample statistic, given that the null hypothesis is true. For example, suppose a factory claims that they produce tires that have a mean weight of 200 pounds.

  5. Feb 15, 2022 · The p-value is a crucial part of the statistical results because it quantifies how strongly the sample data contradict the null hypothesis. When the sample data provide sufficient evidence, you can reject the null hypothesis.

  6. P Value Definition. A p value is used in hypothesis testing to help you support or reject the null hypothesis. The p value is the evidence against a null hypothesis. The smaller the p-value, the stronger the evidence that you should reject the null hypothesis.

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