{"id":16031,"date":"2024-11-25T06:11:07","date_gmt":"2024-11-25T06:11:07","guid":{"rendered":"https:\/\/www.pickl.ai\/blog\/?p=16031"},"modified":"2025-10-09T12:16:42","modified_gmt":"2025-10-09T06:46:42","slug":"p-value-in-statistics","status":"publish","type":"post","link":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/","title":{"rendered":"What Is P-Value in Statistics?"},"content":{"rendered":"\n<p><strong>Summary: <\/strong>The p-value is a crucial statistical measure that quantifies the strength of evidence against the null hypothesis in hypothesis testing. A smaller p-value indicates stronger evidence for rejecting the null hypothesis, guiding researchers in making informed decisions. Understanding p-values helps in interpreting data accurately across various fields<\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_81 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Introduction\" >Introduction<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#What_is_a_P-Value\" >What is a P-Value?<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#How_is_P-Value_Derived\" >How is P-Value Derived?<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#How_P-Value_is_Used_in_Hypothesis_Testing\" >How P-Value is Used in Hypothesis Testing?<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Overview_of_the_Hypothesis_Testing_Process\" >Overview of the Hypothesis Testing Process<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Role_of_P-Value_in_Determining_Statistical_Significance\" >Role of P-Value in Determining Statistical Significance<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Significance_Level_Alpha_and_Its_Relationship_with_P-Value\" >Significance Level (Alpha) and Its Relationship with P-Value<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Decision-Making_Rejecting_or_Failing_to_Reject_the_Null_Hypothesis\" >Decision-Making: Rejecting or Failing to Reject the Null Hypothesis<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Interpreting_P-Value\" >Interpreting P-Value<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Understanding_P-Value_Thresholds\" >Understanding P-Value Thresholds<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#p_%3C_005\" >p &lt; 0.05<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#p_%3C_001\" >p &lt; 0.01<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#p_%3E_005\" >p &gt; 0.05<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Small_P-Value_Strong_Evidence_Against_the_Null_Hypothesis\" >Small P-Value: Strong Evidence Against the Null Hypothesis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Large_P-Value_Insufficient_Evidence_to_Reject_the_Null_Hypothesis\" >Large P-Value: Insufficient Evidence to Reject the Null Hypothesis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Common_Misconceptions_About_P-Values\" >Common Misconceptions About P-Values<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Common_Applications_of_P-Value\" >Common Applications of P-Value<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Medical_Studies\" >Medical Studies<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Social_Sciences\" >Social Sciences<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Business_Analytics\" >Business Analytics<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Limitations_of_P-Value\" >Limitations of P-Value<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-22\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#P-Hacking_and_Over-Reliance_on_P-Values\" >P-Hacking and Over-Reliance on P-Values<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-23\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Binary_Decision-Making\" >Binary Decision-Making<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-24\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#The_Role_of_Effect_Size_and_Confidence_Intervals\" >The Role of Effect Size and Confidence Intervals<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-25\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Alternative_Approaches_to_P-Value\" >Alternative Approaches to P-Value<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-26\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Introduction_to_Bayesian_Statistics\" >Introduction to Bayesian Statistics<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-27\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Why_Some_Statisticians_Advocate_for_Alternatives\" >Why Some Statisticians Advocate for Alternatives<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-28\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Other_Alternatives\" >Other Alternatives<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-29\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Closing_Statements\" >Closing Statements<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-30\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-31\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#What_Does_a_P-Value_Signify_in_Statistics\" >What Does a P-Value Signify in Statistics?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-32\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#How_Do_You_Interpret_a_P-Value_of_003\" >How Do You Interpret a P-Value of 0.03?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-33\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#What_are_Common_Misconceptions_about_P-Values\" >What are Common Misconceptions about P-Values?<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2 id=\"introduction\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Introduction\"><\/span><strong>Introduction<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p><a href=\"https:\/\/pickl.ai\/blog\/statistics-for-data-science\/\">Statistics<\/a> plays a crucial role in <a href=\"https:\/\/pickl.ai\/blog\/different-types-of-data-analysis\/\">data analysis<\/a>. It helps us draw meaningful conclusions from complex data sets. A key <a href=\"https:\/\/pickl.ai\/blog\/parameters-in-statistical-analysis\/\">aspect of statistical analysis<\/a> is hypothesis testing, which guides decision-making. Central to this process is the p-value, a statistical measure that helps assess the strength of evidence against the null hypothesis.&nbsp;<\/p>\n\n\n\n<p>In this blog, &#8220;What Is P-Value in Statistics?&#8221; we will explore its definition, how it&#8217;s used in <a href=\"https:\/\/pickl.ai\/blog\/hypothesis-testing-in-statistics\/\">hypothesis testing<\/a>, and its significance in making informed decisions. Our goal is to demystify the p-value and its practical applications in research.<\/p>\n\n\n\n<p><strong>Key Takeaways<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>A p-value measures evidence against the null hypothesis.<\/li>\n\n\n\n<li>Small p-values (e.g., &lt; 0.05) indicate strong evidence to reject the null hypothesis.<\/li>\n\n\n\n<li>Larger p-values suggest insufficient evidence to reject it.<\/li>\n\n\n\n<li>Misinterpretations can lead to erroneous conclusions; context matters.<\/li>\n\n\n\n<li>Alternatives like Bayesian methods and effect sizes provide additional insights beyond p-values.<\/li>\n<\/ul>\n\n\n\n<h2 id=\"what-is-a-p-value\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_a_P-Value\"><\/span><strong>What is a P-Value?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>A p-value is a probability that measures the strength of evidence against the null hypothesis in a statistical test. It quantifies how likely it is to observe the <a href=\"https:\/\/pickl.ai\/blog\/difference-between-data-and-information\/\">data<\/a> or something more extreme, assuming that the null hypothesis is true. In simple terms, the smaller the p-value, the stronger the evidence against the null hypothesis.<\/p>\n\n\n\n<h3 id=\"how-is-p-value-derived\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_is_P-Value_Derived\"><\/span><strong>How is P-Value Derived?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>To derive the p-value, a statistical test compares the observed data to what we would expect under the null hypothesis. Using test statistics like t-tests or chi-square tests, we calculate a value that measures how far the data deviates from the null hypothesis.&nbsp;<\/p>\n\n\n\n<p>The p-value is then the probability of obtaining a result as extreme as the one observed, given that the null hypothesis is correct.<\/p>\n\n\n\n<h2 id=\"how-p-value-is-used-in-hypothesis-testing\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_P-Value_is_Used_in_Hypothesis_Testing\"><\/span><strong>How P-Value is Used in Hypothesis Testing?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/lh7-rt.googleusercontent.com\/docsz\/AD_4nXdQ-18rsI6XI99rYqSMkRwe5VIzpUJstiGdBE3QMEpoLNmpzo5ARQ_kIKGqYTDDPZmp_BS3Srpb6ENCgV1DTzOGmabPbLFBsB2pcxw9dZTpNtQf3fUmrqtXP70Gt0zRzysozAO5Qg?key=8ZqANygbjoovdj-t3JFAmcNG\" alt=\"Flowchart showing P-Value in hypothesis testing process.\"\/><\/figure>\n\n\n\n<p>Hypothesis testing is a fundamental statistical process used to evaluate the evidence a sample of data provides against a specific claim or hypothesis. The p-value is critical in helping researchers and analysts decide whether a hypothesis is valid.&nbsp;<\/p>\n\n\n\n<p>Now, we&#8217;ll explore how p-values are used in hypothesis testing, their relationship with statistical significance, and the decision-making process involved.<\/p>\n\n\n\n<h3 id=\"overview-of-the-hypothesis-testing-process\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Overview_of_the_Hypothesis_Testing_Process\"><\/span><strong>Overview of the Hypothesis Testing Process<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The <a href=\"https:\/\/pickl.ai\/blog\/process-and-types-of-hypothesis-testing-in-statistics\/\">process of hypothesis testing<\/a> begins with formulating <a href=\"https:\/\/pickl.ai\/blog\/difference-between-null-and-alternate-hypothesis\/\">two competing hypothese<\/a>s: the null hypothesis (H\u2080) and the alternative hypothesis (H\u2081). The null hypothesis typically suggests that there is no effect or no difference, while the alternative hypothesis proposes the opposite\u2014that there is an effect or a significant difference.<\/p>\n\n\n\n<p>Once these hypotheses are established, a sample of <a href=\"https:\/\/pickl.ai\/blog\/understanding-data-collection-methods-types-examples-and-tools\/\">data is collected<\/a>, and a statistical test is conducted to evaluate the evidence. The goal is to determine whether the sample data provides enough evidence to reject the null hypothesis in favour of the alternative hypothesis.<\/p>\n\n\n\n<h3 id=\"role-of-p-value-in-determining-statistical-significance\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Role_of_P-Value_in_Determining_Statistical_Significance\"><\/span><strong>Role of P-Value in Determining Statistical Significance<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The p-value is a critical element of this process. It is the probability of observing data as extreme as\u2014or more extreme than\u2014the results obtained, assuming the null hypothesis is true. In other words, the p-value quantifies the strength of the evidence against the null hypothesis.<\/p>\n\n\n\n<p>A smaller p-value indicates stronger evidence against the null hypothesis. Conversely, a larger p-value suggests weaker evidence, meaning the observed data is more likely to be under the null hypothesis. The p-value helps decide whether the results are statistically significant.<\/p>\n\n\n\n<h3 id=\"significance-level-alpha-and-its-relationship-with-p-value\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Significance_Level_Alpha_and_Its_Relationship_with_P-Value\"><\/span><strong>Significance Level (Alpha) and Its Relationship with P-Value<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The significance level, denoted by alpha (\u03b1), is a threshold set before the test to determine whether the p-value is sufficiently small to reject the null hypothesis. Typically, researchers use a significance level of 0.05 (5%), but this can vary depending on the field or study.<\/p>\n\n\n\n<p>If the p-value is less than or equal to alpha (e.g., p \u2264 0.05), the results are considered statistically significant, and the null hypothesis is rejected.&nbsp;<\/p>\n\n\n\n<p>If the p-value is greater than alpha (e.g., p &gt; 0.05), the null hypothesis is not rejected, meaning the evidence is insufficient to support the alternative hypothesis.<\/p>\n\n\n\n<h3 id=\"decision-making-rejecting-or-failing-to-reject-the-null-hypothesis\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Decision-Making_Rejecting_or_Failing_to_Reject_the_Null_Hypothesis\"><\/span><strong>Decision-Making: Rejecting or Failing to Reject the Null Hypothesis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The decision to reject or fail to reject the null hypothesis is a critical part of hypothesis testing. When the p-value is small (below the chosen significance level), it suggests that the sample data is inconsistent with the null hypothesis, and we reject it in favour of the alternative hypothesis.&nbsp;<\/p>\n\n\n\n<p>However, failing to reject the null hypothesis does not prove it is true; it simply indicates insufficient evidence to support the alternative hypothesis.<\/p>\n\n\n\n<p>Ultimately, the p-value helps researchers make informed decisions about their hypotheses and the validity of their statistical conclusions.<\/p>\n\n\n\n<h2 id=\"interpreting-p-value\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Interpreting_P-Value\"><\/span><strong>Interpreting P-Value<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>When performing statistical hypothesis testing, the p-value is critical to determining whether the evidence is strong enough to reject the null hypothesis. It measures the probability of observing the data or something more extreme if the null hypothesis is true. Interpreting the p-value correctly is essential for making sound conclusions.&nbsp;<\/p>\n\n\n\n<p>Let&#8217;s dive into the key concepts around interpreting p-values and common misunderstandings that arise.<\/p>\n\n\n\n<h3 id=\"understanding-p-value-thresholds\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Understanding_P-Value_Thresholds\"><\/span><strong>Understanding P-Value Thresholds<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>P-values are often compared against a predefined significance level, typically denoted as alpha (\u03b1). The most common threshold is 0.05, but researchers may use other values, such as 0.01 or 0.10, depending on the context.<\/p>\n\n\n\n<h4 id=\"p-0-05\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"p_%3C_005\"><\/span><strong>p &lt; 0.05<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>A p-value less than 0.05 suggests strong evidence against the null hypothesis. This means the observed results are statistically significant, and the null hypothesis is likely untrue. In other words, the probability of getting such a result by chance is less than 5%.<\/p>\n\n\n\n<h4 id=\"p-0-01\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"p_%3C_001\"><\/span><strong>p &lt; 0.01<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>A p-value less than 0.01 indicates even stronger evidence against the null hypothesis, with less than a 1% probability that the result is due to random chance.<\/p>\n\n\n\n<h4 id=\"p-0-05-2\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"p_%3E_005\"><\/span><strong>p &gt; 0.05<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>A p-value greater than 0.05 implies weak evidence against the null hypothesis, suggesting that the data does not show enough evidence to reject it.<\/p>\n\n\n\n<h3 id=\"small-p-value-strong-evidence-against-the-null-hypothesis\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Small_P-Value_Strong_Evidence_Against_the_Null_Hypothesis\"><\/span><strong>Small P-Value: Strong Evidence Against the Null Hypothesis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A &#8220;small&#8221; p-value, typically below 0.05, provides strong evidence that the data do not support the null hypothesis.&nbsp;<\/p>\n\n\n\n<p>For example, if a study tests a new drug and the p-value is 0.02, this indicates that assuming the null hypothesis (no effect) is true, there is only a 2% chance the observed results could be due to random variation.&nbsp;<\/p>\n\n\n\n<p>In this case, researchers would likely reject the null hypothesis, concluding the drug has a significant impact.<\/p>\n\n\n\n<p>However, while a small p-value can indicate a true effect, it does not measure the size or importance of the effect itself. A small p-value does not guarantee a meaningful or practically significant result.<\/p>\n\n\n\n<h3 id=\"large-p-value-insufficient-evidence-to-reject-the-null-hypothesis\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Large_P-Value_Insufficient_Evidence_to_Reject_the_Null_Hypothesis\"><\/span><strong>Large P-Value: Insufficient Evidence to Reject the Null Hypothesis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A &#8220;large&#8221; p-value above the commonly used threshold of 0.05 suggests there is insufficient evidence to reject the null hypothesis.&nbsp;<\/p>\n\n\n\n<p>For example, a p-value of 0.12 means a 12% chance the observed data could have occurred if the null hypothesis were true. In this case, researchers would not reject the null hypothesis, concluding that the data does not provide strong evidence for an effect.<\/p>\n\n\n\n<p>It\u2019s important to remember that failing to reject the null hypothesis does not prove it is true; it merely indicates a lack of strong evidence against it.<\/p>\n\n\n\n<h3 id=\"common-misconceptions-about-p-values\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Common_Misconceptions_About_P-Values\"><\/span><strong>Common Misconceptions About P-Values<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>One common misconception is that a p-value tells us the probability that the null hypothesis is true. It only tells us the probability of obtaining the observed results, assuming the null hypothesis is true.<\/p>\n\n\n\n<p>Another misconception is treating the 0.05 threshold as a strict rule. A p-value just below 0.05 does not automatically mean a result is \u201csignificant\u201d in a meaningful way. Similarly, a p-value slightly above 0.05 is not definitive proof of no effect. Researchers should always consider their findings&#8217; context, study design, and practical significance.<\/p>\n\n\n\n<p>Lastly, p-hacking\u2014manipulating data or repeatedly testing hypotheses until a significant result is found\u2014can lead to misleading interpretations of p-values. Thus, p-values should be interpreted cautiously, and conclusions should always be supported by other evidence and scientific reasoning.<\/p>\n\n\n\n<h2 id=\"common-applications-of-p-value\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Common_Applications_of_P-Value\"><\/span><strong>Common Applications of P-Value<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/lh7-rt.googleusercontent.com\/docsz\/AD_4nXcde9iBbayeMcYYeEYEBIpUzN_f9-u0YRUyiwHKUHzAUBVsMqGTxiDrWWFkaN0jiyJ_0PUeFqaAM71nhmDgz3gAdJPFrb3m62KMpMrs7MXvsBTz9qeo-LbIHSkTIwgET5sxSbLlzQ?key=8ZqANygbjoovdj-t3JFAmcNG\" alt=\"Common Applications of P-Value\"\/><\/figure>\n\n\n\n<p>The p-value is widely applied across various fields, helping researchers make informed decisions and draw conclusions. Let\u2019s explore how p-values are used in real-world scenarios.<\/p>\n\n\n\n<h3 id=\"medical-studies\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Medical_Studies\"><\/span><strong>Medical Studies<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>In clinical trials, p-values help determine whether a new drug or treatment is effective.&nbsp;<\/p>\n\n\n\n<p>For example, suppose a p-value is less than 0.05. In that case, researchers might conclude that the treatment has a statistically significant effect on the health outcome, rejecting the null hypothesis that the drug has no effect. This application ensures that new medications meet scientific standards before being approved.<\/p>\n\n\n\n<h3 id=\"social-sciences\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Social_Sciences\"><\/span><strong>Social Sciences<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>In psychology or sociology, p-values are essential when testing theories or interventions.&nbsp;<\/p>\n\n\n\n<p>For instance, a researcher testing the effectiveness of a new educational program would use a p-value to assess whether the observed improvement in students\u2019 performance is due to the program or just random chance. A low p-value suggests that the program has a meaningful impact.<\/p>\n\n\n\n<h3 id=\"business-analytics\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Business_Analytics\"><\/span><strong>Business Analytics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>In business, p-values help analysts evaluate marketing strategies or product changes.&nbsp;<\/p>\n\n\n\n<p>For example, when testing a new<a href=\"https:\/\/predis.ai\/use-cases\/instagram-ad-maker\/\" rel=\"nofollow\"> instagram advertisement campaign<\/a>, a company might use a p-value to assess whether the observed increase in sales is statistically significant, ensuring that decisions are data-driven and not based on chance fluctuations.<\/p>\n\n\n\n<p>Interpreting p-values enables researchers and analysts to make data-driven decisions confidently in all these fields.<\/p>\n\n\n\n<h2 id=\"limitations-of-p-value\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Limitations_of_P-Value\"><\/span><strong>Limitations of P-Value<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>While p-values are vital in hypothesis testing, researchers must consider several limitations to avoid misinterpretation or misuse.<\/p>\n\n\n\n<h3 id=\"p-hacking-and-over-reliance-on-p-values\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"P-Hacking_and_Over-Reliance_on_P-Values\"><\/span><strong>P-Hacking and Over-Reliance on P-Values<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>One significant issue is p-hacking, where researchers manipulate data or test multiple hypotheses to achieve a desired p-value (usually less than 0.05). This practice can lead to false conclusions and inflate the likelihood of finding statistically significant results, even when the findings are not genuinely meaningful.&nbsp;<\/p>\n\n\n\n<p>Over-reliance on p-values can lead to dismissing other important statistical measures, like the effect size, that provide a clearer understanding of the data.<\/p>\n\n\n\n<h3 id=\"binary-decision-making\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Binary_Decision-Making\"><\/span><strong>Binary Decision-Making<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Another limitation is the binary nature of p-values. When researchers use a strict threshold (typically 0.05) to reject or fail to reject the null hypothesis, they may ignore valuable nuances in the data.&nbsp;<\/p>\n\n\n\n<p>A p-value slightly above 0.05 does not automatically mean the null hypothesis is true or the results are useless. This oversimplification can lead to missing essential findings or failing to recognise significant effects.<\/p>\n\n\n\n<h3 id=\"the-role-of-effect-size-and-confidence-intervals\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"The_Role_of_Effect_Size_and_Confidence_Intervals\"><\/span><strong>The Role of Effect Size and Confidence Intervals<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Incorporating effect size and confidence intervals alongside p-values provides a more comprehensive data view. Effect size measures the magnitude of an effect, while confidence intervals offer a range of plausible values for the parameter. These metrics help us understand the practical significance of results beyond just the statistical significance indicated by p-values.<\/p>\n\n\n\n<h2 id=\"alternative-approaches-to-p-value\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Alternative_Approaches_to_P-Value\"><\/span><strong>Alternative Approaches to P-Value<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/lh7-rt.googleusercontent.com\/docsz\/AD_4nXeQiDkq3tJn2oUKz1puSOeHPZqUZTnWTYkBvoBxbHCVeP2O9MIci8rMaQ7paY9cF3GqWlPXMNS1eS9FOE4lH0kqKt3v5JS_sTMhJRlg7HxTmD0OP3taP5qlA09_UF0FRmD202Pblw?key=8ZqANygbjoovdj-t3JFAmcNG\" alt=\"Comparison of p-value alternatives in statistics.\"\/><\/figure>\n\n\n\n<p>While the p-value has been a cornerstone of statistical hypothesis testing, it has limitations. Over the years, alternative approaches have gained popularity among statisticians, offering different perspectives on assessing the strength of evidence.&nbsp;<\/p>\n\n\n\n<p>Among the most notable alternatives is Bayesian statistics, but other methods also challenge the traditional reliance on p-values. This section explores these approaches, their rationale, and their advantages and disadvantages.<\/p>\n\n\n\n<h3 id=\"introduction-to-bayesian-statistics\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Introduction_to_Bayesian_Statistics\"><\/span><strong>Introduction to Bayesian Statistics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Bayesian statistics offers a fundamentally different approach to <a href=\"https:\/\/pickl.ai\/blog\/what-is-statistical-analysis\/\">statistical analysis<\/a> than frequentist methods, of which p-values are a part. Instead of testing hypotheses based on the likelihood of observing the data under a null hypothesis,&nbsp;<\/p>\n\n\n\n<p>Bayesian methods update the probability of a hypothesis as more data becomes available. This approach incorporates prior knowledge or beliefs about a hypothesis, updated in light of new evidence.<\/p>\n\n\n\n<p>In <a href=\"https:\/\/en.wikipedia.org\/wiki\/Bayesian_statistics\">Bayesian statistics<\/a>, the focus is on calculating the posterior probability of a hypothesis given the data rather than determining whether a p-value is below a certain threshold. This method allows for a more nuanced interpretation of statistical evidence and provides a richer, probabilistic view of uncertainty.<\/p>\n\n\n\n<p><strong>Pros of Bayesian Statistics<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Incorporates Prior Knowledge<\/strong>: Bayesian methods allow for integrating prior knowledge or expert opinion, making the analysis more flexible and informed.<\/li>\n\n\n\n<li><strong>Probabilistic Interpretation<\/strong>: Bayesian statistics provide a probability distribution over possible hypotheses, offering a more intuitive and comprehensive understanding of uncertainty.<\/li>\n\n\n\n<li><strong>Flexibility with Data<\/strong>: Bayesian methods can be more adaptable to different data types and research questions, providing more robust conclusions in some cases.<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons of Bayesian Statistics<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Computational Complexity<\/strong>: Bayesian methods often require more complex computations, especially for large datasets or models with many parameters.<\/li>\n\n\n\n<li><strong>The subjectivity of Priors<\/strong>: The prior choice can influence the results, and determining a &#8220;correct&#8221; prior can be subjective and controversial, leading to debates over model assumptions.<\/li>\n\n\n\n<li><strong>Learning Curve<\/strong>: Bayesian analysis requires a deeper understanding of probability and <a href=\"https:\/\/pickl.ai\/blog\/statistical-modeling-types-and-components\/\">statistical modelling<\/a>, which can be a barrier for researchers accustomed to traditional methods.<\/li>\n<\/ul>\n\n\n\n<h3 id=\"why-some-statisticians-advocate-for-alternatives\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Why_Some_Statisticians_Advocate_for_Alternatives\"><\/span><strong>Why Some Statisticians Advocate for Alternatives<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Many statisticians advocate for alternatives to p-values because they believe that p-values alone can lead to misinterpretation and oversimplification of complex data.&nbsp;<\/p>\n\n\n\n<p>A major critique of p-values is their binary nature\u2014decisions are often made based on an arbitrary threshold (e.g., 0.05), which doesn&#8217;t necessarily reflect the true strength of evidence. This has led to issues like p-hacking, where researchers <a href=\"https:\/\/pickl.ai\/blog\/data-manipulation-types-examples\/\">manipulate data<\/a> or test multiple hypotheses until they achieve a significant result.<\/p>\n\n\n\n<p>Additionally, p-values do not directly measure the probability that a hypothesis is true. They only tell us the likelihood of obtaining results as extreme as the observed data, assuming the null hypothesis is true. This limitation has prompted statisticians to explore other methods that offer a more comprehensive understanding of uncertainty.<\/p>\n\n\n\n<h3 id=\"other-alternatives\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Other_Alternatives\"><\/span><strong>Other Alternatives<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Other alternatives to p-values, in addition to Bayesian methods, include confidence intervals and effect sizes. <a href=\"https:\/\/www.investopedia.com\/terms\/c\/confidenceinterval.asp\">Confidence intervals<\/a> provide a range of values within which the true parameter value is likely to fall, offering more insight than a single p-value.&nbsp;<\/p>\n\n\n\n<p>Effect sizes quantify the magnitude of a relationship or difference, helping to assess the practical significance of a result, which p-values often fail to convey.<\/p>\n\n\n\n<p>However, each alternative also has its drawbacks. Confidence intervals can still be misleading if not interpreted correctly, and effect sizes require additional context to be meaningful.<\/p>\n\n\n\n<h2 id=\"closing-statements\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Closing_Statements\"><\/span><strong>Closing Statements<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Understanding the p-value is essential for effective statistical analysis. It measures the strength of evidence against the null hypothesis, guiding researchers in hypothesis testing. A small p-value indicates strong evidence against the null hypothesis, while a larger p-value suggests insufficient evidence to reject it.&nbsp;<\/p>\n\n\n\n<p>By grasping the nuances of p-values, researchers can make informed decisions based on data, leading to more accurate conclusions in various fields, including medicine, social sciences, and business analytics.<\/p>\n\n\n\n<h2 id=\"frequently-asked-questions\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span><strong>Frequently Asked Questions<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 id=\"what-does-a-p-value-signify-in-statistics\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_Does_a_P-Value_Signify_in_Statistics\"><\/span><strong>What Does a P-Value Signify in Statistics?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>If the null hypothesis is true, a p-value indicates the probability of observing data as extreme as the current results. A smaller p-value suggests stronger evidence against the null hypothesis, while a larger one indicates weaker evidence.<\/p>\n\n\n\n<h3 id=\"how-do-you-interpret-a-p-value-of-0-03\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_Do_You_Interpret_a_P-Value_of_003\"><\/span><strong>How Do You Interpret a P-Value of 0.03?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A p-value of 0.03 suggests that there is only a 3% chance of observing the data if the null hypothesis is true. Since it is below the common significance level of 0.05, it typically leads researchers to reject the null hypothesis.<\/p>\n\n\n\n<h3 id=\"what-are-common-misconceptions-about-p-values\" class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_are_Common_Misconceptions_about_P-Values\"><\/span><strong>What are Common Misconceptions about P-Values?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>One misconception is that a p-value indicates the probability that the null hypothesis is true. It measures the likelihood of observing the data, assuming the null hypothesis holds true. Additionally, p-values should not be viewed as definitive proof of significance.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"Explore what a p-value in statistics means and its importance in hypothesis testing and decision-making.\n","protected":false},"author":27,"featured_media":16034,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[2346],"tags":[3492],"ppma_author":[2217,2184],"class_list":{"0":"post-16031","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-statistics","8":"tag-p-value-in-statistics"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.3 (Yoast SEO v27.0) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Understanding P-Value in Statistics: Key Concepts Explained<\/title>\n<meta name=\"description\" content=\"Learn what a p-value in statistics means and its role in hypothesis testing. You will also learn how you can interpret it effectively.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What Is P-Value in Statistics?\" \/>\n<meta property=\"og:description\" content=\"Learn what a p-value in statistics means and its role in hypothesis testing. You will also learn how you can interpret it effectively.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/\" \/>\n<meta property=\"og:site_name\" content=\"Pickl.AI\" \/>\n<meta property=\"article:published_time\" content=\"2024-11-25T06:11:07+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-10-09T06:46:42+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"628\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Julie Bowie, Anubhav Jain\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Julie Bowie\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"12 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/\"},\"author\":{\"name\":\"Julie Bowie\",\"@id\":\"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/c4ff9404600a51d9924b7d4356505a40\"},\"headline\":\"What Is P-Value in Statistics?\",\"datePublished\":\"2024-11-25T06:11:07+00:00\",\"dateModified\":\"2025-10-09T06:46:42+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/\"},\"wordCount\":2535,\"commentCount\":0,\"image\":{\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg\",\"keywords\":[\"P-Value in Statistics\"],\"articleSection\":[\"Statistics\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/\",\"url\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/\",\"name\":\"Understanding P-Value in Statistics: Key Concepts Explained\",\"isPartOf\":{\"@id\":\"https:\/\/www.pickl.ai\/blog\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg\",\"datePublished\":\"2024-11-25T06:11:07+00:00\",\"dateModified\":\"2025-10-09T06:46:42+00:00\",\"author\":{\"@id\":\"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/c4ff9404600a51d9924b7d4356505a40\"},\"description\":\"Learn what a p-value in statistics means and its role in hypothesis testing. You will also learn how you can interpret it effectively.\",\"breadcrumb\":{\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#primaryimage\",\"url\":\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg\",\"contentUrl\":\"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg\",\"width\":1200,\"height\":628,\"caption\":\"P-Value in Statistics\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.pickl.ai\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Statistics\",\"item\":\"https:\/\/www.pickl.ai\/blog\/category\/statistics\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"What Is P-Value in Statistics?\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.pickl.ai\/blog\/#website\",\"url\":\"https:\/\/www.pickl.ai\/blog\/\",\"name\":\"Pickl.AI\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.pickl.ai\/blog\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/c4ff9404600a51d9924b7d4356505a40\",\"name\":\"Julie Bowie\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/image\/6d567bb101286f6a3fd640329347e093\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/317b68e296bf24b015e618e1fb1fc49f6d8b138bb9cf93c16da2194964636c7d?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/317b68e296bf24b015e618e1fb1fc49f6d8b138bb9cf93c16da2194964636c7d?s=96&d=mm&r=g\",\"caption\":\"Julie Bowie\"},\"description\":\"I am Julie Bowie a data scientist with a specialization in machine learning. I have conducted research in the field of language processing and has published several papers in reputable journals.\",\"url\":\"https:\/\/www.pickl.ai\/blog\/author\/juliebowie\/\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Understanding P-Value in Statistics: Key Concepts Explained","description":"Learn what a p-value in statistics means and its role in hypothesis testing. You will also learn how you can interpret it effectively.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/","og_locale":"en_US","og_type":"article","og_title":"What Is P-Value in Statistics?","og_description":"Learn what a p-value in statistics means and its role in hypothesis testing. You will also learn how you can interpret it effectively.","og_url":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/","og_site_name":"Pickl.AI","article_published_time":"2024-11-25T06:11:07+00:00","article_modified_time":"2025-10-09T06:46:42+00:00","og_image":[{"width":1200,"height":628,"url":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg","type":"image\/jpeg"}],"author":"Julie Bowie, Anubhav Jain","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Julie Bowie","Est. reading time":"12 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#article","isPartOf":{"@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/"},"author":{"name":"Julie Bowie","@id":"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/c4ff9404600a51d9924b7d4356505a40"},"headline":"What Is P-Value in Statistics?","datePublished":"2024-11-25T06:11:07+00:00","dateModified":"2025-10-09T06:46:42+00:00","mainEntityOfPage":{"@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/"},"wordCount":2535,"commentCount":0,"image":{"@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#primaryimage"},"thumbnailUrl":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg","keywords":["P-Value in Statistics"],"articleSection":["Statistics"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/","url":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/","name":"Understanding P-Value in Statistics: Key Concepts Explained","isPartOf":{"@id":"https:\/\/www.pickl.ai\/blog\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#primaryimage"},"image":{"@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#primaryimage"},"thumbnailUrl":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg","datePublished":"2024-11-25T06:11:07+00:00","dateModified":"2025-10-09T06:46:42+00:00","author":{"@id":"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/c4ff9404600a51d9924b7d4356505a40"},"description":"Learn what a p-value in statistics means and its role in hypothesis testing. You will also learn how you can interpret it effectively.","breadcrumb":{"@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#primaryimage","url":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg","contentUrl":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg","width":1200,"height":628,"caption":"P-Value in Statistics"},{"@type":"BreadcrumbList","@id":"https:\/\/www.pickl.ai\/blog\/p-value-in-statistics\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.pickl.ai\/blog\/"},{"@type":"ListItem","position":2,"name":"Statistics","item":"https:\/\/www.pickl.ai\/blog\/category\/statistics\/"},{"@type":"ListItem","position":3,"name":"What Is P-Value in Statistics?"}]},{"@type":"WebSite","@id":"https:\/\/www.pickl.ai\/blog\/#website","url":"https:\/\/www.pickl.ai\/blog\/","name":"Pickl.AI","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.pickl.ai\/blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/c4ff9404600a51d9924b7d4356505a40","name":"Julie Bowie","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.pickl.ai\/blog\/#\/schema\/person\/image\/6d567bb101286f6a3fd640329347e093","url":"https:\/\/secure.gravatar.com\/avatar\/317b68e296bf24b015e618e1fb1fc49f6d8b138bb9cf93c16da2194964636c7d?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/317b68e296bf24b015e618e1fb1fc49f6d8b138bb9cf93c16da2194964636c7d?s=96&d=mm&r=g","caption":"Julie Bowie"},"description":"I am Julie Bowie a data scientist with a specialization in machine learning. I have conducted research in the field of language processing and has published several papers in reputable journals.","url":"https:\/\/www.pickl.ai\/blog\/author\/juliebowie\/"}]}},"jetpack_featured_media_url":"https:\/\/www.pickl.ai\/blog\/wp-content\/uploads\/2024\/11\/image3.jpg","authors":[{"term_id":2217,"user_id":27,"is_guest":0,"slug":"juliebowie","display_name":"Julie Bowie","avatar_url":"https:\/\/secure.gravatar.com\/avatar\/317b68e296bf24b015e618e1fb1fc49f6d8b138bb9cf93c16da2194964636c7d?s=96&d=mm&r=g","first_name":"Julie","user_url":"","last_name":"Bowie","description":"I am Julie Bowie a data scientist with a specialization in machine learning. I have conducted research in the field of language processing and has published several papers in reputable journals."},{"term_id":2184,"user_id":17,"is_guest":0,"slug":"anubhavjain","display_name":"Anubhav Jain","avatar_url":"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/05\/avatar_user_17_1715317161-96x96.jpg","first_name":"Anubhav","user_url":"","last_name":"Jain","description":"I am a dedicated data enthusiast and aspiring leader within the realm of data analytics, boasting an engineering background and hands-on experience in the field of data science. My unwavering commitment lies in harnessing the power of data to tackle intricate challenges, all with the goal of making a positive societal impact. Currently, I am gaining valuable insights as a Data Analyst at TransOrg, where I've had the opportunity to delve into the vast potential of machine learning and artificial intelligence in providing innovative solutions to both businesses and learning institutions."}],"_links":{"self":[{"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/posts\/16031","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/users\/27"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/comments?post=16031"}],"version-history":[{"count":3,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/posts\/16031\/revisions"}],"predecessor-version":[{"id":25381,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/posts\/16031\/revisions\/25381"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/media\/16034"}],"wp:attachment":[{"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/media?parent=16031"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/categories?post=16031"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/tags?post=16031"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.pickl.ai\/blog\/wp-json\/wp\/v2\/ppma_author?post=16031"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}