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id="toc-Estimator_selection" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Estimator_selection"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.3</span> <span>Estimator selection</span> </div> </a> <ul id="toc-Estimator_selection-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Analysis_methods" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Analysis_methods"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.4</span> <span>Analysis methods</span> </div> </a> <ul id="toc-Analysis_methods-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Interpretation" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Interpretation"> <div class="vector-toc-text"> <span class="vector-toc-numb">2.5</span> <span>Interpretation</span> </div> </a> <ul id="toc-Interpretation-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Addressing_statistical_bias" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Addressing_statistical_bias"> <div class="vector-toc-text"> <span class="vector-toc-numb">3</span> <span>Addressing statistical bias</span> </div> </a> <ul id="toc-Addressing_statistical_bias-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-See_also" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#See_also"> <div class="vector-toc-text"> <span class="vector-toc-numb">4</span> <span>See also</span> </div> </a> <ul id="toc-See_also-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-References" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#References"> <div class="vector-toc-text"> <span class="vector-toc-numb">5</span> <span>References</span> </div> </a> <ul id="toc-References-sublist" 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<div id="contentSub"><div id="mw-content-subtitle"></div></div> <div id="mw-content-text" class="mw-body-content"><div class="mw-content-ltr mw-parser-output" lang="en" dir="ltr"><div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none">Systemic inaccuracy</div> <style data-mw-deduplicate="TemplateStyles:r1236090951">.mw-parser-output .hatnote{font-style:italic}.mw-parser-output div.hatnote{padding-left:1.6em;margin-bottom:0.5em}.mw-parser-output .hatnote i{font-style:normal}.mw-parser-output .hatnote+link+.hatnote{margin-top:-0.5em}@media print{body.ns-0 .mw-parser-output .hatnote{display:none!important}}</style><div role="note" class="hatnote navigation-not-searchable">For other uses, see <a href="/wiki/Bias_(disambiguation)" class="mw-disambig" title="Bias (disambiguation)">Bias (disambiguation)</a>.</div> <p><b>Statistical bias</b>, in the <a href="/wiki/Statistics" title="Statistics">mathematical field of statistics</a>, is a systematic tendency in which the methods used to gather <a href="/wiki/Data" title="Data">data</a> and generate statistics present an inaccurate, skewed or <a href="/wiki/Bias" title="Bias">biased</a> depiction of reality. Statistical bias exists in numerous stages of the data collection and analysis process, including: the source of the data, the methods used to collect the data, the <a href="/wiki/Estimator" title="Estimator">estimator</a> chosen, and the methods used to analyze the data. <a href="/wiki/Data_analysis" title="Data analysis">Data analysts</a> can take various measures at each stage of the process to reduce the impact of statistical bias in their work. Understanding the source of statistical bias can help to assess whether the observed results are close to actuality. Issues of statistical bias has been argued to be closely linked to issues of <a href="/wiki/Validity_(statistics)" title="Validity (statistics)">statistical validity</a>.<sup id="cite_ref-1" class="reference"><a href="#cite_note-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> </p><p>Statistical bias can have significant real world implications as data is used to inform decision making across a wide variety of processes in society. Data is used to inform lawmaking, industry regulation, corporate marketing and distribution tactics, and institutional policies in organizations and workplaces. Therefore, there can be significant implications if statistical bias is not accounted for and controlled. For example, if a pharmaceutical company wishes to explore the effect of a medication on the common cold but the data <a href="/wiki/Sample_(statistics)" class="mw-redirect" title="Sample (statistics)">sample</a> only includes men, any conclusions made from that data will be biased towards how the medication affects men rather than people in general. That means the information would be incomplete and not useful for deciding if the medication is ready for release in the general public. In this scenario, the bias can be addressed by broadening the sample. This <a href="/wiki/Sampling_error" title="Sampling error">sampling error</a> is only one of the ways in which data can be biased. </p><p>Bias can be differentiated from other statistical mistakes such as <a href="/wiki/Accuracy_and_precision" title="Accuracy and precision">accuracy</a> (instrument failure/inadequacy), lack of data, or mistakes in transcription (typos). Bias implies that the data selection may have been skewed by the collection criteria. Other forms of human-based bias emerge in data collection as well such as <a href="/wiki/Response_bias" title="Response bias">response bias</a>, in which participants give inaccurate responses to a question. Bias does not preclude the existence of any other mistakes. One may have a poorly designed sample, an inaccurate measurement device, and typos in recording data simultaneously. Ideally, all factors are controlled and accounted for. </p><p>Also it is useful to recognize that the term “error” specifically refers to the outcome rather than the process (<a href="/wiki/Type_I_and_type_II_errors" title="Type I and type II errors">errors of rejection or acceptance of the hypothesis being tested</a>), or from the phenomenon of <a href="/wiki/Random_errors" class="mw-redirect" title="Random errors">random errors</a>.<sup id="cite_ref-:0_2-0" class="reference"><a href="#cite_note-:0-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> The terms <i>flaw</i> or <i>mistake</i> are recommended to differentiate procedural errors from these specifically defined outcome-based terms. </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="Bias_of_an_estimator">Bias of an estimator</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=1" title="Edit section: Bias of an estimator"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1236090951"><div role="note" class="hatnote navigation-not-searchable">Main article: <a href="/wiki/Bias_of_an_estimator" title="Bias of an estimator">Bias of an estimator</a></div> <p>Statistical bias is a feature of a <a href="/wiki/Statistics" title="Statistics">statistical</a> technique or of its results whereby the <a href="/wiki/Expected_value" title="Expected value">expected value</a> of the results differs from the true underlying quantitative <a href="/wiki/Parameter#Statistics_and_econometrics" title="Parameter">parameter</a> being <a href="/wiki/Estimation_theory" title="Estimation theory">estimated</a>. The bias of an estimator of a parameter should not be confused with its degree of precision, as the degree of precision is a measure of the sampling error. The bias is defined as follows: let <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle T}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>T</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle T}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/ec7200acd984a1d3a3d7dc455e262fbe54f7f6e0" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.636ex; height:2.176ex;" alt="{\displaystyle T}"></span> be a statistic used to estimate a parameter <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \theta }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>θ</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \theta }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/6e5ab2664b422d53eb0c7df3b87e1360d75ad9af" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.09ex; height:2.176ex;" alt="{\displaystyle \theta }"></span>, and let <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \operatorname {E} (T)}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi mathvariant="normal">E</mi> <mo>⁡</mo> <mo stretchy="false">(</mo> <mi>T</mi> <mo stretchy="false">)</mo> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \operatorname {E} (T)}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/ec33bea001f0f5ff37854617cec5a5c899d95431" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.838ex; width:5.028ex; height:2.843ex;" alt="{\displaystyle \operatorname {E} (T)}"></span> denote the expected value of <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle T}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>T</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle T}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/ec7200acd984a1d3a3d7dc455e262fbe54f7f6e0" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.636ex; height:2.176ex;" alt="{\displaystyle T}"></span>. Then, </p> <dl><dd><span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \operatorname {bias} (T,\theta )=\operatorname {bias} (T)=\operatorname {E} (T)-\theta }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>bias</mi> <mo>⁡</mo> <mo stretchy="false">(</mo> <mi>T</mi> <mo>,</mo> <mi>θ</mi> <mo stretchy="false">)</mo> <mo>=</mo> <mi>bias</mi> <mo>⁡</mo> <mo stretchy="false">(</mo> <mi>T</mi> <mo stretchy="false">)</mo> <mo>=</mo> <mi mathvariant="normal">E</mi> <mo>⁡</mo> <mo stretchy="false">(</mo> <mi>T</mi> <mo stretchy="false">)</mo> <mo>−</mo> <mi>θ</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \operatorname {bias} (T,\theta )=\operatorname {bias} (T)=\operatorname {E} (T)-\theta }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/3510be1507f0e83ca01e1f96aff41302bc27f9d8" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.838ex; width:32.208ex; height:2.843ex;" alt="{\displaystyle \operatorname {bias} (T,\theta )=\operatorname {bias} (T)=\operatorname {E} (T)-\theta }"></span></dd></dl> <p>is called the bias of the statistic <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle T}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>T</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle T}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/ec7200acd984a1d3a3d7dc455e262fbe54f7f6e0" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.636ex; height:2.176ex;" alt="{\displaystyle T}"></span> (with respect to <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \theta }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>θ</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \theta }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/6e5ab2664b422d53eb0c7df3b87e1360d75ad9af" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.09ex; height:2.176ex;" alt="{\displaystyle \theta }"></span>). If <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \operatorname {bias} (T,\theta )=0}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>bias</mi> <mo>⁡</mo> <mo stretchy="false">(</mo> <mi>T</mi> <mo>,</mo> <mi>θ</mi> <mo stretchy="false">)</mo> <mo>=</mo> <mn>0</mn> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \operatorname {bias} (T,\theta )=0}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/4f53490e892ea27bcbc44610eab997ba4b7cc9ca" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.838ex; width:13.849ex; height:2.843ex;" alt="{\displaystyle \operatorname {bias} (T,\theta )=0}"></span>, then <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle T}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>T</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle T}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/ec7200acd984a1d3a3d7dc455e262fbe54f7f6e0" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.636ex; height:2.176ex;" alt="{\displaystyle T}"></span> is said to be an <i>unbiased estimator</i> of <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \theta }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>θ</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \theta }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/6e5ab2664b422d53eb0c7df3b87e1360d75ad9af" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.09ex; height:2.176ex;" alt="{\displaystyle \theta }"></span>; otherwise, it is said to be a <i>biased estimator</i> of <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \theta }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>θ</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \theta }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/6e5ab2664b422d53eb0c7df3b87e1360d75ad9af" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.09ex; height:2.176ex;" alt="{\displaystyle \theta }"></span>. </p><p>The bias of a statistic <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle T}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>T</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle T}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/ec7200acd984a1d3a3d7dc455e262fbe54f7f6e0" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.636ex; height:2.176ex;" alt="{\displaystyle T}"></span> is always relative to the parameter <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \theta }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>θ</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \theta }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/6e5ab2664b422d53eb0c7df3b87e1360d75ad9af" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.09ex; height:2.176ex;" alt="{\displaystyle \theta }"></span> it is used to estimate, but the parameter <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \theta }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>θ</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \theta }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/6e5ab2664b422d53eb0c7df3b87e1360d75ad9af" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.09ex; height:2.176ex;" alt="{\displaystyle \theta }"></span> is often omitted when it is clear from the context what is being estimated. </p> <div class="mw-heading mw-heading2"><h2 id="Types">Types</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=2" title="Edit section: Types"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Statistical bias comes from all stages of data analysis. The following sources of bias will be listed in each stage separately. </p> <div class="mw-heading mw-heading3"><h3 id="Data_selection">Data selection</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=3" title="Edit section: Data selection"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p><a href="/wiki/Selection_bias" title="Selection bias">Selection bias</a> involves individuals being more likely to be selected for study than others, <a href="/wiki/Sampling_bias" title="Sampling bias">biasing the sample</a>. This can also be termed selection effect, <a href="/wiki/Sampling_bias" title="Sampling bias">sampling bias</a> and <i><a href="/wiki/Berkson%27s_paradox" title="Berkson's paradox">Berksonian bias</a></i>.<sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> </p> <ul><li><a href="/wiki/Spectrum_bias" title="Spectrum bias">Spectrum bias</a> arises from evaluating diagnostic tests on biased patient samples, leading to an overestimate of the <a href="/wiki/Sensitivity_and_specificity" title="Sensitivity and specificity">sensitivity and specificity</a> of the test. For example, a high prevalence of disease in a study population increases positive predictive values, which will cause a bias between the prediction values and the real ones.<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Selection_bias" title="Selection bias">Observer selection bias</a> occurs when the evidence presented has been pre-filtered by observers, which is so-called <a href="/wiki/Anthropic_Bias_(book)" class="mw-redirect" title="Anthropic Bias (book)">anthropic principle</a>. The data collected is not only filtered by the design of experiment, but also by the necessary precondition that there must be someone doing a study.<sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> An example is the impact of the Earth in the past. The impact event may cause the extinction of intelligent animals, or there were no intelligent animals at that time. Therefore, some impact events have not been observed, but they may have occurred in the past.<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup></li> <li>Volunteer bias occurs when volunteers have intrinsically different characteristics from the target population of the study.<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> Research has shown that volunteers tend to come from families with higher socioeconomic status.<sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> Furthermore, another study shows that women are more probable to volunteer for studies than men.<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Funding_bias" title="Funding bias">Funding bias</a> may lead to the selection of outcomes, test samples, or test procedures that favor a study's financial sponsor.<sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Attrition_bias" class="mw-redirect" title="Attrition bias">Attrition bias</a> arises due to a loss of participants, e.g., loss of follow up during a study.<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Recall_bias" title="Recall bias">Recall bias</a> arises due to differences in the accuracy or completeness of participant recollections of past events; for example, patients cannot recall how many cigarettes they smoked last week exactly, leading to over-estimation or under-estimation.</li></ul> <div class="mw-heading mw-heading3"><h3 id="Hypothesis_testing">Hypothesis testing</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=4" title="Edit section: Hypothesis testing"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p><a href="/wiki/Type_I_and_type_II_errors" title="Type I and type II errors">Type I and type II errors</a> in <a href="/wiki/Statistical_hypothesis_testing" class="mw-redirect" title="Statistical hypothesis testing">statistical hypothesis testing</a> leads to wrong results.<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup> Type I error happens when the null hypothesis is correct but is rejected. For instance, suppose that the null hypothesis is that if the average driving speed limit ranges from 75 to 85 km/h, it is not considered as speeding. On the other hand, if the average speed is not in that range, it is considered speeding. If someone receives a ticket with an average driving speed of 7 km/h, the decision maker has committed a Type I error. In other words, the average driving speed meets the null hypothesis but is rejected. On the contrary, Type II error happens when the null hypothesis is not correct but is accepted. </p><p>Bias in hypothesis testing occurs when the power (the complement of the type II error rate) at some alternative is lower than the supremum of the Type I error rate (which is usually the significance level, <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \alpha }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>α</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \alpha }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/b79333175c8b3f0840bfb4ec41b8072c83ea88d3" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.488ex; height:1.676ex;" alt="{\displaystyle \alpha }"></span>). Equivalently, if no rejection rate at any alternative is lower than the rejection rate at any point in the null hypothesis set, the test is said to be unbiased.<sup id="cite_ref-13" class="reference"><a href="#cite_note-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Estimator_selection">Estimator selection</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=5" title="Edit section: Estimator selection"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The <a href="/wiki/Bias_of_an_estimator" title="Bias of an estimator">bias of an estimator</a> is the difference between an estimator's expected value and the true value of the parameter being estimated. Although an unbiased estimator is theoretically preferable to a biased estimator, in practice, biased estimators with small biases are frequently used. A biased estimator may be more useful for several reasons. First, an unbiased estimator may not exist without further assumptions. Second, sometimes an unbiased estimator is hard to compute. Third, a biased estimator may have a lower value of mean squared error. </p> <ul><li>A biased estimator is better than any unbiased estimator arising from the <a href="/wiki/Poisson_distribution" title="Poisson distribution">Poisson distribution</a>.<sup id="cite_ref-14" class="reference"><a href="#cite_note-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-15" class="reference"><a href="#cite_note-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup> The value of a biased estimator is always positive and the mean squared error of it is smaller than the unbiased one, which makes the biased estimator be more accurate.</li></ul> <ul><li><a href="/wiki/Omitted-variable_bias" title="Omitted-variable bias">Omitted-variable bias</a> is the bias that appears in estimates of parameters in regression analysis when the assumed specification omits an independent variable that should be in the model.</li></ul> <div class="mw-heading mw-heading3"><h3 id="Analysis_methods">Analysis methods</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=6" title="Edit section: Analysis methods"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li>Detection bias occurs when a phenomenon is more likely to be observed for a particular set of study subjects. For instance, the <a href="/wiki/Syndemic" title="Syndemic">syndemic</a> involving <a href="/wiki/Obesity" title="Obesity">obesity</a> and <a href="/wiki/Diabetes_mellitus" class="mw-redirect" title="Diabetes mellitus">diabetes</a> may mean doctors are more likely to look for diabetes in obese patients than in thinner patients, leading to an inflation in diabetes among obese patients because of skewed detection efforts.</li> <li>In <a href="/wiki/Educational_measurement" title="Educational measurement">educational measurement</a>, bias is defined as "Systematic errors in test content, test administration, and/or scoring procedures that can cause some test takers to get either lower or higher scores than their true ability would merit."<sup id="cite_ref-16" class="reference"><a href="#cite_note-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> The source of the bias is irrelevant to the trait the test is intended to measure.</li> <li><a href="/wiki/Observer_bias" title="Observer bias">Observer bias</a> arises when the researcher subconsciously influences the experiment due to <a href="/wiki/Cognitive_bias" title="Cognitive bias">cognitive bias</a> where judgment may alter how an experiment is carried out / how results are recorded.</li></ul> <div class="mw-heading mw-heading3"><h3 id="Interpretation">Interpretation</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=7" title="Edit section: Interpretation"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p><a href="/wiki/Reporting_bias" title="Reporting bias">Reporting bias</a> involves a skew in the availability of data, such that observations of a certain kind are more likely to be reported. </p> <div class="mw-heading mw-heading2"><h2 id="Addressing_statistical_bias">Addressing statistical bias</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=8" title="Edit section: Addressing statistical bias"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Depending on the type of bias present, researchers and analysts can take different steps to reduce bias on a data set. All types of bias mentioned above have corresponding measures which can be taken to reduce or eliminate their impacts. </p><p>Bias should be accounted for at every step of the data collection process, beginning with clearly defined research parameters and consideration of the team who will be conducting the research.<sup id="cite_ref-:0_2-1" class="reference"><a href="#cite_note-:0-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> <a href="/wiki/Observer_bias" title="Observer bias">Observer bias</a> may be reduced by implementing a <a href="/wiki/Blind_study" class="mw-redirect" title="Blind study">blind</a> or <a href="/wiki/Double-blind" class="mw-redirect" title="Double-blind">double-blind</a> technique. Avoidance of <a href="/wiki/P-Hacking" class="mw-redirect" title="P-Hacking">p-hacking</a> is essential to the process of accurate data collection. One way to check for bias in results after is rerunning analyses with different independent variables to observe whether a given phenomenon still occurs in dependent variables.<sup id="cite_ref-17" class="reference"><a href="#cite_note-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> Careful use of language in reporting can reduce misleading phrases, such as discussion of a result "approaching" statistical significant as compared to actually achieving it.<sup id="cite_ref-:0_2-2" class="reference"><a href="#cite_note-:0-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=9" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Trueness" class="mw-redirect" title="Trueness">Trueness</a></li> <li><a href="/wiki/Systematic_error" class="mw-redirect" title="Systematic error">Systematic error</a></li></ul> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Bias_(statistics)&action=edit&section=10" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1239543626">.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist .references{font-size:100%;margin-bottom:0;list-style-type:inherit}.mw-parser-output .reflist-columns-2{column-width:30em}.mw-parser-output .reflist-columns-3{column-width:25em}.mw-parser-output .reflist-columns{margin-top:0.3em}.mw-parser-output .reflist-columns ol{margin-top:0}.mw-parser-output .reflist-columns li{page-break-inside:avoid;break-inside:avoid-column}.mw-parser-output .reflist-upper-alpha{list-style-type:upper-alpha}.mw-parser-output .reflist-upper-roman{list-style-type:upper-roman}.mw-parser-output .reflist-lower-alpha{list-style-type:lower-alpha}.mw-parser-output .reflist-lower-greek{list-style-type:lower-greek}.mw-parser-output .reflist-lower-roman{list-style-type:lower-roman}</style><div class="reflist"> <div class="mw-references-wrap mw-references-columns"><ol class="references"> <li id="cite_note-1"><span class="mw-cite-backlink"><b><a href="#cite_ref-1">^</a></b></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}</style><cite id="CITEREFCole1981" class="citation journal cs1">Cole, Nancy S. 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(2002-10-01). <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/12353947/">"Spectrum bias or spectrum effect? Subgroup variation in diagnostic test evaluation"</a>. <i>Annals of Internal Medicine</i>. <b>137</b> (7): <span class="nowrap">598–</span>602. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.7326%2F0003-4819-137-7-200210010-00011">10.7326/0003-4819-137-7-200210010-00011</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1539-3704">1539-3704</a>. <a href="/wiki/PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/12353947">12353947</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:35752032">35752032</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Annals+of+Internal+Medicine&rft.atitle=Spectrum+bias+or+spectrum+effect%3F+Subgroup+variation+in+diagnostic+test+evaluation&rft.volume=137&rft.issue=7&rft.pages=%3Cspan+class%3D%22nowrap%22%3E598-%3C%2Fspan%3E602&rft.date=2002-10-01&rft.issn=1539-3704&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A35752032%23id-name%3DS2CID&rft_id=info%3Apmid%2F12353947&rft_id=info%3Adoi%2F10.7326%2F0003-4819-137-7-200210010-00011&rft.aulast=Mulherin&rft.aufirst=Stephanie+A.&rft.au=Miller%2C+William+C.&rft_id=https%3A%2F%2Fpubmed.ncbi.nlm.nih.gov%2F12353947%2F&rfr_id=info%3Asid%2Fen.wikipedia.org%3ABias+%28statistics%29" class="Z3988"></span></span> </li> <li id="cite_note-5"><span class="mw-cite-backlink"><b><a href="#cite_ref-5">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFBostrom2013" class="citation book cs1">Bostrom, Nick (2013-05-31). <a rel="nofollow" class="external text" href="https://www.taylorfrancis.com/books/mono/10.4324/9780203953464/anthropic-bias-nick-bostrom"><i>Anthropic Bias: Observation Selection Effects in Science and Philosophy</i></a>. 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title="Centre for Evidence-Based Medicine">Centre for Evidence-Based Medicine</a> cataloguing biases that affect health evidence.</li></ul> <div class="navbox-styles"><style data-mw-deduplicate="TemplateStyles:r1129693374">.mw-parser-output .hlist dl,.mw-parser-output .hlist ol,.mw-parser-output .hlist ul{margin:0;padding:0}.mw-parser-output .hlist dd,.mw-parser-output .hlist dt,.mw-parser-output .hlist li{margin:0;display:inline}.mw-parser-output .hlist.inline,.mw-parser-output .hlist.inline dl,.mw-parser-output .hlist.inline ol,.mw-parser-output .hlist.inline ul,.mw-parser-output .hlist dl dl,.mw-parser-output .hlist dl ol,.mw-parser-output .hlist dl ul,.mw-parser-output .hlist ol dl,.mw-parser-output .hlist ol ol,.mw-parser-output .hlist ol ul,.mw-parser-output .hlist ul dl,.mw-parser-output .hlist ul ol,.mw-parser-output .hlist ul ul{display:inline}.mw-parser-output .hlist .mw-empty-li{display:none}.mw-parser-output .hlist dt::after{content:": "}.mw-parser-output .hlist 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padding: .1em 0;"><a href="/wiki/Cognitive_bias" title="Cognitive bias">Cognitive biases</a></div></th><td class="navbox-list-with-group navbox-list navbox-odd hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Acquiescence_bias" title="Acquiescence bias">Acquiescence</a></li> <li><a href="/wiki/Ambiguity_effect" title="Ambiguity effect">Ambiguity</a></li> <li><a href="/wiki/Affinity_bias" title="Affinity bias">Affinity</a></li> <li><a href="/wiki/Anchoring_(cognitive_bias)" class="mw-redirect" title="Anchoring (cognitive bias)">Anchoring</a></li> <li><a href="/wiki/Attentional_bias" title="Attentional bias">Attentional</a></li> <li><a href="/wiki/Attribution_bias" title="Attribution bias">Attribution</a> <ul><li><a href="/wiki/Actor%E2%80%93observer_asymmetry" title="Actor–observer asymmetry">Actor–observer</a></li> <li><a href="/wiki/Fundamental_attribution_error" title="Fundamental attribution error">Correspondence</a></li></ul></li> <li><a href="/wiki/Authority_bias" title="Authority bias">Authority</a></li> <li><a href="/wiki/Automation_bias" title="Automation bias">Automation</a></li> <li><a href="/wiki/Availability_heuristic" title="Availability heuristic">Availability</a> <ul><li><a href="/wiki/Mean_world_syndrome" title="Mean world syndrome">Mean world</a></li></ul></li> <li><a href="/wiki/Belief_bias" title="Belief bias">Belief</a></li> <li><a href="/wiki/Bias_blind_spot" title="Bias blind spot">Blind spot</a></li> <li><a href="/wiki/Choice-supportive_bias" title="Choice-supportive bias">Choice-supportive</a></li> <li><a href="/wiki/Escalation_of_commitment" title="Escalation of commitment">Commitment</a></li> <li><a href="/wiki/Confirmation_bias" title="Confirmation bias">Confirmation</a> <ul><li><a href="/wiki/Selective_perception" title="Selective perception">Selective perception</a></li></ul></li> <li><a href="/wiki/Compassion_fade" title="Compassion fade">Compassion fade</a></li> <li><a href="/wiki/Congruence_bias" title="Congruence bias">Congruence</a></li> <li><a href="/wiki/Cultural_bias" title="Cultural bias">Cultural</a></li> <li><a href="/wiki/Declinism" title="Declinism">Declinism</a></li> <li><a href="/wiki/Distinction_bias" title="Distinction bias">Distinction</a></li> <li><a href="/wiki/Dunning%E2%80%93Kruger_effect" title="Dunning–Kruger effect">Dunning–Kruger</a></li> <li><a href="/wiki/Egocentric_bias" title="Egocentric bias">Egocentric</a> <ul><li><a href="/wiki/Curse_of_knowledge" title="Curse of knowledge">Curse of knowledge</a></li></ul></li> <li><a href="/wiki/Emotional_bias" title="Emotional bias">Emotional</a></li> <li><a href="/wiki/Extrinsic_incentives_bias" title="Extrinsic incentives bias">Extrinsic incentives</a></li> <li><a href="/wiki/Fading_affect_bias" title="Fading affect bias">Fading affect</a></li> <li><a href="/wiki/Framing_effect_(psychology)" title="Framing effect (psychology)">Framing</a></li> <li><a href="/wiki/Frequency_illusion" title="Frequency illusion">Frequency</a></li> <li><a href="/wiki/Frog_pond_effect" title="Frog pond effect">Frog pond effect</a></li> <li><a href="/wiki/Halo_effect" title="Halo effect">Halo effect</a></li> <li><a href="/wiki/Hindsight_bias" title="Hindsight bias">Hindsight</a></li> <li><a href="/wiki/Horn_effect" title="Horn effect">Horn effect</a></li> <li><a href="/wiki/Hostile_attribution_bias" title="Hostile attribution bias">Hostile attribution</a></li> <li><a href="/wiki/Impact_bias" title="Impact bias">Impact</a></li> <li><a href="/wiki/Implicit_stereotype" title="Implicit stereotype">Implicit</a></li> <li><a href="/wiki/In-group_favoritism" title="In-group favoritism">In-group</a></li> <li><a href="/wiki/Intentionality_bias" title="Intentionality bias">Intentionality</a></li> <li><a href="/wiki/Illusion_of_transparency" title="Illusion of transparency">Illusion of transparency</a></li> <li><a href="/wiki/Mean_world_syndrome" title="Mean world syndrome">Mean world syndrome</a></li> <li><a href="/wiki/Mere-exposure_effect" title="Mere-exposure effect">Mere-exposure effect</a></li> <li><a href="/wiki/Narrative_bias" title="Narrative bias">Narrative</a></li> <li><a href="/wiki/Negativity_bias" title="Negativity bias">Negativity</a></li> <li><a href="/wiki/Normalcy_bias" title="Normalcy bias">Normalcy</a></li> <li><a href="/wiki/Omission_bias" title="Omission bias">Omission</a></li> <li><a href="/wiki/Optimism_bias" title="Optimism bias">Optimism</a></li> <li><a href="/wiki/Out-group_homogeneity" title="Out-group homogeneity">Out-group homogeneity</a></li> <li><a href="/wiki/Outcome_bias" title="Outcome bias">Outcome</a></li> <li><a href="/wiki/Overton_window" title="Overton window">Overton window</a></li> <li><a href="/wiki/Precision_bias" title="Precision bias">Precision</a></li> <li><a href="/wiki/Present_bias" title="Present bias">Present</a></li> <li><a href="/wiki/Pro-innovation_bias" title="Pro-innovation bias">Pro-innovation</a></li> <li><a href="/wiki/Proximity_bias" title="Proximity bias">Proximity</a></li> <li><a href="/wiki/Response_bias" title="Response bias">Response</a></li> <li><a href="/wiki/Restraint_bias" title="Restraint bias">Restraint</a></li> <li><a href="/wiki/Self-serving_bias" title="Self-serving bias">Self-serving</a></li> <li><a href="/wiki/Social_comparison_bias" title="Social comparison bias">Social comparison</a></li> <li><a href="/wiki/Social_influence_bias" title="Social influence bias">Social influence bias</a></li> <li><a href="/wiki/Spotlight_effect" title="Spotlight effect">Spotlight</a></li> <li><a href="/wiki/Status_quo_bias" title="Status quo bias">Status quo</a></li> <li><a href="/wiki/Attribute_substitution" title="Attribute substitution">Substitution</a></li> <li><a href="/wiki/Time-saving_bias" title="Time-saving bias">Time-saving</a></li> <li><a href="/wiki/Trait_ascription_bias" title="Trait ascription bias">Trait ascription</a></li> <li><a href="/wiki/Turkey_illusion" title="Turkey illusion">Turkey illusion</a></li> <li><a href="/wiki/Von_Restorff_effect" title="Von Restorff effect">von Restorff effect</a></li> <li><a href="/wiki/Zero-risk_bias" title="Zero-risk bias">Zero-risk</a></li> <li><a href="/wiki/Cognitive_bias_in_animals" title="Cognitive bias in animals">In animals</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a class="mw-selflink selflink">Statistical biases</a></th><td class="navbox-list-with-group navbox-list navbox-even hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Bias_of_an_estimator" title="Bias of an estimator">Estimator</a></li> <li><a href="/wiki/Forecast_bias" title="Forecast bias">Forecast</a></li> <li><a href="/wiki/Healthy_user_bias" title="Healthy user bias">Healthy user</a></li> <li><a href="/wiki/Information_bias_(epidemiology)" title="Information bias (epidemiology)">Information</a> <ul><li><a href="/wiki/Information_bias_(psychology)" title="Information bias (psychology)">Psychological</a></li></ul></li> <li><a href="/wiki/Lead_time_bias" title="Lead time bias">Lead time</a></li> <li><a href="/wiki/Length_time_bias" title="Length time bias">Length time</a></li> <li><a href="/wiki/Participation_bias" title="Participation bias">Non-response</a></li> <li><a href="/wiki/Observer_bias" title="Observer bias">Observer</a></li> <li><a href="/wiki/Omitted-variable_bias" title="Omitted-variable bias">Omitted-variable</a></li> <li><a href="/wiki/Participation_bias" title="Participation bias">Participation</a></li> <li><a href="/wiki/Recall_bias" title="Recall bias">Recall</a></li> <li><a href="/wiki/Sampling_bias" title="Sampling bias">Sampling</a></li> <li><a href="/wiki/Selection_bias" title="Selection bias">Selection</a></li> <li><a href="/wiki/Self-selection_bias" title="Self-selection bias">Self-selection</a></li> <li><a href="/wiki/Social-desirability_bias" title="Social-desirability bias">Social desirability</a></li> <li><a href="/wiki/Spectrum_bias" title="Spectrum bias">Spectrum</a></li> <li><a href="/wiki/Survivorship_bias" title="Survivorship bias">Survivorship</a></li> <li><a href="/wiki/Systematic_error" class="mw-redirect" title="Systematic error">Systematic error</a></li> <li><a href="/wiki/Systemic_bias" title="Systemic bias">Systemic</a></li> <li><a href="/wiki/Verification_bias" title="Verification bias">Verification</a></li> <li><a href="/wiki/Wet_bias" title="Wet bias">Wet</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Other biases</th><td class="navbox-list-with-group navbox-list navbox-odd hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Academic_bias" title="Academic bias">Academic</a></li> <li><a href="/wiki/Basking_in_reflected_glory" title="Basking in reflected glory">Basking in reflected glory</a></li> <li><i><a href="/wiki/D%C3%A9formation_professionnelle" title="Déformation professionnelle">Déformation professionnelle</a></i></li> <li><a href="/wiki/Funding_bias" title="Funding bias">Funding</a></li> <li><a href="/wiki/FUTON_bias" class="mw-redirect" title="FUTON bias">FUTON</a></li> <li><a href="/wiki/Inductive_bias" title="Inductive bias">Inductive</a></li> <li><a href="/wiki/Infrastructure_bias" title="Infrastructure bias">Infrastructure</a></li> <li><a href="/wiki/Inherent_bias" title="Inherent bias">Inherent</a></li> <li><a href="/wiki/Bias_in_education" class="mw-redirect" title="Bias in education">In education</a></li> <li><a href="/wiki/Liking_gap" title="Liking gap">Liking gap</a></li> <li><a href="/wiki/Media_bias" title="Media bias">Media</a> <ul><li><a href="/wiki/False_balance" title="False balance">False balance</a></li> <li><a href="/wiki/United_States_news_media_and_the_Vietnam_War" title="United States news media and the Vietnam War">Vietnam War</a></li> <li><a href="/wiki/Media_bias_in_South_Asia" title="Media bias in South Asia">South Asia</a></li> <li><a href="/wiki/Media_bias_in_the_United_States" title="Media bias in the United States">United States</a></li> <li><a href="/wiki/Media_coverage_of_the_Arab%E2%80%93Israeli_conflict" class="mw-redirect" title="Media coverage of the Arab–Israeli conflict">Arab–Israeli conflict</a></li> <li><a href="/wiki/Media_portrayal_of_the_Ukrainian_crisis" class="mw-redirect" title="Media portrayal of the Ukrainian crisis">Ukraine</a></li></ul></li> <li><a href="/wiki/Net_bias" title="Net bias">Net</a></li> <li><a href="/wiki/Political_bias" title="Political bias">Political bias</a></li> <li><a href="/wiki/Publication_bias" title="Publication bias">Publication</a></li> <li><a href="/wiki/System_justification" title="System justification">System justification</a></li> <li><a href="/wiki/Reporting_bias" title="Reporting bias">Reporting</a></li> <li><a href="/wiki/White_hat_bias" title="White hat bias">White hat</a></li> <li><a href="/wiki/Ideological_bias_on_Wikipedia" title="Ideological bias on Wikipedia">Ideological bias on Wikipedia</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Bias reduction</th><td class="navbox-list-with-group navbox-list navbox-even hlist" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Cognitive_bias_mitigation" title="Cognitive bias mitigation">Cognitive bias mitigation</a></li> <li><a href="/wiki/Debiasing" title="Debiasing">Debiasing</a></li> <li><a href="/wiki/Heuristic_(psychology)" title="Heuristic (psychology)">Heuristics in judgment and decision-making</a></li></ul> </div></td></tr><tr><td class="navbox-abovebelow hlist" colspan="2"><div> <ul><li>Lists: <a href="/wiki/List_of_cognitive_biases" title="List of cognitive biases">General</a></li> <li><a href="/wiki/List_of_cognitive_biases#Memory_biases" title="List of cognitive biases">Memory</a></li></ul> </div></td></tr></tbody></table></div>    </div><noscript><img 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