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Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual probabilities in the contingency table. It is also important to note that the expected frequency for each column must be at least 5. The expected frequencies are then used to calculate the chi-square value and P-value.

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Expected FrequencyContingency TableObserved FrequenciesIndependenceStatistical ProbabilityChi square ValueP valueIndependent VariablesEvent ProbabilitiesData Analysis

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8.13 : Determination of Expected Frequency

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8.1 : توزيعات تقدير معلمة السكان

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8.2 : درجات الحرية

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8.3 : توزيع الطالب

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8.4 : الاختيار بين توزيع z و t

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8.5 : توزيع مربع كاي

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8.6 : إيجاد قيم حرجة لمربع كاي

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8.7 : تقدير الانحراف المعياري للسكان

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8.8 : اختبار الملاءمة الجيدة

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8.9 : الترددات المتوقعة في اختبارات الملاءمة

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8.10 : جدول الطوارئ

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8.11 : مقدمة في اختبار الاستقلال

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8.12 : اختبار الفرضيات لاختبار الاستقلالية

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8.14 : اختبار التجانس

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8.15 : توزيع F

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