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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

From Chapter 8:

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8.13 : Determination of Expected Frequency

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8.1 : התפלגות להערכת פרמטר אוכלוסייה

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8.2 : דרגות חופש

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8.3 : התפלגות סטודנטים t

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8.4 : בחירה בין התפלגות z ו- t

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8.5 : התפלגות צ'י-ריבוע

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8.6 : מציאת ערכים קריטיים עבור Chi-Square

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8.7 : הערכת סטיית התקן של האוכלוסייה

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8.8 : מבחן התאמה טובה

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8.9 : תדרים צפויים במבחני התאמה טובה

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8.10 : טבלת מגירה

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8.11 : מבוא למבחן העצמאות

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8.12 : מבחן השערה למבחן העצמאות

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8.14 : מבחן הומוגניות

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8.15 : התפלגות F

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