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8.13 : Determination of Expected Frequency

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

来自章节 8:

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8.13 : Determination of Expected Frequency

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8.1 : 用于估计总体的分布参数

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8.2 : 自由度

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8.3 : 学生 t 分布

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8.4 : 在 z 分布和 t 分布之间进行选择

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8.5 : 卡方分布

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8.6 : 求卡方的临界值

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8.7 : 估计总体标准差

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8.8 : 拟合优度检验

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8.9 : 拟合优度检验中的预期频率

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8.10 : 列联表

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8.11 : 独立性测试简介

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8.12 : 独立性检验的假设检验

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8.14 : 均匀性检验

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8.15 : F 分布

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