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Independence Tests - Excel definitions

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  • Chi-square Test

    A statistical method used to assess whether two categorical variables are independent by comparing observed and expected frequencies.
  • Contingency Table

    A matrix displaying the frequency distribution of variables, organizing observed counts by categories for analysis.
  • Row Total

    The sum of observed frequencies across all columns for a specific row in a contingency table.
  • Column Total

    The sum of observed frequencies down all rows for a specific column in a contingency table.
  • Grand Total

    The overall sum of all observed frequencies in a contingency table, representing the total sample size.
  • Expected Value

    A calculated frequency for a cell in a contingency table, found by multiplying row and column totals and dividing by the grand total.
  • Observed Frequency

    The actual count recorded in each cell of a contingency table, based on collected data.
  • P-value

    A probability measure indicating the strength of evidence against the null hypothesis in a statistical test.
  • Alpha Level

    A threshold probability, such as 0.05, used to determine statistical significance in hypothesis testing.
  • Null Hypothesis

    A statement proposing no association between variables, serving as the default assumption in hypothesis testing.
  • Alternative Hypothesis

    A statement suggesting a relationship or dependence between variables, considered if evidence contradicts the null hypothesis.
  • Categorical Data

    Data sorted into distinct groups or categories, often used in contingency tables for statistical analysis.
  • Statistical Inference

    The process of drawing conclusions about populations based on sample data using probability and statistical tests.
  • Homogeneity Test

    A statistical procedure similar to the independence test, used to compare distributions of a categorical variable across groups.
  • CHISQ.TEST Function

    An Excel function that calculates the p-value for a chi-square test by comparing observed and expected frequencies.