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8.2 Setting Up a Chi-Square Goodness of Fit Test

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Chi-Square Goodness of Fit: Setup

Chi-square goodness-of-fit test

Hypotheses:

  • H0{H_0}: The population follows the claimed distribution [state the claimed proportions]
  • Ha{H_a}: The population does NOT follow the claimed distribution

Conditions:

  1. Random: Data come from a random sample
  2. Independence / 10% condition: n<10%{n < 10\%} of population (if sampling without replacement)
  3. Large Counts: All expected counts ≥5{\geq 5}
    Ei=n⋅piE_i = n \cdot p_i

(Note: For chi-square, the condition is on expected counts, not observed.)

Degrees of freedom: df=k−1{df = k - 1} where k{k} = number of categories

In this unit

6 lessons

  1. 8.1Introducing Statistics: Are My Results Unexpected?Preview lesson
  2. 8.2Setting Up a Chi-Square Goodness of Fit TestThis lesson
  3. 8.3Carrying Out a Chi-Square Test for Goodness of FitPreview lesson
  4. 8.4Expected Counts in Two-Way TablesPreview lesson
  5. 8.5Setting Up a Chi-Square Test for Homogeneity or IndependencePreview lesson
  6. 8.6Carrying Out a Chi-Square Test for Homogeneity or IndependencePreview lesson

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