Hypothesis

Front

What is a Goodness-of-Fit Test?

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Checks if observed data matches what we expect.

Front

1. Null Hypothesis (H₀)

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The null hypothesis is what you assume is true before testing.

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Null hypothesis (H₀)

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The alternative hypothesis is what you suspect might be true instead of H₀.

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Purpose of Testing

Back

• Once we have H₀ and H₁, we collect data.

• The test helps us decide whether H₀ is still likely true or whether our suspicion (H₁) might be correct.

Front

To perform a goodness-of-fit test, you only need three key things:

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1. 1.Expected Value (EV)

   • What we expect to happen if H₀ is true.

Front

To perform a goodness-of-fit test, you only need three key things:

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• 2.Observed Value (OV)

  • What actually happened – the data you collected.

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Degrees of Freedom (df)

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df=n−1

Where n = number of categories

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Next Step: Chi-Square Calculation or p value calculation.

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Chi-Square-Measures how far the observed data is from what we expected.

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Next Step: Chi-Square/P-value Calculation

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The p-value is the probability of getting results as extreme as your observed data, assuming the null hypothesis (H₀) is true.

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GDC Goodness-of-Fit Test Steps

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Menu → Statistics 2 → Enter Data (List 1: Observed, List 2: Expected) → Test (F3) → CHI F3 → GOF F1 → df → execute