To find a test statistic, you first need to understand the type of hypothesis test you are conducting. The appropriate test statistic depends on the nature of your data, the hypothesis you are testing, and the assumptions you can make about the population. Here's a breakdown of common scenarios and how to calculate the relevant test statistic:
Z-test: This is used when you have a large sample size (typically n > 30) and know the population standard deviation, or when the sample is large enough to rely on the central limit theorem. The <a href="https://www.wikiwhat.page/kavramlar/Z-test%20statistic">Z-test statistic</a> is calculated as:
For a single sample mean: Z = (x̄ - μ) / (σ / √n)
For comparing two sample means (independent samples): Z = (x̄₁ - x̄₂) / √(σ₁²/n₁ + σ₂²/n₂)
T-test: This is used when the population standard deviation is unknown and the sample size is small (typically n < 30). You estimate the population standard deviation using the sample standard deviation. The <a href="https://www.wikiwhat.page/kavramlar/T-test%20statistic">T-test statistic</a> is calculated as:
For a single sample mean: t = (x̄ - μ) / (s / √n)
For comparing two sample means (independent samples, equal variances assumed):
t = (x̄₁ - x̄₂) / (sp * √(1/n₁ + 1/n₂))
For comparing two sample means (independent samples, unequal variances assumed - Welch's t-test): The formula is more complex, consult a statistical resource or software package. The degrees of freedom are also calculated differently, often using the Welch-Satterthwaite equation.
For paired samples: t = (d̄ - 0) / (sd / √n)
Chi-square test: This is used for categorical data, often to test independence or goodness-of-fit. The <a href="https://www.wikiwhat.page/kavramlar/Chi-square%20test%20statistic">Chi-square test statistic</a> is calculated as:
χ² = Σ [(O - E)² / E]
F-test: This is often used in ANOVA (Analysis of Variance) to compare the variances of two or more groups or to assess the overall significance of a regression model. The <a href="https://www.wikiwhat.page/kavramlar/F-test%20statistic">F-test statistic</a> is generally a ratio of variances (Mean Square Between Groups / Mean Square Within Groups). Consult specific ANOVA tables and formulas.
Steps to find a test statistic:
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