T-score is used for hypothesis testing when population standard deviation is unknown or sample size is small.
⚠Sample size must be at least 2. Sample standard deviation must be positive.
What is T Score?
The t-score (t-statistic) is a statistical measure used in hypothesis testing when the population standard deviation is unknown and/or the sample size is small.
T-Distribution
Similar to normal but with fatter tails for small samples
T-score (t-statistic) measures how many standard errors the sample mean is from the population mean. t = (x̄ - μ) / (s/√n). Used when population σ is unknown.
Difference between t-score and z-score?▼
Z-score uses population σ, t-score uses sample s. T-distribution has fatter tails, especially with small n. Use t when n<30 or σ unknown.
What are degrees of freedom?▼
DF = n - 1 for one-sample t-test. DF determines the shape of t-distribution. Larger DF makes t-distribution closer to normal.
When to use t-score?▼
Use t-score for small samples (n<30), when population standard deviation is unknown, or when sampling from non-normal distributions with large n.
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