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t-Statistic - Coggle Diagram
t-Statistic
Cohen’s d measures effect size in standard deviation units.
The original formula uses population mean difference and population standard deviation
The sample mean after treatment is used as the “treatment” mean.
A larger Cohen’s d indicates a stronger treatment effect.
The sample standard deviation replaces the population standard deviation
Estimated error
Difference between a sample estimate and the true population value.
Denominator is the estimated standard error
Confidence interval
used to estimate an unknown population mean
provides a range of plausible values for the population mean
z-score
Test statistic used when the population standard deviation is known
Standard error
Measures the expected difference between a sample mean and a population mean
Estimated standard error
Estimate of standard error calculated from sample data
Sample Mean
Average score of a sample
Population Mean
Average score of population
Population Standard Deviation
Measures variability in the population
Sample Variance
Measures variability in a sample
t-distribution
distribution used with t-tests; similar to the normal distribution but with heavier tails.
Degree of Freedom
Number of independent values in a sample that can vary
Population Variance
True variance of entire population
Independent Scores
Values in a sample that can vary freely without restriction.
Test statistic used when the population standard deviation is unknown
Is a ratio
Null hypothesis provides the value of μ.