Parametric statistics | Statistical tests

Student's t-test

A t-test is any statistical hypothesis test in which the test statistic follows a Student's t-distribution under the null hypothesis. It is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic were known (typically, the scaling term is unknown and therefore a nuisance parameter). When the scaling term is estimated based on the data, the test statistic—under certain conditions—follows a Student's t distribution. The t-test's most common application is to test whether the means of two populations are different. (Wikipedia).

Student's t-test
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I explain the differences of finding Power of a t-Test compared to Power of a z-Test. Find free review test, useful notes and more at http://www.mathplane.com If you'd like to make a donation to support my efforts look for the "Tip the Teacher" button on my channel's homepage www.YouTube.c

From playlist AP Statistics

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From playlist t-test

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From playlist WK10 One Sample t Tests - Online Statistics for the Flipped Classroom

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From playlist WK11 Independent Sample t Tests and Paired t Tests - Online Statistics for the Flipped Classroom

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From playlist Hypothesis Tests and Critical Values

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From playlist WK10 One Sample t Tests - Online Statistics for the Flipped Classroom

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From playlist Probability Distributions

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From playlist RStats Videos

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From playlist Jamovi Tutorials

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From playlist Business Statistics Lectures (FA2020, QBA337 @ MSU)

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From playlist Jamovi 2022 Tutorials

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From playlist Business Statistics Lectures (FA2020, QBA337 @ MSU)

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From playlist WK10 One Sample t Tests - Online Statistics for the Flipped Classroom

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From playlist Jamovi 2022 Tutorials

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From playlist Introduction to SPSS Statistics 27

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From playlist RStats Videos

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SPSS | Welch–Satterthwaite equation | Šidák correction for t-test | Mann–Whitney U test | Slutsky's theorem | Wilcoxon signed-rank test | MATLAB | P-value | Skewness | Nuisance parameter | Paired difference test | Exact test | Statistics | Analysis of variance | Chi-squared distribution | Noncentral t-distribution | Sample mean | Behrens–Fisher problem | Law of large numbers | Stata | Null hypothesis | Outlier | Independence (probability theory) | Central limit theorem | Location test | Observational study | Conditional change model | Levene's test | DAP (software) | F-test | Student's t-distribution | Q–Q plot | Brown–Forsythe test | Scale parameter | Blocking (statistics) | Gretl | Variance | Julia (programming language) | Welch's t-test | Posterior probability | Simple linear regression | Pearson correlation coefficient | QtiPlot | R (programming language) | Bartlett's test | Z-test | Normal distribution | Standard deviation | Statistical hypothesis testing | Arithmetic mean | PSPP | Hotelling's t-squared statistic | Degrees of freedom (statistics) | Type I and type II errors | Expected value | Test statistic | Location testing for Gaussian scale mixture distributions | Statistical significance | SAS (software) | F-test of equality of variances | Pearson distribution