A new window named “Probability Plot of HtBk” appears, which covers the results of the normality test.A new window named “Normality Test” pops up.Click Stat → Basic Statistics → Normality Test.Step 1: Test whether the data are normally distributed
Use Minitab to Run a One-Sample T-TestĬase study: We want to compare the average height of basketball players against 7 feet.ĭata File: “One Sample T-Test” tab in “Sample Data.xlsx”
If |tcalc| < tcrit, we fail to reject the null and claim there is not any statistically significant difference between the population mean μ and the specified value μ0. One sample t-test is more robust than the z-test when the sample size is small ( tcrit, we reject the null and claim there is a statistically significant difference between the population mean μ and the specified value μ0.The variance of the population of our interest is unknown.The data of the population are normally distributed.The data of the population are continuous.The sample data of the population of interest are unbiased and representative.μ0 is the specific value we want to compare against.μ is the mean of a population of our interest.One sample t test is a hypothesis test to study whether there is a statistically significant difference between a population mean and a specified value. It helps us separate fact from fiction, and special cause from noise, when we are looking to make decisions based on data. Hypothesis testing is a critical tool in the Six Sigma tool belt. Hypothesis tests help to determine whether a hypothesis about a population or multiple populations is true with certain confidence level based on sample data. A hypothesis test is a statistical method in which a specific hypothesis is formulated about a population, and the decision of whether to reject the hypothesis is made based on sample data. We apply a one sample t test when the population variance (σ) is unknown and we use the sample standard deviation (s) instead.
In statistics, a t test is a hypothesis test in which the test statistic follows a Student’s t distribution if the null hypothesis is true.
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