17.3.1 One-Sample T-Test

1 Introduction
2 Handling Missing Values
3 Performing One-Sample t-test

Introduction

The one-sample Student's t-Test determines whether or not the mean of a sample taken from a normally distributed population is consistent with the hypothetical value for a given confidence level. By choosing a one- or two-tailed t-test, you can test how likely it is that the sample mean is greater than, less than, or equal to the true population mean. Note that the one-sample t-test is appropriate when the standard deviation of the entire population is unknown.

The t statistic value and p-value will be calculated to decide whether or not to reject the null hypothesis. The p-value is the probability that null hypothesis is true, and a small p-value suggests that you should reject it.

The confidence interval provides lower and upper limits for the possible value of the population mean. For a given significance level, $\alpha$ , this interval indicates we have $(1-\alpha )\times 100\%$ confidence to say the true population mean falls within the interval.

Handling Missing Values

The missing values in the data range will be excluded in the analysis

Performing One-Sample t-test

To perform a one-sample t-test:

Select Statistics: Hypothesis Testing: One-Sample t-Test. This opens the OneSampletTest dialog.
Specify your Input Data, the Test Mean, and the desired Alternative Hypothesis.
Upon clicking OK, two result sheets are generated: PlotData# and OneSampletTest#. The first sheet stores the plot data of the result graphs in second sheet. The second sheet is the report table sheet which shows the result tables of the test and the result graphs including the summary report and diagnostic report.