One-sample t test

The one-sample t-test is a statistical method used to determine if the mean of a single sample differs significantly from a known or hypothesized population mean. Employed in various fields, including psychology, medicine, and economics, this test assesses whether the observed sample mean is statistically different from the expected population mean. By comparing the sample mean to the population mean and considering the sample size and variability, the one-sample t-test provides a reliable means to draw inferences about the population, aiding researchers in making informed decisions based on their collected data.

Questions
  • What is the CRITICAL VALUE for a one-tailed t-test with df=54 and α=.05 ?
  • What are the conditions for conducting a one-sample t test for the mean?
  • If the sample mean = 16, population mean = 8, sample standard deviation = 4, and sample size = 150, what is the one sided t-score of the sample?
  • How does a t distribution differ from a normal curve?
  • When would you reject the null hypothesis in a t-test?
  • How do I find the P-value for a right tailed test with n = 19 and t = 2.599?