If the population standard deviation is available and the sample size is greater than 30, t-distribution can be used with the population standard deviation instead of the sample standard deviation. Summary: If the sample sizes are larger than 30, the z-distribution and the t-distributions are pretty much the same and either one can be used. The t-score is calculated using the formula: T-Score tells you how many standard deviations from the mean your result is. t-statistics (t-score), also known as Student's T-Distribution, is used when the data follows a normal distribution, population standard deviation ( sigma) is NOT known, but the sample standard deviation ( s) is known or can be calculated, and the sample size is below 30.We can also use z-scores to compute the percent of data that falls in an interval between two values. In case you are looking for a more technical definition, then we can say that the z score is a measure of how many standard deviations there are that are above or below the population mean. Using the standard normal table for a z-score of 1.48. The z-score is calculated using the formula: The z-score, which is also known as the standard score, is the number of standard deviations from the mean a data point is. ![]() ![]() Z-Score tells you how many standard deviations from the mean your result is. z-statistics (z-score) is used when the data follows a normal distribution, population standard deviation sigma is known and the sample size is above 30.If you are interested in T-test, you can do similar:
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