How to compute Unpaired t- test (independent t-test) In R? скачать в хорошем качестве

How to compute Unpaired t- test (independent t-test) In R?

n unpaired t-test (also known as an independent t-test) is a statistical procedure that compares the averages/means of two independent or unrelated groups to determine if there is a significant difference between the two. The assumptions of an unpaired t-test ● The dependent variable is normally distributed ● The observations are sampled independently ● The dependent variable is measured on an incremental level, such as ratios or intervals. ● The variance of data is the same between groups, meaning that they have the same standard deviation ●The independent variables must consist of two independent groups. When to use an unpaired t-test? An unpaired t-test is used to compare the mean between two independent groups. You use an unpaired t-test when you are comparing two separate groups with equal variance. ● Research, such as a pharmaceutical study or other treatment plan, where ½ of the subjects are assigned to the treatment group and ½ of the subjects are randomly assigned to the control group. ● Research during which there are two independent groups, such as women and men, that examines whether the average bone density is significantly different between the two groups. ● Comparing the average commuting distance traveled by New York City and San Francisco residents using 1,000 randomly selected participants from each city. If you want the code, please write to my email address, wakjiratesfahun@gmail.com