Understanding T Tests in Statistics

Who invented the T Test and for what company did he work?

• Ronald Fisher, Fisher Scientific

• John Tukey, Bell Labs

• William Gosset, Guinness

• Karl Pearson, Pearson Publishing

What is the primary purpose of a T Test in statistics?

• To determine the correlation between two variables

• To compare the means of two groups

• To compare the variances of two groups

• To calculate the probability of an event

In a T Test, what does a large T value indicate?

• A large difference between means

• A large variance

• A small sample size

• A small difference between means

Which type of T Test would you use for comparing the same group before and after a treatment?

• One-sample T Test

• Two-sample T Test

• Unpaired T Test

• Paired T Test

What is the main difference between a paired and an unpaired T Test?

• Paired T Test compares two different groups, unpaired compares the same group

• Paired T Test compares the same group, unpaired compares two different groups

• Paired T Test is used for large samples, unpaired for small samples

• Paired T Test is used for categorical data, unpaired for numerical data

When would you use a one-sample T Test?

• When comparing a sample mean to a known population mean

• When comparing two independent groups

• When comparing variances of two samples

• When comparing two related groups

What is a critical assumption for the validity of a T Test?

• The data must be collected from a single source

• The data should be approximately normally distributed

• The sample size must be exactly 10

• The data must be categorical

Why is it important to have a reasonable sample size in a T Test?

• To decrease the mean difference

• To obtain reliable results

• To increase the variance

• To ensure the data is normally distributed

What is the minimum recommended sample size for each group in a T Test?

• At least 50

• At least 10

• At least 20

• At least 30

What happens if the sample sizes in a T Test are not roughly the same?

• The T Test will show a larger mean difference

• The T Test will not run

• The T Test results may be unreliable

• The T Test becomes more accurate