Student's t-test

The video tutorial explains the origin and application of the Student's t-test, a statistical method developed by William Sealy Gosset under the pseudonym 'Student'. It covers the conceptual understanding of the t-test, including the calculation of the t-value using spreadsheets, and how to perform a t-test to determine statistical significance between two sample sets. The tutorial also discusses the assumptions required for a t-test and the difference between independent and paired tests, as well as one-tailed and two-tailed tests.

Who developed the t-test and why is it known as the Student's t-test?

• Karl Pearson, because he was a student

• Ronald Fisher, because he was a student

• Francis Galton, because he published under a pseudonym

• William Sealy Gosset, because he published under a pseudonym

What is the primary purpose of using a t-test?

• To compare the means of two samples

• To find the mode of a distribution

• To determine the range of a dataset

• To calculate the median of a dataset

In the context of a t-test, what does the 'signal' refer to?

• The noise in the data

• The difference between the means of two samples

• The variance within a sample

• The standard deviation of a dataset

Which tool is recommended for calculating the t-value efficiently?

• A statistical textbook

• A graphing calculator

• A spreadsheet software like Excel or Google Sheets

• A scientific calculator

What is the null hypothesis in a t-test?

• There is a statistically significant difference between samples

• There is no statistically significant difference between samples

• The samples have identical variances

• The samples have different standard deviations

How do you determine the critical value in a t-test?

• By using a t-table and considering the degrees of freedom

• By calculating the mean of the samples

• By using a z-table

• By finding the standard deviation of the samples

What is the significance of a p-value in a t-test?

• It indicates the probability of the null hypothesis being true

• It shows the average of the sample data

• It measures the variance of the dataset

• It calculates the standard deviation of the samples

What is the difference between an independent t-test and a paired t-test?

• Both tests compare two different populations

• Both tests compare the same population at different times

• Independent t-test compares the same population at different times, paired t-test compares two different populations

• Independent t-test compares two different populations, paired t-test compares the same population at different times

Which assumption is NOT required for running a t-test?

• Normal distribution in the population

• Similar variance in samples

• Large sample size over 100

• Roughly the same number of data points in each sample

When should a z-test be used instead of a t-test?

• When the sample size is small

• When the data is not normally distributed

• When the sample size is large

• When comparing more than two samples