T-Test Quiz

What is a one-sample t-test?

• A one-sample t-test is a statistical test used to determine if the mean of a single sample is significantly different from a hypothesized population mean.

• A one-sample t-test is used to compare the means of two independent samples.

• A one-sample t-test is used to determine if the variance of a single sample is significantly different from a hypothesized population variance.

• A one-sample t-test is used to determine if the median of a single sample is significantly different from a hypothesized population median.

What are the assumptions of a t-test?

• The assumptions of a t-test are: 1) The data is normally distributed. 2) The variances of the two groups being compared are equal. 3) The observations within each group are independent.

• The assumptions of a t-test are: 1) The data is normally distributed. 2) The variances of the two groups being compared are not equal. 3) The observations within each group are dependent.

• The assumptions of a t-test are: 1) The data is not normally distributed. 2) The variances of the two groups being compared are equal. 3) The observations within each group are independent.

• The assumptions of a t-test are: 1) The data is normally distributed. 2) The variances of the two groups being compared are equal. 3) The observations within each group are not independent.

How do you interpret the results of a t-test?

• Compare the calculated t-value to the critical t-value from the t-distribution table.

• Refer to the z-distribution table to interpret the results.

• Calculate the p-value and compare it to the significance level.

• Use the mean and standard deviation to determine the t-value.

What is effect size in a t-test?

• Effect size in a t-test measures the correlation between two groups being compared.

• Effect size in a t-test measures the magnitude of the difference between two groups being compared.

• Effect size in a t-test measures the variability within each group being compared.

• Effect size in a t-test measures the similarity between two groups being compared.

What is a hypothesis t-test?

• A hypothesis t-test is a statistical test used to determine if there is a significant difference between the means of two groups in a sample population.

• A hypothesis t-test is a test used to determine if there is a significant difference between the medians of two groups in a sample population.

• A hypothesis t-test is a test used to determine if there is a significant difference between the variances of two groups in a sample population.

• A hypothesis t-test is a test used to determine if there is a significant difference between the proportions of two groups in a sample population.

What is the null hypothesis in a one-sample t-test?

• The null hypothesis states that there is no significant difference between the mean of the sample and a hypothesized population mean.

• The null hypothesis states that the sample mean is greater than the population mean.

• The null hypothesis states that there is a significant difference between the mean of the sample and a hypothesized population mean.

• The null hypothesis states that the sample mean is equal to the population mean.

What is the alternative hypothesis in a one-sample t-test?

• The sample mean is less than the hypothesized population mean.

• The sample mean is equal to the hypothesized population mean.

• There is no significant difference between the sample mean and the hypothesized population mean.

• There is a significant difference between the sample mean and the hypothesized population mean.

What is the formula for calculating the t-statistic in a t-test?

• (x̄ - μ) * (s / √n)

• (x̄ - μ) / (s / √n)

• (x̄ - μ) / (s * √n)

• (x̄ + μ) / (s / √n)

What is the critical value in a t-test?

• The critical value in a t-test is the value that separates the upper tail from the lower tail in the t-distribution.

• The critical value in a t-test is the value that indicates the probability of making a Type II error.

• The critical value in a t-test is the value that represents the average of the sample data.

• The critical value in a t-test is the value that separates the critical region from the non-critical region in the t-distribution.

How do you calculate the degrees of freedom in a t-test?

• Sample size + 1

• Sample size

• Sample size - 2

• Sample size - 1