Final Exam Practice Questions (2)

Front

What is the expected count in a contingency table cell?

Back

The expected count in a contingency table cell is calculated based on the proportion of the total sample size that falls into that category, often used in chi-square tests.

Front

How do you conduct a two-sample t-test?

Back

To conduct a two-sample t-test, randomly assign subjects to two groups, apply different treatments or conditions, and then compare the means of the two groups to assess if there is a statistically significant difference.

Front

What happens to the standard deviation as sample size increases?

Back

As the sample size increases, the standard deviation of the sampling distribution of the sample mean decreases, leading to more precise estimates.

Front

What is the mean and standard deviation of a sample proportion?

Back

For a sample proportion p̂, the mean is equal to the population proportion (p), and the standard deviation is calculated as sqrt[(p(1-p)/n)], where n is the sample size.

Front

What does a P-value of 0.05 indicate in hypothesis testing?

Back

A P-value of 0.05 indicates that there is a 5% probability of observing the data, or something more extreme, if the null hypothesis is true. It is commonly used as a threshold for statistical significance.

Front

Define the term 'null hypothesis'.

Back

The null hypothesis is a statement that there is no effect or no difference, and it serves as the default assumption in hypothesis testing.

Front

What is a confidence interval?

Back

A confidence interval is a range of values derived from sample data that is likely to contain the true population parameter with a specified level of confidence, typically 95%.

Front

Explain the concept of statistical significance.

Back

Statistical significance indicates that the observed results are unlikely to have occurred by chance alone, typically assessed using a P-value.

Front

What is the difference between Type I and Type II errors?

Back

Type I error occurs when the null hypothesis is incorrectly rejected (false positive), while Type II error occurs when the null hypothesis is not rejected when it is false (false negative).

Front

What is a sampling distribution?

Back

A sampling distribution is the probability distribution of a statistic (like the sample mean) obtained from a large number of samples drawn from the same population.