STAT 200 FINAL EXAM
COMPREHENSIVE REVIEW (2026/2027)
QUESTIONS AND ANSWERS
1. A researcher conducts a hypothesis test and obtains a p-value of 0.034. If the significance
level is set at 0.05, which of the following is the most appropriate conclusion?
A. Fail to reject the null hypothesis because the p-value is greater than the significance
level.
B. Accept the null hypothesis as true because the p-value is close to the significance level.
C. Reject the null hypothesis and conclude that there is sufficient evidence for the
alternative hypothesis.
D. Reject the alternative hypothesis because the result is not statistically significant.
Answer: C
Conceptual Explanation: Since the p-value (0.034) is less than the significance level alpha
(0.05), we reject the null hypothesis, indicating sufficient statistical evidence for the
alternative hypothesis.
,2. Which of the following describes a Type II error in the context of hypothesis testing?
A. Rejecting the null hypothesis when it is actually true.
B. Rejecting the alternative hypothesis when it is actually true.
C. Failing to reject the null hypothesis when it is actually false.
D. Accepting the null hypothesis when the alternative hypothesis is false.
Answer: C
Conceptual Explanation: A Type II error, or false negative, occurs when the test fails to
reject a null hypothesis that is actually false.
3. According to the Central Limit Theorem, what happens to the sampling distribution of the
sample mean as the sample size increases?
A. The distribution approaches a normal distribution regardless of the population shape.
B. The mean of the sampling distribution increases.
C. The distribution becomes more skewed.
D. The standard deviation of the sampling distribution increases.
Answer: A
Conceptual Explanation: The Central Limit Theorem states that as sample size increases,
the sampling distribution of the mean approaches a normal distribution, regardless of the
population’s original distribution.
, 4. In a simple linear regression model, if the correlation coefficient (r) is -0.9, what is the
value of the coefficient of determination (R-squared)?
A. -0.81
B. -0.90
C. 0.90
D. 0.81
Answer: D
Conceptual Explanation: The coefficient of determination R-squared is the square of the
correlation coefficient r. (-0.9)^2 = 0.81. It is always non-negative.
5. Which measure of central tendency is most affected by extreme outliers in a dataset?
A. Median
B. Mode
C. Mean
D. Interquartile Range
Answer: C
Conceptual Explanation: The mean uses the values of all observations in its calculation,
making it highly sensitive to extreme outliers compared to the median or mode.
COMPREHENSIVE REVIEW (2026/2027)
QUESTIONS AND ANSWERS
1. A researcher conducts a hypothesis test and obtains a p-value of 0.034. If the significance
level is set at 0.05, which of the following is the most appropriate conclusion?
A. Fail to reject the null hypothesis because the p-value is greater than the significance
level.
B. Accept the null hypothesis as true because the p-value is close to the significance level.
C. Reject the null hypothesis and conclude that there is sufficient evidence for the
alternative hypothesis.
D. Reject the alternative hypothesis because the result is not statistically significant.
Answer: C
Conceptual Explanation: Since the p-value (0.034) is less than the significance level alpha
(0.05), we reject the null hypothesis, indicating sufficient statistical evidence for the
alternative hypothesis.
,2. Which of the following describes a Type II error in the context of hypothesis testing?
A. Rejecting the null hypothesis when it is actually true.
B. Rejecting the alternative hypothesis when it is actually true.
C. Failing to reject the null hypothesis when it is actually false.
D. Accepting the null hypothesis when the alternative hypothesis is false.
Answer: C
Conceptual Explanation: A Type II error, or false negative, occurs when the test fails to
reject a null hypothesis that is actually false.
3. According to the Central Limit Theorem, what happens to the sampling distribution of the
sample mean as the sample size increases?
A. The distribution approaches a normal distribution regardless of the population shape.
B. The mean of the sampling distribution increases.
C. The distribution becomes more skewed.
D. The standard deviation of the sampling distribution increases.
Answer: A
Conceptual Explanation: The Central Limit Theorem states that as sample size increases,
the sampling distribution of the mean approaches a normal distribution, regardless of the
population’s original distribution.
, 4. In a simple linear regression model, if the correlation coefficient (r) is -0.9, what is the
value of the coefficient of determination (R-squared)?
A. -0.81
B. -0.90
C. 0.90
D. 0.81
Answer: D
Conceptual Explanation: The coefficient of determination R-squared is the square of the
correlation coefficient r. (-0.9)^2 = 0.81. It is always non-negative.
5. Which measure of central tendency is most affected by extreme outliers in a dataset?
A. Median
B. Mode
C. Mean
D. Interquartile Range
Answer: C
Conceptual Explanation: The mean uses the values of all observations in its calculation,
making it highly sensitive to extreme outliers compared to the median or mode.
