WGU C784 APPLIED HEALTHCARE STATISTICS MODULE 6 EXAM PREP 2022/2023(VERIFIED QUESTIONS AND ANSWERS)

WGU C784 APPLIED HEALTHCARE STATISTICS MODULE
6 EXAM PREP 2022/2023
1. An association between two variables is a strong indication of causation. True or False?



a. True



b. False (correct answers)False; Correct. This statement is false. An association between two variables is
not a strong indication of causation. Often there are associations between two variables where
causation does not exist.

2. Causation is a cause-and-effect relationship between two variables. True or False?



a. True



b. False (correct answers)a. True



Correct. This statement is true. Causation indicates a cause-and-effect relationship between two
variables.

3. Sunscreen sales increase when shark attacks become more frequent, therefore there is a causal
relationship. True or False?



a. True



b. False (correct answers)False. There is not a proven cause-and-effect relationship between sunscreen
sales and shark attacks. This is an association, but a causal relationship does NOT exist.

4. One dose of the measles vaccine is about 93% effective at preventing measles, if exposed to the virus.
Doctors, scientists, and epidemiologists have shown that the vaccine is the cause of the reduction in
measles cases. Therefore, there is a causal relationship. True or False?

, a. True



b. False (correct answers)True; Correct. This statement is true. There is a proven cause-and-effect
relationship between the measles vaccine and a reduction in measles cases.

5. Obesity rates decrease as exposure to sunlight increases. Therefore, there is a causal relationship
between sunlight exposure and obesity. True or False?



a. True



b. False (correct answers)False; Correct. This statement is false. We have not shown a proven cause-and-
effect relationship between lack of sunlight exposure and obesity. This is an association, but we cannot
be sure that a causal relationship exists without more information.

A ____________________ variable* is a variable that is associated with both variables, but was not
included in the study. As you may have guessed, the lurking variable in this example is age. Age
increases the risk of high blood pressure. Bone density also decreases with age. (correct answers)Lurking
Variable

A lurking variable can hide the true relationship, or falsely identify a strong relationship, between
variables. True or False? (correct answers)This statement is true. A lurking variable impacts analysis
because it is a variable that is not included as an explanatory variable or response variable.

A lurking variable only affects the response variable. True or False? (correct answers)This statement is
false. A lurking variable can have an effect on both the explanatory and response variables.

A lurking variable is a variable that is included in an original study. True or False? (correct answers)This
statement is false. A lurking variable is not a variable that is intended to be included in the original
analysis.

Lurking variables are unimportant for a correct understanding of cause and effect. True or False?
(correct answers)This statement is false. Lurking variables can offer a more accurate explanation of
cause and effect, such as age causing higher blood pressure and lower bone density.

5. According to the first scatterplot, what type of relationship (if any) is there between testosterone
levels in males and systolic blood pressure?



a. Weak negative association between systolic blood pressure and testosterone levels.