Chapter 9 Causality
1. In epidemiology, researchers often study a sample instead of an entire population. What
is the primary advantage of using a sample in research?
a. It ensures data is collected from every individual in the population.
b. It reduces the need for statistical inference.
c. It is quicker, less expensive, provides better accuracy, and allows for more specific
analysis.
d. It eliminates the possibility of errors in research findings.
2. Statistical inference is a key concept in epidemiological research. What does statistical
inference allow researchers to do?
a. Make broad assumptions about public health without using data.
b. Use data from a sample to gain information about an entire population.
c. Avoid the need for hypothesis testing in experimental studies.
d. Prove causation rather than correlation in epidemiological studies.
3. A confidence interval is an important statistical tool in epidemiology. Which statement
best describes its purpose?
a. It provides a range of reasonable values in which a population parameter is likely
to lie, based on data from a sample.
b. It determines the exact value of a population parameter.
c. It calculates the probability of a Type I error in statistical testing.
d. It ensures that the sample used in a study is representative of the population.
4. In epidemiological research, hypotheses are essential for guiding investigations. How is a
hypothesis best defined?
, a. A definitive statement proving causation between two factors.
b. A statistical method used to eliminate confounding variables.
c. A reasoned proposal predicting an association among multiple factors or
explaining an observed phenomenon.
d. A mathematical model used to calculate the probability of disease occurrence.
5. Inductive reasoning is a fundamental approach in epidemiology. Which scenario best
illustrates inductive reasoning?
a. A researcher formulates a general theory about disease transmission and then tests
specific cases to confirm it.
b. A researcher observes a pattern of disease outbreaks in a specific population and
then develops a general explanation for their occurrence.
c. A scientist uses laboratory experiments to test a single exposure’s effect on disease
risk.
d. A health official makes assumptions about disease risk based on personal experience
rather than collected data.
6. In scientific research, inductive reasoning relies on several essential components. Which
of the following is NOT a key requirement for inductive reasoning to be valid?
a. A randomized experimental study with a control group.
b. Exact and correct observations.
c. Accurate interpretation of facts to understand relationships and causality.
d. A scientific approach that provides clear, rational explanations of findings.
7. The p-value is used in epidemiological studies to assess statistical significance. What
does a p-value indicate?
1. In epidemiology, researchers often study a sample instead of an entire population. What
is the primary advantage of using a sample in research?
a. It ensures data is collected from every individual in the population.
b. It reduces the need for statistical inference.
c. It is quicker, less expensive, provides better accuracy, and allows for more specific
analysis.
d. It eliminates the possibility of errors in research findings.
2. Statistical inference is a key concept in epidemiological research. What does statistical
inference allow researchers to do?
a. Make broad assumptions about public health without using data.
b. Use data from a sample to gain information about an entire population.
c. Avoid the need for hypothesis testing in experimental studies.
d. Prove causation rather than correlation in epidemiological studies.
3. A confidence interval is an important statistical tool in epidemiology. Which statement
best describes its purpose?
a. It provides a range of reasonable values in which a population parameter is likely
to lie, based on data from a sample.
b. It determines the exact value of a population parameter.
c. It calculates the probability of a Type I error in statistical testing.
d. It ensures that the sample used in a study is representative of the population.
4. In epidemiological research, hypotheses are essential for guiding investigations. How is a
hypothesis best defined?
, a. A definitive statement proving causation between two factors.
b. A statistical method used to eliminate confounding variables.
c. A reasoned proposal predicting an association among multiple factors or
explaining an observed phenomenon.
d. A mathematical model used to calculate the probability of disease occurrence.
5. Inductive reasoning is a fundamental approach in epidemiology. Which scenario best
illustrates inductive reasoning?
a. A researcher formulates a general theory about disease transmission and then tests
specific cases to confirm it.
b. A researcher observes a pattern of disease outbreaks in a specific population and
then develops a general explanation for their occurrence.
c. A scientist uses laboratory experiments to test a single exposure’s effect on disease
risk.
d. A health official makes assumptions about disease risk based on personal experience
rather than collected data.
6. In scientific research, inductive reasoning relies on several essential components. Which
of the following is NOT a key requirement for inductive reasoning to be valid?
a. A randomized experimental study with a control group.
b. Exact and correct observations.
c. Accurate interpretation of facts to understand relationships and causality.
d. A scientific approach that provides clear, rational explanations of findings.
7. The p-value is used in epidemiological studies to assess statistical significance. What
does a p-value indicate?
