Question

For questions 3, 4, and 5 refer to the following example:

A researcher believes that older people run faster. She conducts an experiment to test her hypothesis. She recruits 30 children (age 8) and 30 teenagers (age 15). She finds that the children have the slowest race times, and the teenagers have the fastest race time. She concludes that being older makes you run faster.
3. this example, age is:
a. The independent variable (IV).
b. The dependent variable (DV).
c. A sample characteristic (not a variable).
d. The hypothesis.
4. In this example, the time it takes to complete the race is:
a. The inclusion criteria.
b. The outcome.
c. The dependent variable (DV).
d. The independent variable (IV).
5. Children are usually shorter than teenagers. You point out to the researcher that teenagers may run faster because they are taller, not because they are older. In this example height is:
a. The unknown variable.
b. The independent variable (IV).
c. A confound variable.
d. The dependent variable (DV).

Answer 1

3. In this example, age is:
a. The independent variable (IV).Explanation:Age is the independent variable as it is a cause for a change. Here the researcher is measuring the impact of age on running speed.4. In this example, the time it takes to complete the race is:
c. The dependent variable (DV).Explanation: Time is dependent on age, which means that time depends on age. As the age of the participant increases, the running time decreases. Hence, time is a dependent variable.5. In this example height is:
c. A confound variable.Explanation:Height is considered as a confounding variable because it might also be the reason for teenagers running faster. The researcher cannot control the height of the participants, which makes it difficult to determine whether the height or age is the reason behind faster running. A confounding variable is an external variable that affects the relationship between independent and dependent variables.