---

Question 1:

Which of the following statements is true about experimental variables?

A) Experimental variables are held constant or controlled.
B) Experimental variables are not important in an experiment.
C) Experimental variables are the variables being manipulated or changed.
D) Experimental variables are the outcome variables of an experiment.

Show Answer

Explanation: The correct answer is C) Experimental variables are the variables being manipulated or changed. Experimental variables, also known as independent variables, are the variables that are intentionally manipulated or changed by the researcher in an experiment. They are the factors of interest that are hypothesized to have an effect on the dependent variable.

---

Question 2:

What is the purpose of control variables in an experiment?

A) Control variables are the variables being manipulated or changed.
B) Control variables are held constant to ensure a fair comparison.
C) Control variables are the outcome variables of an experiment.
D) Control variables are not necessary in an experiment.

Show Answer

Explanation: The correct answer is B) Control variables are held constant to ensure a fair comparison. Control variables, also known as constant variables, are the variables that are intentionally kept constant or controlled throughout an experiment. They are important for reducing or eliminating the influence of potential confounding factors on the dependent variable. By holding control variables constant, researchers can ensure that any observed effects or changes in the dependent variable are primarily due to the manipulation of the independent variable.

---

Question 3:

What is the purpose of the control group in an experiment?

A) The control group is the group that receives the experimental treatment.
B) The control group is not important in an experiment.
C) The control group provides a baseline for comparison.
D) The control group is the group that measures the dependent variable.

Show Answer

Explanation: The correct answer is C) The control group provides a baseline for comparison. The control group in an experiment is a group of participants or subjects that does not receive the experimental treatment or intervention. It serves as a baseline against which the effects of the experimental group are compared. By comparing the outcomes of the control group with those of the experimental group, researchers can determine the specific effects of the independent variable on the dependent variable.

---

Question 4:

Which of the following is an example of a control variable in an experiment?

A) The variable being manipulated or changed.
B) The variable that is held constant or controlled.
C) The outcome variable of the experiment.
D) The variable that represents different categories or groups.

Show Answer

Explanation: The correct answer is B) The variable that is held constant or controlled. Control variables, also known as constant variables, are the variables that are intentionally kept the same or held constant throughout an experiment. They are important for ensuring that any observed effects or changes in the dependent variable are primarily due to the manipulation of the independent variable and not influenced by other factors.

---

Question 5:

What is the purpose of random assignment in an experiment?

A) Random assignment ensures that participants have similar characteristics.
B) Random assignment ensures a fair comparison between groups.
C) Random assignment determines the outcome of the experiment.
D) Random assignment eliminates the need for control variables.

Show Answer

Explanation: The correct answer is B) Random assignment ensures a fair comparison between groups. Random assignment is the process of randomly assigning participants to different groups in an experiment. It helps ensure that the participants in each group are similar in terms of their characteristics and that any differences observed between groups are primarily due to the manipulation of the independent variable. Random assignment reduces the likelihood of bias and confounding variables, allowing for a more valid and reliable comparison of the effects of the independent variable.