Question 1

The ability to make a causal inference between two variables is a function of the statistical techniques one uses,not the research design used to generate the data that are analyzed by those statistical techniques.

Accepted Answer

The ability to make a causal inference between two variables is heavily dependent on the research design used to generate the data. Statistical techniques can help support or refute causal relationships, but they cannot create a causal relationship if one does not exist in the data.

Question 2

A procedure for reducing sampling error is to define the groups such that the variances of scores in the populations (ó²)will be smaller.

Accepted Answer

This is true as reducing the variance of scores in the populations will lead to less variability among the sample means, which in turn will result in less sampling error.

Question 3

One way an investigator can reduce sampling error is to reduce the sample sizes for the various groups.

Accepted Answer

To reduce sampling error, increasing the sample sizes for the various groups is recommended. This allows for a more representative sample of the population and reduces the likelihood of obtaining results that are biased or do not accurately reflect the larger population.

Question 4

A disturbance variable increases sampling error by increasing variability within groups.

Accepted Answer

A disturbance variable can introduce additional sources of variability within groups, which can result in increased sampling error. This is because the disturbance variable makes it more difficult to distinguish true group differences from random variation, making it more likely that observed differences are due to chance rather than the variables being studied.

Question 5

Random assignment guarantees that the research groups will not differ beforehand on the dependent variable.

Accepted Answer

Random assignment ensures that each participant has an equal chance of being placed in any group, which helps control for pre-existing differences, but it does not guarantee that groups will be identical on the dependent variable.

Question 6

One advantage of the between-subjects approach as compared with the within-subjects approach is that it is more economical in terms of the number of research participants.

Accepted Answer

The between-subjects approach requires more participants because each participant is only exposed to one condition, unlike the within-subjects approach where the same participants are used across all conditions.

Question 7

In practice,it is often difficult to identify appropriate variables to serve as a basis
for matching,and,once identified,to readily complete the matching process.

Accepted Answer

Matching requires identifying appropriate variables that are both predictive of the outcome and well-balanced across treatment and control groups. This can be a challenging task, and even when appropriate variables are identified, the process of completing the matching may be time-consuming and complex.

Question 8

With the technique of matching,an individual in one group is "matched" with an individual in each of the other groups such that all of these individuals have the
same value on the independent variable.

Accepted Answer

Matching involves pairing individuals across groups based on similar values of confounding variables, not the independent variable.

Question 9

For many observational independent variables,only between-subjects designs are applicable.

Accepted Answer

Observational independent variables refer to variables that cannot be manipulated by the researcher, such as age, gender, and race. In some cases, it may be possible to use within-subjects designs to study these variables (e.g., by measuring changes over time within the same individuals). However, for many observational independent variables, only between-subjects designs are applicable.

Question 10

When an experimental research strategy is used,inferences of causation can be made only when confounded variables are controlled.

Accepted Answer

Confounding variables are the variables that affect the dependent variable along with the independent variable. In order to make a causal inference, it is important to control for these confounding variables. This is the main advantage of using an experimental research strategy, as it allows researchers to manipulate the independent variable and control for other variables that may affect the outcome. Therefore, the statement is true that inferences of causation can be made only when confounded variables are controlled.

Question 11

Random assignment is feasible only when an investigator is using a manipulative experimental strategy to "create" values on an independent variable.

Accepted Answer

Random assignment involves randomly assigning subjects to different groups or conditions in an experiment. This is typically done when the independent variable is being manipulated by the researcher. Random assignment helps to control for extraneous variables and increase the internal validity of the experiment. It would not be necessary or feasible if the researcher is not manipulating an independent variable.

Question 12

Since experimental independent variables will always be confounded with all other variables that are naturally related to them,causal inferences are typically not possible when an experimental research strategy is used.

Accepted Answer

While it is true that experimental independent variables can be confounded with other naturally related variables, researchers use experimental designs precisely to minimize or control these confounding factors so that causal inferences CAN be made.

Question 13

Random assignment is an effective method for controlling confounding variables defined by individual differences.

Accepted Answer

Random assignment involves randomly assigning participants to different groups, which helps to ensure that any individual differences between the groups are evenly distributed. This reduces the likelihood of confounding variables skewing the results.

Question 14

A confounding variable is one that is related to the independent variable (the presumed cause)and that affects the dependent variable (the presumed effect),rendering a relational inference between the independent variable and the dependent variable ambiguous.

Accepted Answer

This is the correct definition of a confounding variable. It is related to the independent variable and affects the dependent variable, making it difficult to determine the true relationship between the two.

Question 15

It is entirely possible for two variables to be related to one another,but for no causal relationship to exist between them.

Accepted Answer

This is true. Just because two variables have a correlation or association does not mean that one causes the other. There could be other factors or variables that are the actual cause.

Question 16

A disturbance variable is one that is related to the independent variable (and hence,confounded with it)but that also affects the dependent variable.

Accepted Answer

The answer of A disturbance variable is one that is...

Question 17

A between-subjects variable is one whose values are "split up" between subjects instead of occurring completely within the same individuals.

Accepted Answer

A between-subjects variable refers to a characteristic or condition that varies between different individuals or groups of participants in a study. It is also referred to as an independent variable because researchers manipulate or select the levels of this variable and assign participants to different groups based on these levels. For example, in a study comparing the effectiveness of two different treatments for a medical condition, the treatment received would be a between-subjects variable as it is assigned to different participants.

Question 18

Between-subjects designs and within-subjects designs are both viable strategies only when the independent variable is experimental in nature.

Accepted Answer

Both between-subjects and within-subjects designs can be used with experimental variables as well as non-experimental variables such as gender, age, or personality traits. Therefore, the statement is false.

Question 19

The major disadvantage of holding a variable constant is that it may restrict the generalizability of the results.

Accepted Answer

When a variable is held constant, it means it is not allowed to vary or change during the study. This may limit the scope of the study and make it difficult to generalize the results to other situations or populations where the variable is not held constant. Therefore, holding a variable constant can be a major disadvantage in research.

Question 20

Since random assignment cannot be applied to experimental groups,experimental
variables will always be confounded with all other variables that are naturally related to them.

Accepted Answer

Random assignment can be applied to experimental groups. It is a method used to assign participants to different groups in an experiment in a random and unbiased manner. By doing so, researchers can control for extraneous variables and increase the internal validity of the study. Therefore, experimental variables will not always be confounded with all other variables that are naturally related to them.

Quiz 9: Principles of Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships