Question 1

A common strategy to control disturbance variables is (are):

Accepted Answer

The answer of A common strategy to control disturbance variables...

Question 2

Statisticians can determine the effects of violating assumptions by using _____ or performing _____.

Accepted Answer

Statisticians use mathematical logic to theoretically understand the effects of assumption violations and Monte Carlo studies to empirically simulate and analyze these effects.

Question 3

Which of the following statements is true of a control group?

Accepted Answer

A control group is a group that is not exposed to the experimental manipulation and therefore acts as a baseline for evaluating the effects of the manipulation. Therefore, statement B is true. Statements A and C are incorrect as a control group is not a level of the dependent variable and it is not always measured in the observational sense. Therefore, the correct answer is B.

Question 4

_____ refers to the extent to which conclusions drawn on the basis of a statistical test (for example,rejection of the null hypothesis)are unaffected by violations of the assumptions underlying the test.

Accepted Answer

Robustness refers to the ability of a statistical test to perform adequately even when assumptions about the data being tested are violated. In other words, the conclusions drawn from a statistical test should be robust (or reliable) in the face of outliers, non-normality, or other departures from the assumptions of the statistical test. Therefore, choice C, robustness, is the correct answer.

Question 5

Random assignment is possible with

Accepted Answer

The answer of Random assignment is possible with
...

Question 6

Which of the following levels of measurement can be appropriately analyzed with nonparametric statistics?

Accepted Answer

The answer of Which of the following levels of measurement...

Question 7

A matched-subjects design often has the power of a within-subjects design while avoiding the problem(s)of ___.

Accepted Answer

A matched-subjects design selects pairs of participants who are similar on relevant characteristics, such as age or IQ, and assigns one member of each pair to the treatment group and the other to the control group. By doing so, the design controls for individual differences between the groups, which is a problem with between-subjects designs. The design also avoids carry-over effects because each participant only receives one level of the independent variable. However, subject economy is not a problem with matched-subjects design as it requires the same number of participants as a between-subjects design.

Question 8

A confounding variable

Accepted Answer

A confounding variable is related to both the independent and dependent variables, potentially affecting the outcome of the study.

Question 9

Experimental and observational strategies can be used together.

Accepted Answer

Experimental and observational strategies can be combined to get a more complete understanding of the phenomenon being studied. For example, an experiment can be designed to test a specific hypothesis or intervention, while observational data can be collected to provide additional information or to validate the findings of the experiment. However, it is important to carefully consider the strengths and limitations of both strategies and to ensure that they are used appropriately to address the research question at hand.

Question 10

Two important distributional assumptions are the _____ assumption and the _____ assumption.

Accepted Answer

The two important distributional assumptions are normality and homogeneity of variance. Normality assumes that the data follows a normal distribution, while homogeneity of variance assumes that the variances of the groups being compared are equal. Collapse

Question 11

A problem with holding a variable,such as gender,constant is that

Accepted Answer

Holding a variable, such as gender, constant can reduce the generalizability of the results because it may overlook differences that exist within different genders. This may limit the ability to apply the findings to the larger population. Therefore, it is usually better to include the variable as a factor in the study rather than holding it constant.

Question 12

Which of the following methods can be used in the design of a study to control for alternative explanations of the results?

Accepted Answer

Random assignment to experimental groups helps to control for alternative explanations by ensuring that individuals in each group are on average similar in all respects, including background characteristics that could affect the outcome. Increasing the sample size for each group reduces sampling error, making the results more reliable. Defining the groups in such a way as to reduce variance can also help to control for alternative explanations, as it means that the groups are more homogeneous and differences between them are more likely to be due to the treatment being tested. Together, these methods provide a strong basis for designing a study that can safely attribute observed effects to the treatment being tested, rather than to other factors.

Question 13

Based on the Applications to the Analysis of Social Problems section of Chapter 9,historical variables that are confounded with age refer to

Accepted Answer

The answer of Based on the Applications to the Analysis...

Question 14

A common strategy to control confounding variables is (are):

Accepted Answer

All three strategies listed - holding a variable constant, matching, and random assignment to experimental groups - are commonly used to control confounding variables. Holding a variable constant involves keeping a particular variable the same for all participants or groups in a study, so that it cannot be a source of variation between groups. Matching involves selecting comparison groups that are similar on important variables that could be confounding factors. Random assignment helps to ensure that any potential confounding variables are distributed evenly across groups, reducing the likelihood that one group will have a particular confounding variable that causes an effect. Therefore, the best choice would be D - all of these.

Question 15

Which of the following can influence a test of robustness?

Accepted Answer

All of the options listed can influence a test of robustness. 
- Sample size can affect the power of the statistical test and the ability to detect violations of assumptions. 
- The degree of violation refers to the level of departure from the assumptions of the test, and a higher degree of violation might affect the validity of the results. 
- The form of violation refers to the nature of the departure from the assumptions, and different forms of violation might require different approaches to testing robustness.

Question 16

A disturbance variable

Accepted Answer

A disturbance variable is an unmeasured or uncontrollable variable that affects the dependent variable but is not accounted for in the study design. Therefore, it is not related to the independent variable but affects the dependent variable.

Question 17

A(n)_________ strategy is where a set of procedures or manipulations is performed to created different values of the independent variable for the research participants;while a(n)__________ strategy involves measuring differences in values that naturally exist in the research participants.

Accepted Answer

Experimental strategy involves manipulating an independent variable to see its effect on the dependent variable, while nonexperimental strategy involves making observations without manipulating any variables. Therefore, option D best fits the description of this scenario.

Question 18

The extent to which conclusions made on the basis of a statistical test are unaffected by violations of the assumptions underlying the test is called ____.

Accepted Answer

Robustness refers to the ability of a statistical test to produce accurate or valid results even when assumptions underlying the test are violated to some extent. In other words, robustness refers to the extent to which the results of a statistical test are resistant to deviations from the assumptions. Therefore, option A) is the correct choice. Option B) refers to the level of significance chosen by the researcher for the test, and option C) refers to the ability of a statistical test to detect an effect if it exists, which are not related to the robustness of the test. Therefore, options B) and C) are not the correct choices in this context.

Question 19

_____ statistics tend to focus on medians,interquartile ranges,and ordinal level measures.

Accepted Answer

Nonparametric statistics are used when data does not meet the assumptions of parametric statistics, such as having a normal distribution. They typically focus on measures such as medians, interquartile ranges, and other ordinal level measures. Qualitative statistics focus on categorical data, while quantitative statistics focus on numerical data.

Question 20

_____ statistics require quantitative dependent variables and are usually applied when these variables are measured on a level that at least approximates interval characteristics.

Accepted Answer

Parametric statistics assume that the data follow a normal distribution and require interval or ratio level data. Nonparametric statistics are used when the data is not normally distributed or when the data is measured on ordinal or nominal scales. Quantitative data refers to numerical data while qualitative data refers to non-numerical data.

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

A common strategy to control disturbance variables is (are) :

Statisticians can determine the effects of violating assumptions by using _ or performing _.

Which of the following statements is true of a control group?

_____ refers to the extent to which conclusions drawn on the basis of a statistical test (for example,rejection of the null hypothesis) are unaffected by violations of the assumptions underlying the test.

Random assignment is possible with

Which of the following levels of measurement can be appropriately analyzed with nonparametric statistics?

A matched-subjects design often has the power of a within-subjects design while avoiding the problem(s) of ___.

A confounding variable

Experimental and observational strategies can be used together.

Two important distributional assumptions are the _ assumption and the _ assumption.

A problem with holding a variable,such as gender,constant is that

Which of the following methods can be used in the design of a study to control for alternative explanations of the results?

Based on the Applications to the Analysis of Social Problems section of Chapter 9,historical variables that are confounded with age refer to

A common strategy to control confounding variables is (are) :

Which of the following can influence a test of robustness?

A disturbance variable

A(n) _ strategy is where a set of procedures or manipulations is performed to created different values of the independent variable for the research participants;while a(n) __ strategy involves measuring differences in values that naturally exist in the research participants.

The extent to which conclusions made on the basis of a statistical test are unaffected by violations of the assumptions underlying the test is called ____.

_____ statistics tend to focus on medians,interquartile ranges,and ordinal level measures.

_____ statistics require quantitative dependent variables and are usually applied when these variables are measured on a level that at least approximates interval characteristics.

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

A common strategy to control disturbance variables is (are) :

Statisticians can determine the effects of violating assumptions by using _____ or performing _____.

Which of the following statements is true of a control group?

_____ refers to the extent to which conclusions drawn on the basis of a statistical test (for example,rejection of the null hypothesis) are unaffected by violations of the assumptions underlying the test.

Random assignment is possible with

Which of the following levels of measurement can be appropriately analyzed with nonparametric statistics?

A matched-subjects design often has the power of a within-subjects design while avoiding the problem(s) of ___.

A confounding variable

Experimental and observational strategies can be used together.

Two important distributional assumptions are the _____ assumption and the _____ assumption.

A problem with holding a variable,such as gender,constant is that

Which of the following methods can be used in the design of a study to control for alternative explanations of the results?

Based on the Applications to the Analysis of Social Problems section of Chapter 9,historical variables that are confounded with age refer to

A common strategy to control confounding variables is (are) :

Which of the following can influence a test of robustness?

A disturbance variable

A(n) _________ strategy is where a set of procedures or manipulations is performed to created different values of the independent variable for the research participants;while a(n) __________ strategy involves measuring differences in values that naturally exist in the research participants.

The extent to which conclusions made on the basis of a statistical test are unaffected by violations of the assumptions underlying the test is called ____.

_____ statistics tend to focus on medians,interquartile ranges,and ordinal level measures.

_____ statistics require quantitative dependent variables and are usually applied when these variables are measured on a level that at least approximates interval characteristics.

Statisticians can determine the effects of violating assumptions by using _ or performing _.

Two important distributional assumptions are the _ assumption and the _ assumption.

A(n) _ strategy is where a set of procedures or manipulations is performed to created different values of the independent variable for the research participants;while a(n) __ strategy involves measuring differences in values that naturally exist in the research participants.