Question 1

________ is defined as the amount of change in one variable systematically associated with a change in another variable.
A)Correspondence
B)Covariation
C)Covariable change analysis
D)An alpha relationship
E)A beta relationship

Accepted Answer

Covariation is the statistical relationship between two variables, indicating how much they systematically increase or decrease together.

Question 2

The stronger a relationship the:
A)larger the absolute size of the correlation coefficient
B)larger the strength coefficient
C)closer to zero is the correlation coefficient
D)larger, positive size of the correlation coefficient
E)larger the beta

Accepted Answer

The strength of a relationship between two variables in statistics is often measured by the correlation coefficient. The closer the absolute value of the correlation coefficient is to 1, the stronger the relationship. This means that both strong positive and strong negative relationships will have a large absolute size of the correlation coefficient, regardless of the direction of the relationship.

Question 3

Which type of relationship is described by the formula: y = a + bx?
A)causal relationship
B)linear relationship
C)categorical relationship
D)Boolean relationship
E)a beta relationship

Accepted Answer

The formula y = a + bx describes a linear relationship between two variables, where "x" is the independent variable and "y" is the dependent variable. The slope "b" of the line determines the direction and strength of the relationship.

Question 4

Which type of relationship is a "straight-line" relationship between two variables which allows us to know one variable if we have knowledge of the other?
A)causal relationship
B)linear relationship
C)categorical relationship
D)Boolean relationship
E)a beta relationship

Accepted Answer

A straight-line relationship between two variables is known as a linear relationship, where a change in one variable causes a proportional change in the other variable. Hence, if we know the value of one variable, we can calculate the value of the other variable using a simple linear function. Therefore, option B, i.e., linear relationship, is the correct answer. The other options are incorrect as they do not describe this type of relationship between two variables.

Question 5

What is the name of the statistical procedure to determine if a systematic linear relationship exists between two metric-scaled variables?
A)chi-square
B)correlation coefficient
C)Pearson chi-square
D)Pearson Product Moment Correlation Coefficient
E)Pearson Beta coefficient

Accepted Answer

The Pearson Product Moment Correlation Coefficient is the statistical procedure used to determine if a systematic linear relationship exists between two metric-scaled variables.

Question 6

Bivariate regression analysis is defined as a predictive analysis technique in which:
A)a pattern in one variable is identified over time and projected into the future
B)a relationship between three variables that exists across time is observed to make a prediction
C)one variable is used to predict the level of another variable
D)two variables are used to predict two others by the use of a scatter diagram
E)three or more variables variances are analyzed

Accepted Answer

Bivariate regression analysis involves using one variable to predict the level of another variable. It does not involve analyzing three or more variables, identifying patterns over time, or using scatter diagrams to predict multiple variables.

Question 7

Which of the following is true of the dependent variable in regression analysis?
A)used to predict the independent variable, and it is the x in the regression formula
B)used to predict the independent variable, and it is the y in the regression formula
C)predicted, and it is usually termed x in the regression formula
D)predicted, and it is usually termed y in the regression formula
E)predicted by the categorical variable, termed i, in the regression formula

Accepted Answer

The dependent variable is the variable that is being predicted or explained in the regression analysis, and it is typically denoted as y in the regression formula. Therefore, option D is the correct answer. Option A is incorrect because the dependent variable is what is being predicted, not what is used to predict the independent variable. Option B is incorrect because the independent variable is typically denoted as x in the regression formula. Option C is incorrect because it is the independent variable that is usually denoted as x in the regression formula, not the dependent variable. Option E is also incorrect because the categorical variable is not typically used to predict the dependent variable in regression analysis.

Question 8

The null hypothesis for a correlation states that:
A)the population correlation coefficient is equal to zero.
B)the population correlation coefficient is +1.
C)the population correlation coefficient is -1
D)the population correlation coefficient is ±1.
E)the population correlation coefficient is positive.

Accepted Answer

The null hypothesis for a correlation states that the population correlation coefficient is equal to zero. This implies that there is no relationship between the two variables being studied.

Question 9

A ________ (where the target variable is clearly indicated,probably in the title,and the statistically significant positive and negative correlations are identified and separated)is suggested when presenting correlation findings.
A)table
B)cross-tabulation table
C)lengthy discussion
D)graph
E)none of the above; there is no "best" communication vehicle for cross-tabulation analysis.

Accepted Answer

A table is suggested for presenting correlation findings as it clearly indicates the target variable and separates statistically significant positive and negative correlations.

Question 10

Should XL Data Analyst find there is no significant relationship in a cross-tabulation table,it:
A)presents Column or Row Percents with a warning
B)presents both Column and Row Percents
C)presents only Column Percents
D)presents an asterisk
E)none of the above; inspecting a table of non-significant relationships is not productive

Accepted Answer

When analyzing data, if a cross-tabulation reveals no significant relationship, it is generally considered unproductive to further inspect or present the table in detail. The focus should shift to more promising analyses or relationships that could yield actionable insights.

Question 11

If you wished to perform correlation analysis using your XL Data Analyst,which command sequence would you use?
A)Relate-Correlate
B)Correlate-Summarize
C)Coefficient-Relate
D)Correlate-Pearson-Beta
E)none of the above; XL Data Analyst will not run correlation analysis

Accepted Answer

The correct command sequence for performing correlation analysis in XL Data Analyst is "Relate-Correlate".

Question 12

Which of the following is NOT true regarding the independent variable in regression analysis?
A)It is used to predict the dependent variable.
B)It is the x in the regression formula.
C)The term independent variable is an arbitrary designation.
D)It is predicted by the dependent variable.
E)There is no cause-and-effect relationship or true dependence between the dependent and the independent variables.

Accepted Answer

The independent variable is used to predict the dependent variable and is represented by x in the regression formula. The term "independent variable" is arbitrary in that it does not necessarily indicate true independence from other variables in the model. There is also no implication of causality or true dependence between the independent and dependent variables. However, the independent variable is not predicted by the dependent variable.

Question 13

In the formula for a straight line,the b stands for the ________.
A)intercept
B)dependent variable
C)independent variable
D)slope
E)predicted variable

Accepted Answer

The answer of In the formula for a straight line,the...

Question 14

A correlation coefficient is an index number constrained to fall between the range of:
A)0 to 1.00
B)0 to 100
C)-1.00 to +1.00
D).05 to .95
E)none of the above; it is not constrained

Accepted Answer

Correlation coefficient is a measure of the degree of the linear relationship between two variables. It varies between -1.00 and +1.00, where -1.00 indicates a perfect negative correlation, 0 indicates no correlation, and +1.00 indicates a perfect positive correlation. Therefore, the correct range is -1.00 to +1.00.

Question 15

Assume you run a correlation analysis and your XL Data Analyst informs you that you have a significant relationship.What can you use to determine how strong the relationship is?
A)the strength coefficient, which ranges from 1 to 10, with 10 being the strongest
B)the strength coefficient, which ranges from 1 to 5, with 5 being the strongest
C)the size of the correlation coefficient
D)the size of the beta
E)none of the above; correlation is not measured in terms of strength

Accepted Answer

The size of the correlation coefficient indicates the strength of the relationship. A correlation coefficient of 1 indicates a perfect positive relationship, whereas a correlation coefficient of -1 indicates a perfect negative relationship. The closer the coefficient is to 0, the weaker the relationship. Therefore, the size of the correlation coefficient is the best choice to determine the strength of the relationship in a correlation analysis. Choices A, B, and D are not valid options as there is no universally accepted strength coefficient or beta coefficient range for correlation analysis. Choice E is incorrect as correlation is indeed measured in terms of strength.

Question 16

What is the command sequence for the XL Data Analyst to perform cross-tabulation analysis and generate row and column percentage tables?
A)Go-Boolean
B)Summarize-Boolean-Cross
C)Relate-Crosstabs
D)Relate-2 Variables
E)Relate-Boolean-Stacked Bar

Accepted Answer

The command sequence for performing cross-tabulation analysis and generating row and column percentage tables in XL Data Analyst is Relate-Crosstabs. This command allows the user to define the row and column variables, specify filtering options, and choose the statistical measures to be computed. It also provides the option to generate row and column percentages, which are useful for comparing the relative frequencies of different categories. Therefore, Option C is the best choice for this task.

Question 17

Correlation coefficients that fall between -1.00 and -.81 or between -1.00 and -.81 are generally considered to be:
A)weak
B)moderate
C)strong
D)nonexistent
E)very weak

Accepted Answer

Correlation coefficients that fall between -1.00 and -.81 or between .81 and 1.00 (assuming a typo in the question) are generally considered to be strong, indicating a strong relationship between the variables.

Question 18

If a correlation coefficient is not statistically significant:
A)you can still use the size of the coefficient to indicate the amount of the association though you know it is not significant
B)you can use the direction of the coefficient to indicate the nature of the association though you know it is not significant
C)you must assume the correlation is zero; the coefficient has no meaning at all
D)you should rerun the analysis to see if the beta is significant
E)none of the above; all coefficients are statistically significant

Accepted Answer

The correlation coefficient has no meaning at all if it is not statistically significant.

Question 19

Which of the following is NOT true of a scatter diagram?
A)It plots data pairs in an x- and y-axis graph.
B)It will portray the amount of covariation between two metric variables.
C)It plots the points corresponding to each matched pair of x and y variables.
D)When there is no apparent association or relationship between two variables, the points on a scatter diagram fail to create any identifiable pattern.
E)There is no relationship between scatter diagrams and correlation coefficients.

Accepted Answer

Scatter diagrams and correlation coefficients are closely related. In fact, correlation coefficients are often used to quantify the strength and direction of the relationship between variables in a scatter diagram. Therefore, statement E is not true.

Question 20

A predictive analysis technique in which variables are used to predict the level of another by use of the straight-line formula,y= a + bx is:
A)chi-square
B)Pearson correlation
C)digression analysis
D)regression analysis
E)summarization analysis

Accepted Answer

The technique described in the question is regression analysis. The formula y = a + bx is the equation for a simple linear regression, where y is the dependent variable being predicted using the independent variable x. The other options listed are not relevant to this type of analysis.

Quiz 14: Determining Relationships

________ is defined as the amount of change in one variable systematically associated with a change in another variable.

The stronger a relationship the:

Which type of relationship is described by the formula: y = a + bx?

Which type of relationship is a "straight-line" relationship between two variables which allows us to know one variable if we have knowledge of the other?

What is the name of the statistical procedure to determine if a systematic linear relationship exists between two metric-scaled variables?

Bivariate regression analysis is defined as a predictive analysis technique in which:

Which of the following is true of the dependent variable in regression analysis?

The null hypothesis for a correlation states that:

A ________ (where the target variable is clearly indicated,probably in the title,and the statistically significant positive and negative correlations are identified and separated) is suggested when presenting correlation findings.

Should XL Data Analyst find there is no significant relationship in a cross-tabulation table,it:

If you wished to perform correlation analysis using your XL Data Analyst,which command sequence would you use?

Which of the following is NOT true regarding the independent variable in regression analysis?

In the formula for a straight line,the b stands for the ________.

A correlation coefficient is an index number constrained to fall between the range of:

Assume you run a correlation analysis and your XL Data Analyst informs you that you have a significant relationship.What can you use to determine how strong the relationship is?

What is the command sequence for the XL Data Analyst to perform cross-tabulation analysis and generate row and column percentage tables?

Correlation coefficients that fall between -1.00 and -.81 or between -1.00 and -.81 are generally considered to be:

If a correlation coefficient is not statistically significant:

Which of the following is NOT true of a scatter diagram?

A predictive analysis technique in which variables are used to predict the level of another by use of the straight-line formula,y= a + bx is: