Question 1

A statistical test that can examine the relationship between two interval or ratio level variables while controlling for the influence of a third, potentially confounding one is&#10;A) partial r.&#10;B) Pearson's r.&#10;C) factor analysis.&#10;D) Kendall's tau.

Accepted Answer

Partial r is a statistical test that can examine the relationship between two interval or ratio level variables while controlling for the influence of a third, potentially confounding one. Pearson's r and Kendall's tau are measures of association between two variables but do not allow for control of a third variable. Factor analysis is a method for analyzing the interrelationships among variables, but does not examine the relationship between specific variables while controlling for a third.

Question 2

Two variables reflected a strong, statistically significant negative correlation within a research sample. How should this be interpreted?&#10;A) The values of one variable cannot have caused the values of the other variable.&#10;B) The values of the predictor variable caused the values of the outcome variable.&#10;C) The values of the outcome variable caused the values of the predictor variables.&#10;D) The values of the predictor value may have caused the values of the outcome variable.

Accepted Answer

A negative correlation indicates that as the values of one variable increase, the values of the other variable decrease. This does not necessarily mean that the values of one variable caused the values of the other variable, but it does suggest that there may be a causal relationship between the two variables.

Question 3

A form of statistical analysis that uses correlation to identify redundancy in a newly constructed data collection instrument so that it can be eliminated or equivalent forms of the instrument can be developed is:

A) factor analysis
B) cluster analysis
C) Multiple R
D) factor rotation

factor analysis

Accepted Answer

Factor analysis is a statistical method that can be used to identify redundancy in a data collection instrument by analyzing the interrelationships among a large set of variables. It aims to identify a smaller number of latent variables (or factors) that can explain the covariation among the observed variables. This can help researchers to identify items or questions in the instrument that may be measuring the same underlying construct, and eliminate them or develop equivalent forms of the instrument. Cluster analysis is a method used to group individuals or objects based on similarities in their characteristics, and Multiple R is a statistical method used to examine the relationship between two or more variables. Factor rotation is a technique used to simplify and clarify the factor structure of a set of variables, but it does not directly address redundancy in a data collection instrument.

Question 4

If, in the previous question, the correlation had been -1.0, what would happen after the students are asked to line up by weight?&#10;A) About half of the students will move; others will stay in place.&#10;B) Only the 13th student will stay in place; everyone else will move to the same position but in the opposite end of the line.&#10;C) Everyone will have to move, but in no discernible pattern.&#10;D) No one will have to move.

Accepted Answer

A correlation of -1.0 indicates a perfect negative relationship between two variables. In this context, it means that as one variable (height) increases, the other variable (weight) decreases in a perfectly predictable manner. Therefore, if students are already lined up by height, asking them to line up by weight would result in everyone except the student exactly in the middle (assuming an odd number of students for a clear middle) moving to mirror positions at the opposite end of the line, reflecting the perfect inverse relationship between their heights and weights.

Question 5

If one or both variables are interval or ratio level but skewed, a correlation coefficient can still be produced by computing:&#10;A) partial r.&#10;B) Kendall's tau or Spearman's rho&#10;C) Pearson's r&#10;D) Multiple R

Accepted Answer

When one or both variables are interval or ratio level but skewed, the best choice for producing a correlation coefficient is either Kendall's tau or Spearman's rho. This is because these methods do not rely on the assumption of normality, and are better suited for analyzing non-parametric data. Pearson's r, which is the traditional correlation coefficient, assumes normal distribution, making it unsuitable when dealing with skewed data. Partial r and Multiple R are not relevant in this context.

Question 6

A form of statistical analysis that uses correlation to identify redundancy in a newly constructed data collection instrument so that it can be eliminated or equivalent forms of the instrument can be developed is:

A) factor analysis
B) cluster analysis
C) Multiple R
D) factor rotation

Accepted Answer

Cluster analysis is a form of statistical analysis that uses correlation to form homogeneous groups of cases based upon their responses to several different questions. Factor analysis is another form of statistical analysis that reduces a large number of variables into a smaller number of components. Multiple R is a statistical measure of the correlation between two variables. Factor rotation is a technique used in factor analysis to simplify the interpretation of the data.

Question 7

Which correlation coefficient below suggests the strongest relationship between two variables?&#10;A) .65&#10;B) .05&#10;C) -.72&#10;D) .50

Accepted Answer

The correlation coefficient of -.72 suggests a strong negative relationship between the two variables. A correlation coefficient closer to -1 or 1 indicates a stronger relationship than one closer to 0.

Question 8

Correlation between variables can be displayed graphically using a:&#10;A) frequency polygon.&#10;B) stem and leaf plot&#10;C) scattergram.&#10;D) pie chart.

Accepted Answer

Correlation between variables can be displayed graphically using a scattergram where each point represents a pair of values for two variables. The correlation can be determined by the pattern of points on the graph. Frequency polygons, stem and leaf plots, and pie charts are not appropriate for displaying the correlation between variables.

Question 9

In a social work class, there is a perfect positive correlation (1.0) between height and weight. All 25 students are asked to line up by height, shortest to tallest. What will happen if they are then asked to line up by weight, lightest to heaviest?

A) About half of the students will move; others will stay in place.
B) Only the 13th student will stay in place; everyone else will move to the same position but in the opposite end of the line.
C) Everyone will have to move, but in no discernible pattern.
D) No one will have to move.

Accepted Answer

A perfect positive correlation (1.0) between height and weight means that as height increases, weight increases in a perfectly linear manner. Therefore, if students are lined up from shortest to tallest, they are also automatically lined up from lightest to heaviest, meaning no one will have to move when asked to line up by weight.

Question 10

Which pair of variables below are probably correlated, but the correlation is not a linear one?&#10;A) age and earned income for ages 16 to 90.&#10;B) automobile weight and gasoline mileage&#10;C) earned income and monthly house payment&#10;D) alcohol consumption and severity of marital problems

Accepted Answer

The relationship between age and earned income is likely to be non-linear because income tends to increase with age up to a certain point (as people progress in their careers) but then may decrease or plateau as people retire or reduce their working hours.

Question 11

If two variables reflect a perfect (1.0 or -1.0) correlation,&#10;A) the body of the graph of the correlation will contain a straight line.&#10;B) there will be no exception to the overall pattern of the relationship between variables.&#10;C) the two &#34;variables&#34; are probably just two different indicators of the same variable.&#10;D) all of the above

Accepted Answer

The answer of If two variables reflect a perfect (1.0...

Question 12

A correlation of .70 between two variables suggests that about percent of the variations in one variable is related to the variations in the other one.&#10;A) 1&#10;B) 70&#10;C) 49&#10;D) 100

Accepted Answer

The answer of A correlation of .70 between two variables...

Question 13

Correlation analyses are used for:&#10;A) construction of data collection instruments such as scales.&#10;B) describing the strength and direction of a relationship between variables.&#10;C) determining if a relationship between variables is statistically significant.&#10;D) all of the above

Accepted Answer

The answer of Correlation analyses are used for:&#10;A) construction of...

Question 14

A table that displays the bivariate correlations between several different pairs of variables is called a:&#10;A) scattergram.&#10;B) correlation matrix.&#10;C) step-down graph&#10;D) beta weight

Accepted Answer

The answer of A table that displays the bivariate correlations...

Question 15

Which pair of variables below reflect a strong linear correlation, but the correlation is probably explained at least partially by one or more confounding variables?&#10;A) education level and per capita income&#10;B) number of siblings and mother's education level&#10;C) soft drink consumption and drowning rates&#10;D) all of the above

Accepted Answer

The answer of Which pair of variables below reflect a...

Deck 9: Correlation Analyses