Question 1

There is a positive correlation between two variables x and y. Which of the following statements is true?

Accepted Answer

A)  As x increases, y will increase 
B)  As x increases, y will decrease 
C)  As x increases, y will remain unchanged 
D)  We cannot say what happens as x increases 
A)  As x increases, y will increase 
B)  As x increases, y will decrease 
C)  As x increases, y will remain unchanged 
D)  We cannot say what happens as x increases A

Question 2

Which of the following options gives the best definition of correlation?

Accepted Answer

A)  An estimate of strength of a relationship between two variables 
B)  An estimate of the spread of values in a set of data 
C)  An estimate of skewness in a set of data 
D)  An estimate of causality between two variables 
A)  An estimate of strength of a relationship between two variables 
B)  An estimate of the spread of values in a set of data 
C)  An estimate of skewness in a set of data 
D)  An estimate of causality between two variables A

Question 3

Which of the following options is not a valid value for the correlation coefficient?

Accepted Answer

A)  -0.94 
B)  0 
C)  0.36 
D)  1.2 
A)  -0.94 
B)  0 
C)  0.36 
D)  1.2 D

Question 4

Correlation and regression are related statistical functions. Which option best describes this relationship?

Accepted Answer

A)  Regression is a measure of how well correlation explains the relationship between two variables 
B)  The correlation coefficient always lies on the regression line 
C)  Correlation can indicate how well the regression line 'fits' the data 
D)  The regression line can be calculated using values for the mean and the correlation coefficient 
A)  Regression is a measure of how well correlation explains the relationship between two variables 
B)  The correlation coefficient always lies on the regression line 
C)  Correlation can indicate how well the regression line 'fits' the data 
D)  The regression line can be calculated using values for the mean and the correlation coefficient

Question 5

Data from established manufacturing companies in Morocco shows that the number of years' experience a sales person has is correlated with their average yearly sales. The correlation coefficient ( r) is 0.62. Calculate, to 1 decimal place, the percentage of variation in sales that is accounted for by experience.

Accepted Answer

A)  62.0% 
B)  61.6% 
C)  45.3% 
D)  38.4% 
A)  62.0% 
B)  61.6% 
C)  45.3% 
D)  38.4%

Question 6

What term is used to describe differences in the value of an independent variable which are accounted for by the y on x regression line?

Accepted Answer

A)  Correlated differences 
B)  Explained differences 
C)  Unexplained differences 
D)  Regression differences 
A)  Correlated differences 
B)  Explained differences 
C)  Unexplained differences 
D)  Regression differences

Question 7

The analysis of two variables indicates a correlation with r = -0.85. Calculate, to 1 decimal place, the percentage of variation in the independent variable that is not accounted for by the dependent variable.

Accepted Answer

A)  85.0% 
B)  72.3% 
C)  56.3% 
D)  27.8% 
A)  85.0% 
B)  72.3% 
C)  56.3% 
D)  27.8%

Question 8

Which of the following statements is TRUE?

Accepted Answer

A)  Causality normally implies correlation 
B)  Correlation normally implies causality 
C)  There is never a relationship between causality and correlation 
D)  Correlation only occurs when there is causality 
A)  Causality normally implies correlation 
B)  Correlation normally implies causality 
C)  There is never a relationship between causality and correlation 
D)  Correlation only occurs when there is causality

Question 9

Which of the following statements about rank correlation is NOT true?

Accepted Answer

A)  Rank correlation is sometimes used to approximate product moment correlation 
B)  If one variable is non-numeric the rank correlation is most appropriate 
C)  Rank correlation can be used if variables can be placed in order (e.g. of size) 
D)  Rank correlation is usually considered to be more accurate than product moment correlation 
A)  Rank correlation is sometimes used to approximate product moment correlation 
B)  If one variable is non-numeric the rank correlation is most appropriate 
C)  Rank correlation can be used if variables can be placed in order (e.g. of size) 
D)  Rank correlation is usually considered to be more accurate than product moment correlation

Question 10

Which of the following relationships would you expect to be negatively correlated?

Accepted Answer

A)  Marketing budget and Sales revenue 
B)  Years of experience and Salary 
C)  Volume of raw materials purchased and Unit cost 
D)  Car speed and Stopping distance 
A)  Marketing budget and Sales revenue 
B)  Years of experience and Salary 
C)  Volume of raw materials purchased and Unit cost 
D)  Car speed and Stopping distance

Exam 14: Correlation Techniques

There is a positive correlation between two variables x and y. Which of the following statements is true?

Which of the following options gives the best definition of correlation?

Which of the following options is not a valid value for the correlation coefficient?

Correlation and regression are related statistical functions. Which option best describes this relationship?

What term is used to describe differences in the value of an independent variable which are accounted for by the y on x regression line?

The analysis of two variables indicates a correlation with r = -0.85. Calculate, to 1 decimal place, the percentage of variation in the independent variable that is not accounted for by the dependent variable.

Which of the following statements is TRUE?

Which of the following statements about rank correlation is NOT true?

Which of the following relationships would you expect to be negatively correlated?

Introduction to Business Mathematics and Statistics

Sampling and Data Collection

Data and Their Accuracy

Frequency Distributions and Charts

General Charts and Graphs

Arithmetic Mean

Median

Mode and Other Measures of Location

Measures of Dispersion and Skewness

Standard Deviation

Quantiles and the Quartile Deviation

Linear Functions and Graphs

Regression Techniques

Time Series Model

Time Series Trend

Seasonal Variation and Forecasting

Index Relatives

Composite Index Numbers

Special Published Indices

Interest and Depreciation

Present Value and Investment Appraisal

Annuities

Functions and Graphs

Linear Equations

Quadratic and Cubic Equations

Differentiation and Integration

Cost, Revenue and Profit Functions

Set Theory and Enumeration

Introduction to Probability

Conditional Probability and Expectation

Combinations and Permutations

Binomial and Poisson Distributions

Normal Distribution

Linear Inequalities

Matrices

Inventory Control

Network Planning and Analysis

Filters