Question 1

The type of sampling in which each member of the population selected for the sample is returned to the population before the next member is selected is called _________
A)sampling without replacement
B)sampling with replacement
C)simple random sampling
D)systematic sampling

Accepted Answer

Sampling with replacement means that each member of the population can be selected more than once because after being selected, they are "replaced" back into the population before the next selection. This allows for the possibility of the same member being chosen multiple times.

Question 2

___________ is a set of elements taken from a larger population according to certain rules
A)sample
B)population
C)statistic
D)element

Accepted Answer

A sample is a subset of elements drawn from a larger population, typically selected for the purpose of conducting a study or analysis.

Question 3

Questionnaires can address events and characteristics taking place ______
A)in the past (retrospective questions)
B)in the present (current time questions)
C)in the future (prospective questions)
D)all of the above

Accepted Answer

Questionnaires can be designed to gather information about events or characteristics from the past, present, or anticipated in the future, making all the options correct.

Question 4

Which of the following terms best describes data that were originally collected at an earlier time by a different person for a different purpose
A)primary data
B)secondary data
C)experimental data
D)field notes

Accepted Answer

Secondary data refers to data that were collected by someone else for a different purpose but are being used by a researcher for a new study. This contrasts with primary data, which are collected firsthand by the researcher for the specific purpose of their study. Experimental data and field notes are types of primary data.

Question 5

Correlation refers to
A)the causal relationship between two variables
B)the association between two variables
C)the proportion of variance that two variables share
D)a statistical method that can only be used with a correlational research design

Accepted Answer

Correlation refers to the association or relationship between two variables, indicating how one variable may change as the other changes.

Question 6

If two variables are highly correlated, what do you know
A)that they always go together
B)that high values on one variable lead to high values on the other variable
C)that there are no other variables responsible for the relationship
D)that changes in one variable are accompanied by predictable changes in the other

Accepted Answer

Highly correlated variables indicate that changes in one variable are accompanied by predictable changes in the other, but it does not imply causation or exclude the influence of other variables.

Question 7

A researcher finds a correlation of 0.40 between personal income and the number of years of college completed. Based upon this finding he can conclude that
A)a person who attended four years of college will have an annual income of rs. 40,000
B)more years of education causes higher income
C)personal income is a positively skewed variable
D)more years of education are associated with higher income

Accepted Answer

The correlation of 0.40 indicates a positive relationship between the number of years of college completed and personal income, meaning as one increases, so does the other. However, correlation does not imply causation, nor does it provide specific income values or indicate the distribution shape of personal income.

Question 8

Which of the following would not allow you to calculate a correlation?
A)a negative relationship between x and y
B)a positive relationship between x and y
C)a curvilinear relationship between x and y
D)a linear relationship between x and y

Accepted Answer

Correlation measures the strength and direction of a linear relationship between two variables. A curvilinear relationship, where the relationship between x and y changes direction, does not meet the criteria for calculating a correlation coefficient, which assumes a linear relationship.

Question 9

Correlation relates the relative position of a score in one distribution to
A)the relative position of a score in another distribution
B)the mean of the z-scores from another distribution
C)the total variance of all scores in both distributions
D)the standard deviation of the z-scores for both distributions

Accepted Answer

Correlation measures the relationship between two variables, specifically how the position of a score in one distribution is related to its position in another distribution. This is why option A is correct, as it directly describes this relationship.

Question 10

If a positive correlation exists between height and weight, a person with above average height is expected to have above average weight
A) true
B) false
C) insufficient information to draw a conclusion
D) any of the above

Accepted Answer

A positive correlation between height and weight suggests that as one variable increases, the other also tends to increase. Therefore, if a person has an above-average height, they are expected to also have an above-average weight, based on the trend indicated by the positive correlation.

Question 11

Regression analysis:
A)measures the demand for a good
B)measures growth
C)establishes cause and effect
D)establishes a relationship between two variables

Accepted Answer

Regression analysis is primarily used to establish a relationship between two variables, where one variable is dependent on the other. It does not inherently measure demand, growth, or establish cause and effect without further context or analysis.

Question 12

In the equation of a straight line, Y = mX + c the term, m is the:
A)independent variable
B)intercept
C)dependent variable
D)slope

Accepted Answer

The term m in the equation Y = mX + c represents the slope of the line, which indicates how steep the line is.

Question 13

In the equation of a straight line, Y = mX + c , if c is equal to zero then:
A)the line of best fit passes through the origin
B)the line of best fit cuts the x axis to the right of the y axis
C)does not cross the x axis
D)the line of best fit cuts the x axis to the left of the y axis

Accepted Answer

When c = 0 in the equation Y = mX + c, the line passes through the origin (0,0), because substituting X = 0 gives Y = 0.

Question 14

In the equation of a straight line, Y = mX + c , if m is equal to ?2 then:
A)there is a positive relationship between the two variables
B)there is no relationship between the two variables
C)there is a negative relationship between the two variables
D)the relationship between the two variables is perfect

Accepted Answer

In the equation Y = mX + c, the coefficient m represents the slope of the line. A negative slope (m = -2) indicates that as X increases, Y decreases, which defines a negative relationship between the two variables.

Question 15

In the equation of a straight line, Y = mX + c , if m is equal to zero then when:
A)x increases y decreases
B)y increases x increases
C)x increases y increases
D)x increases y remains constant

Accepted Answer

When m (the slope) is equal to zero, the equation Y = mX + c simplifies to Y = c, indicating that Y is constant regardless of changes in X.

Question 16

The mathematical notation R2 is for:
A)the co-efficient of determination
B)the co-efficient of variation
C)spearman's co-efficient of rank correlation
D)pearson's co-efficient of correlation

Accepted Answer

R-squared, or R^2, is known as the coefficient of determination. It measures the proportion of the variance in the dependent variable that is predictable from the independent variable(s) in a regression model.

Question 17

If the slope of the regression line is calculated to be 2.5 and the intercept 16 then the value of Y when X is 4 is:
A)16
B)66.5
C)2.5
D)26

Accepted Answer

The value of Y can be calculated using the equation of the line, Y = mx + b, where m is the slope and b is the intercept. Substituting the given values, Y = 2.5*4 + 16 = 10 + 16 = 26.

Question 18

If Spearman's co-efficient of rank correlation is equal to one, then:
A)all the 'total variation' is 'explained' by the regression line
B)the rankings of the two variables partially agree
C)the rankings of the two variables is totally different
D)the rankings of the two variables totally agree

Accepted Answer

Spearman's coefficient of rank correlation being equal to one indicates a perfect positive correlation between the rankings of the two variables, meaning their rankings totally agree.

Quiz 4: Sampling, Correlation, and Regression Analysis

The type of sampling in which each member of the population selected for the sample is returned to the population before the next member is selected is called _________

___________ is a set of elements taken from a larger population according to certain rules

Questionnaires can address events and characteristics taking place ______

Which of the following terms best describes data that were originally collected at an earlier time by a different person for a different purpose

Correlation refers to

If two variables are highly correlated, what do you know

A researcher finds a correlation of 0.40 between personal income and the number of years of college completed. Based upon this finding he can conclude that

Which of the following would not allow you to calculate a correlation?

Correlation relates the relative position of a score in one distribution to

If a positive correlation exists between height and weight, a person with above average height is expected to have above average weight

Regression analysis:

In the equation of a straight line, Y = mX + c the term, m is the:

In the equation of a straight line, Y = mX + c , if c is equal to zero then:

In the equation of a straight line, Y = mX + c , if m is equal to ?2 then:

In the equation of a straight line, Y = mX + c , if m is equal to zero then when:

The mathematical notation R2 is for:

If the slope of the regression line is calculated to be 2.5 and the intercept 16 then the value of Y when X is 4 is:

If Spearman's co-efficient of rank correlation is equal to one, then: