MGMT 650 UNIT 4 QUIZ: CORRELATION
AND REGRESSION CONCEPTS ACTUAL
EXAM PAPER 2026 QUESTIONS WITH
ANSWERS GRADED A+
◍ What's the different between n − 1 for sample data and N for population
data?.
Answer: - Using n −1 for sample variance corrects for the bias that occurs
because we’re estimating the population mean from a limited sample, not
entire population.- acknowledging limitation and compensating for i-
estimating the mean from the sample reduces variability, and n − 1 corrects
this downward bias--> making your estimate more accurate and less biased
towards the small sample
◍ Covariance for POPULATION DATA.
Answer: σₓᵧ
◍ On an international exam, students are asked to respond to a variety of
background questions. For the 41 nations that participated in the exam, the
correlation between the percentage of items answered in the background
questionnaire (used as a proxy for student task persistence) and mean score
on the exam was 0.731. Does this suggest there is a linear relation between
student task persistence and achievement score? Write a sentence that
explains what this result might mean.LOADIN
G. .. Click the icon to view the critical values table.Does this suggest there is
a linear relation between student task persistence and achievement score?
Choose the best response below.
A. No, since |0.731| is less than the critical value for 30.
B. No, since |0.731| is greater than the critical value for 30.
, C. Yes, since |0.731| is greater than the critical value for 30.
D. Yes, since |0.731| is less than the critical value for 30.What does this
result mean?
A. There is no linear relation between countries in which students answered
a greater percentage of items in the background questionnaire and higher
mean scores on the exam.
B. Countries in which students answered a lesser percentage of items in the
background questionnaire tended to have higher mean scores on the exam.
C. Countries in which students answered a greater percentage of items in the
background questionnaire tended to have higher mean scores on the exam.
D. Countries in which students cheated on the exam also cheated on the
items in the background questionnaire..
Answer: Yes, since |0.731| is greater than the critical value for 30.Countries
in which students answered a greater percentage of items in the background
questionnaire tended to have higher mean scores on the exam.
◍ What does it mean if r=0?.
Answer: No linear relationship exists between the variables.
◍ Scales of Measurement: Ratio scale.
Answer: the data have the properties of interval data, and the ratio of two
values is meaningful.EX:FINANCIAL FIGURES:- ratio scale- meaningful
zero point (no sales)- interval between figures is consistent- Company A
$200,000 = Revenue has twice as much as Company B's $100,000 Revenue
◍ Prior and Posterior Probabilities.
Answer: - begin probability analysis with initial or prior probabilities. -
Then, from a sample, special report, or a product test we obtain some
additional information. - Given this information, we calculate revised or
posterior probabilities. - Bayes' theorem provides the means for revising the
prior probabilities.
◍ Correlation Coefficient.
Answer: - Correlation is a measure of linear association and not necessarily
causation.- Just because two variables are highly correlated, it does not
, mean that one variable is the cause of the other. UNIT FREE MEASURE
◍ Will the following variables have positive correlation, negative correlation,
or no correlation?outside temperature and the number of people wearing
coats.
Answer: Negative
◍ An engineer wanted to determine how the weight of a car affects gas
mileage. The following data represent the weight of various cars and their
gas mileage. Complete parts (a) through (d).(a) Determine which variable is
the likely explanatory variable and which is the likely response variable.a.
The explanatory variable is the miles per gallon and the response variable is
the weight.b. The explanatory variable is the weight and the response
variable is the miles per gallon..
Answer: a) The explanatory variable is the weight and the response variable
is the miles per gallon.b) -.880c) Because the correlation coefficient is
negative and the absolute value of the correlation coefficient, . 880, is
greater than the critical value for this data set, . 878, a negative linear
relation exists between the weight of a car and its miles per gallon
◍ Explain what each point on the least-squares regression line represents..
Answer: Each point on the least-squares regression line represents the
predicted y-value at the corresponding value of x
◍ "Maximum".
Answer: (Q3 + 1.5*IQR)
◍ Counting Rule for Multiple-Step Experiments.
Answer: - A multiple-step experiment can be described as a sequence of k
steps with n1 possible outcomes on the first step, n2 possible outcomes on
the second step, and so on. (n1,n2,n3,...,nk) - As an example, consider the
random experiment of tossing two coins, one at a time. The first tossed coin
has n1 = 2 outcomes, and the second tossed coin has also n2 = 2 outcomes.
Thus, we have: 1st toss 2nd toss = 2 2 = 4 experimental outcomes
◍ (a) Scatter diagram II
AND REGRESSION CONCEPTS ACTUAL
EXAM PAPER 2026 QUESTIONS WITH
ANSWERS GRADED A+
◍ What's the different between n − 1 for sample data and N for population
data?.
Answer: - Using n −1 for sample variance corrects for the bias that occurs
because we’re estimating the population mean from a limited sample, not
entire population.- acknowledging limitation and compensating for i-
estimating the mean from the sample reduces variability, and n − 1 corrects
this downward bias--> making your estimate more accurate and less biased
towards the small sample
◍ Covariance for POPULATION DATA.
Answer: σₓᵧ
◍ On an international exam, students are asked to respond to a variety of
background questions. For the 41 nations that participated in the exam, the
correlation between the percentage of items answered in the background
questionnaire (used as a proxy for student task persistence) and mean score
on the exam was 0.731. Does this suggest there is a linear relation between
student task persistence and achievement score? Write a sentence that
explains what this result might mean.LOADIN
G. .. Click the icon to view the critical values table.Does this suggest there is
a linear relation between student task persistence and achievement score?
Choose the best response below.
A. No, since |0.731| is less than the critical value for 30.
B. No, since |0.731| is greater than the critical value for 30.
, C. Yes, since |0.731| is greater than the critical value for 30.
D. Yes, since |0.731| is less than the critical value for 30.What does this
result mean?
A. There is no linear relation between countries in which students answered
a greater percentage of items in the background questionnaire and higher
mean scores on the exam.
B. Countries in which students answered a lesser percentage of items in the
background questionnaire tended to have higher mean scores on the exam.
C. Countries in which students answered a greater percentage of items in the
background questionnaire tended to have higher mean scores on the exam.
D. Countries in which students cheated on the exam also cheated on the
items in the background questionnaire..
Answer: Yes, since |0.731| is greater than the critical value for 30.Countries
in which students answered a greater percentage of items in the background
questionnaire tended to have higher mean scores on the exam.
◍ What does it mean if r=0?.
Answer: No linear relationship exists between the variables.
◍ Scales of Measurement: Ratio scale.
Answer: the data have the properties of interval data, and the ratio of two
values is meaningful.EX:FINANCIAL FIGURES:- ratio scale- meaningful
zero point (no sales)- interval between figures is consistent- Company A
$200,000 = Revenue has twice as much as Company B's $100,000 Revenue
◍ Prior and Posterior Probabilities.
Answer: - begin probability analysis with initial or prior probabilities. -
Then, from a sample, special report, or a product test we obtain some
additional information. - Given this information, we calculate revised or
posterior probabilities. - Bayes' theorem provides the means for revising the
prior probabilities.
◍ Correlation Coefficient.
Answer: - Correlation is a measure of linear association and not necessarily
causation.- Just because two variables are highly correlated, it does not
, mean that one variable is the cause of the other. UNIT FREE MEASURE
◍ Will the following variables have positive correlation, negative correlation,
or no correlation?outside temperature and the number of people wearing
coats.
Answer: Negative
◍ An engineer wanted to determine how the weight of a car affects gas
mileage. The following data represent the weight of various cars and their
gas mileage. Complete parts (a) through (d).(a) Determine which variable is
the likely explanatory variable and which is the likely response variable.a.
The explanatory variable is the miles per gallon and the response variable is
the weight.b. The explanatory variable is the weight and the response
variable is the miles per gallon..
Answer: a) The explanatory variable is the weight and the response variable
is the miles per gallon.b) -.880c) Because the correlation coefficient is
negative and the absolute value of the correlation coefficient, . 880, is
greater than the critical value for this data set, . 878, a negative linear
relation exists between the weight of a car and its miles per gallon
◍ Explain what each point on the least-squares regression line represents..
Answer: Each point on the least-squares regression line represents the
predicted y-value at the corresponding value of x
◍ "Maximum".
Answer: (Q3 + 1.5*IQR)
◍ Counting Rule for Multiple-Step Experiments.
Answer: - A multiple-step experiment can be described as a sequence of k
steps with n1 possible outcomes on the first step, n2 possible outcomes on
the second step, and so on. (n1,n2,n3,...,nk) - As an example, consider the
random experiment of tossing two coins, one at a time. The first tossed coin
has n1 = 2 outcomes, and the second tossed coin has also n2 = 2 outcomes.
Thus, we have: 1st toss 2nd toss = 2 2 = 4 experimental outcomes
◍ (a) Scatter diagram II
