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Question 1

Response Variable.

Answer 1

dependent variable

Question 2

Unexplained Responses.

Answer 2

error

Question 3

Explanatory Variable.

Answer 3

Independent Variable

Question 4

Line used to represent the relationship between response and explanatory
variable

Answer 4

. Linear Relationship

Question 5

A mathematical representation (or mathematical model) of observed data.

Answer 5

Statistical Model

Question 6

What is the purpose of a simple linear regression model?

Answer 6

C) To predict values of an output variable based on an input variable

Question 7

What is the definition of the slope in linear regression?

Answer 7

D) The change in the response variable for a unit change in the explanatory variable

Question 8

What effect does adding an additional explanatory variable to a linear regression have on the
slope of the original variable?

Answer 8

D) It increases the slope of the original variable

Question 9

If the slope of a linear regression is 2, what does it mean?

Answer 9

For a unit increase in the explanatory variable, the response variable increases by 2

Question 10

If the slope of a linear regression is negative, what can we say about the relationship between
the explanatory and response variables?

Answer 10

B) There is a negative relationship

Question 11

If two variables have a positive association, the slope is

Answer 11

positive

Question 12

If two variables have a negative association, the slope is

Answer 12

negative

Question 13

if two variables are not associated, then the slope is

Answer 13

0 (and the line is horizontal)

Question 14

The point where the line or curve crosses the axis of the graph.

Answer 14

Intercept

Question 15

a measure of its steepness.

Answer 15

Slope

Question 16

The best way to find violations and errors is to examine the plot themselves.

t orr f

Answer 16

true

Question 17

The regression line can be plotted anywhere on the graph even at points when it
doesn’t make sense.
true or false

Answer 17

false

Question 18

Violations against normality mainly revolves around errors when it comes to the
normal distribution of plotted data.

Answer 18

true

Question 19

You can transform the formula of some variables in the software you are using in
case that your data is not linear.

Answer 19

true

Question 20

An outlier does not affect the appearance of the graph at all.

Answer 20

false

Question 21

A term given to a data that lies outside the normal expected data pattern.

Answer 21

Outlier

Question 22

The type of error which refers to the rejection of a null hypothesis that is actually true in
the population.

Answer 22

type 1 error

Question 23

The violation concerned with the independent variables and samples used.

Answer 23

b. Violation against Independence

Question 24

The concept which assures that the values of the samples received doesn’t affect other
samples.

Answer 24

independence

Question 25

Graphs that present the relationship between two variables of data using a two-dimensional plane/cartesian coordinate system to represent the data.

Answer 25

Scatterplot

Question 26

The state of data wherein the samples collected follow the normal distribution pattern when plotted.

Answer 26

Normality

Question 27

The concept which refers to the inclination of two or more variables to change at the same rate, which when plotted, shows a straight line.

Answer 27

Linearity

Question 28

The probability that the null hypothesis will be rejected.

Answer 28

Power

Question 29

The sample size of a hypothesis test depends on these two factors.

Answer 29

Power and Type 1 error.Power and Type 1 error.

Question 30

1. It is a crucial step in identifying and solving the main problem of the study.

Answer 30

Describing the Data

Question 31

a graph that presents the relationship between two variables of the data.

Answer 31

C. Scatter Plot

Question 32

used by scatter plots to represent the data.

Answer 32

Two-Dimensional Plane

Question 33

4. Scatter plots are used as a _________________.

Answer 33

Graphical Summary

Question 34

What can be seen on the horizontal axis of a scatter plot?

Answer 34

Independent Variable

Question 35

What can be seen on the vertical axis of a scatter plot?

Answer 35

B. Dependent Variable

Question 36

is a measure between two variables of how much one variable changes when the other variable changes.

Answer 36

Association

Question 37

8. If one variable increases as the other variable increases, the association is ___________.

Answer 37

Positive

Question 38

9. If one variable decreases as the other variable increases, the association is

Answer 38

negative

Question 39

10. What do you call the point in a scatter plot?

Answer 39

observation

Question 40

is a statistical measure that describes the relationship between two variables.

Answer 40

A. Correlation

Question 41

12. Correlation is used as a ___________.

Answer 41

C. Numerical Summary

Question 42

This is the numerical value of correlation that indicates a perfectly positive relationship between two variables.

Answer 42

A. +1

Question 43

14. This is the numerical value of correlation that indicates no relationship between two variables.

Answer 43

B. 0

Question 44

15. This is the numerical value of correlation that indicates a perfectly negative relationship between two variables.

Answer 44

C. -1

Question 45

True or False: The regression formula represents the relationship between the dependent and independent variables.

Answer 45

True

Question 46

True or False: The prediction equation is used to estimate the value of the dependent variable based on the values of the independent variables.

Answer 46

True

Question 47

True or False: Heteroscedasticity is a violation of the assumption that the variance of the error terms is constant across all levels of the independent variables.

Answer 47

True

Question 48

True or False: In a regression model, the coefficients represent the average change in the dependent variable for a one-unit change in the independent variable, holding other variables constant.

Answer 48

True

Question 49

True or False: The Ordinary Least Squares (OLS) method is used to estimate the coefficients in a linear regression model.

Answer 49

True

Question 50

True or False: If heteroscedasticity is present in a regression model, the standard errors of the coefficients can be biased.

Answer 50

True

Question 51

True or False: Transforming variables (e.g., taking the logarithm) is a common technique for addressing heteroscedasticity.

Answer 51

True

Question 52

True or False: Weighted Least Squares (WLS) is a regression technique that can be used to correct for heteroscedasticity.

Answer 52

True

Question 53

True or False: A scatter plot of residuals against predicted values can be used to visually detect heteroscedasticity.

Answer 53

True

Question 54

10. True or False: The Breusch-Pagan test is a statistical test used to formally detect heteroscedasticity.

Answer 54

True

Question 55

True or False: Heteroscedasticity always leads to biased coefficient estimates in a regression model.

Answer 55

False

Question 56

True or False: If heteroscedasticity is detected, it is always necessary to take corrective action before interpreting the regression results.

Answer 56

False

Question 57

True or False: Robust standard errors are used to correct the standard errors in cases of heteroscedasticity.

Answer 57

True

Question 58

True or False: In some cases, heteroscedasticity may not significantly affect the validity of the regression results, especially when the sample size is very large.

Answer 58

True

Question 59

True or False: The Goldfeld-Quandt test is a statistical test used to formally detect heteroscedasticity.

Answer 59

True