g3 Flashcards

1
Q

Response Variable.

A

dependent variable

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2
Q

Unexplained Responses.

A

error

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3
Q

Explanatory Variable.

A

Independent Variable

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4
Q

Line used to represent the relationship between response and explanatory
variable

A

. Linear Relationship

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5
Q

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

A

Statistical Model

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6
Q

What is the purpose of a simple linear regression model?

A

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

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7
Q

What is the definition of the slope in linear regression?

A

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

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8
Q

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

A

D) It increases the slope of the original variable

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9
Q

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

A

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

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10
Q

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

A

B) There is a negative relationship

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11
Q

If two variables have a positive association, the slope is

A

positive

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12
Q

If two variables have a negative association, the slope is

A

negative

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13
Q

if two variables are not associated, then the slope is

A

0 (and the line is horizontal)

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14
Q

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

A

Intercept

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15
Q

a measure of its steepness.

A

Slope

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16
Q

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

t orr f

A

true

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17
Q

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

A

false

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18
Q

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

A

true

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19
Q

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

A

true

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20
Q

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

A

false

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21
Q

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

A

Outlier

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22
Q

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

A

type 1 error

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23
Q

The violation concerned with the independent variables and samples used.

A

b. Violation against Independence

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24
Q

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

A

independence

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25
Q

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

A

Scatterplot

26
Q

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

A

Normality

27
Q

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.

A

Linearity

28
Q

The probability that the null hypothesis will be rejected.

A

Power

29
Q

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

A

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

30
Q
  1. It is a crucial step in identifying and solving the main problem of the study.
A

Describing the Data

31
Q

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

A

C. Scatter Plot

32
Q

used by scatter plots to represent the data.

A

Two-Dimensional Plane

33
Q
  1. Scatter plots are used as a _________________.
A

Graphical Summary

34
Q

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

A

Independent Variable

35
Q

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

A

B. Dependent Variable

36
Q

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

A

Association

37
Q
  1. If one variable increases as the other variable increases, the association is ___________.
A

Positive

38
Q
  1. If one variable decreases as the other variable increases, the association is
A

negative

39
Q
  1. What do you call the point in a scatter plot?
A

observation

40
Q

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

A

A. Correlation

41
Q
  1. Correlation is used as a ___________.
A

C. Numerical Summary

42
Q

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

A

A. +1

43
Q
  1. This is the numerical value of correlation that indicates no relationship between two
    variables.
A

B. 0

44
Q
  1. This is the numerical value of correlation that indicates a perfectly negative relationship
    between two variables.
A

C. -1

45
Q

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

A

True

46
Q

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

A

True

47
Q

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.

A

True

48
Q

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.

A

True

49
Q

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

A

True

50
Q

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

A

True

51
Q

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

A

True

52
Q

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

A

True

53
Q

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

A

True

54
Q
  1. True or False: The Breusch-Pagan test is a statistical test used to formally detect
    heteroscedasticity.
A

True

55
Q

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

A

False

56
Q

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

A

False

57
Q

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

A

True

58
Q

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.

A

True

59
Q

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

A

True

60
Q
A