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Statistics for Machine Learning > 6. Regression Analysis & Correlation > Flashcards

6. Regression Analysis & Correlation Flashcards

Principles of Regression

1
Q

What is regression analysis?

A

A statistical method for modeling relationships between variables.

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2
Q

What is the dependent variable in regression?

A

The variable being predicted or explained.

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3
Q

What is the independent variable in regression?

A

The variable used to predict the dependent variable.

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4
Q

What is simple linear regression?

A

A model that explains the relationship between two variables using a straight line.

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5
Q

What is multiple linear regression?

A

A model that explains the relationship between a dependent variable and multiple independent variables.

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6
Q

What does R-squared represent?

A

The proportion of variance in the dependent variable explained by the independent variables.

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7
Q

What is multicollinearity?

A

A situation where independent variables are highly correlated, leading to unreliable estimates.

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8
Q

What is logistic regression used for?

A

Predicting categorical outcomes (e.g., binary classification).

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9
Q

What is heteroscedasticity?

A

When the variance of residuals is not constant across all levels of an independent variable.

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10
Q

What is autocorrelation?

A

When residuals are correlated with each other over time, violating independence assumptions.

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11
Q

What is regression analysis?

A

A statistical method for modeling relationships between variables.

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12
Q

What is the dependent variable in regression?

A

The variable being predicted or explained.

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13
Q

What is the independent variable in regression?

A

The variable used to predict the dependent variable.

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14
Q

What is simple linear regression?

A

A model that explains the relationship between two variables using a straight line.

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15
Q

What is multiple linear regression?

A

A model that explains the relationship between a dependent variable and multiple independent variables.

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16
Q

What does R-squared represent?

A

The proportion of variance in the dependent variable explained by the independent variables.

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17
Q

What is multicollinearity?

A

A situation where independent variables are highly correlated, leading to unreliable estimates.

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18
Q

What is logistic regression used for?

A

Predicting categorical outcomes (e.g., binary classification).

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19
Q

What is heteroscedasticity?

A

When the variance of residuals is not constant across all levels of an independent variable.

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20
Q

What is autocorrelation?

A

When residuals are correlated with each other over time, violating independence assumptions.

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21
Q

What is regression analysis?

A

A statistical method for modeling relationships between variables.

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22
Q

What is the dependent variable in regression?

A

The variable being predicted or explained.

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23
Q

What is the independent variable in regression?

A

The variable used to predict the dependent variable.

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24
Q

What is simple linear regression?

A

A model that explains the relationship between two variables using a straight line.

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25
What is multiple linear regression?
A model that explains the relationship between a dependent variable and multiple independent variables.
26
What does R-squared represent?
The proportion of variance in the dependent variable explained by the independent variables.
27
What is multicollinearity?
A situation where independent variables are highly correlated, leading to unreliable estimates.
28
What is logistic regression used for?
Predicting categorical outcomes (e.g., binary classification).
29
What is heteroscedasticity?
When the variance of residuals is not constant across all levels of an independent variable.
30
What is autocorrelation?
When residuals are correlated with each other over time, violating independence assumptions.
31
What is regression analysis?
A statistical method for modeling relationships between variables.
32
What is the dependent variable in regression?
The variable being predicted or explained.
33
What is the independent variable in regression?
The variable used to predict the dependent variable.
34
What is simple linear regression?
A model that explains the relationship between two variables using a straight line.
35
What is multiple linear regression?
A model that explains the relationship between a dependent variable and multiple independent variables.
36
What does R-squared represent?
The proportion of variance in the dependent variable explained by the independent variables.
37
What is multicollinearity?
A situation where independent variables are highly correlated, leading to unreliable estimates.
38
What is logistic regression used for?
Predicting categorical outcomes (e.g., binary classification).
39
What is heteroscedasticity?
When the variance of residuals is not constant across all levels of an independent variable.
40
What is autocorrelation?
When residuals are correlated with each other over time, violating independence assumptions.
41
What is regression analysis?
A statistical method for modeling relationships between variables.
42
What is the dependent variable in regression?
The variable being predicted or explained.
43
What is the independent variable in regression?
The variable used to predict the dependent variable.
44
What is simple linear regression?
A model that explains the relationship between two variables using a straight line.
45
What is multiple linear regression?
A model that explains the relationship between a dependent variable and multiple independent variables.
46
What does R-squared represent?
The proportion of variance in the dependent variable explained by the independent variables.
47
What is multicollinearity?
A situation where independent variables are highly correlated, leading to unreliable estimates.
48
What is logistic regression used for?
Predicting categorical outcomes (e.g., binary classification).
49
What is heteroscedasticity?
When the variance of residuals is not constant across all levels of an independent variable.
50
What is autocorrelation?
When residuals are correlated with each other over time, violating independence assumptions.
51
What is regression analysis?
A statistical method for modeling relationships between variables.
52
What is the dependent variable in regression?
The variable being predicted or explained.
53
What is the independent variable in regression?
The variable used to predict the dependent variable.
54
What is simple linear regression?
A model that explains the relationship between two variables using a straight line.
55
What is multiple linear regression?
A model that explains the relationship between a dependent variable and multiple independent variables.
56
What does R-squared represent?
The proportion of variance in the dependent variable explained by the independent variables.
57
What is multicollinearity?
A situation where independent variables are highly correlated, leading to unreliable estimates.
58
What is logistic regression used for?
Predicting categorical outcomes (e.g., binary classification).
59
What is heteroscedasticity?
When the variance of residuals is not constant across all levels of an independent variable.
60
What is autocorrelation?
When residuals are correlated with each other over time, violating independence assumptions.
61
What is regression analysis?
A statistical method for modeling relationships between variables.
62
What is the dependent variable in regression?
The variable being predicted or explained.
63
What is the independent variable in regression?
The variable used to predict the dependent variable.
64
What is simple linear regression?
A model that explains the relationship between two variables using a straight line.
65
What is multiple linear regression?
A model that explains the relationship between a dependent variable and multiple independent variables.
66
What does R-squared represent?
The proportion of variance in the dependent variable explained by the independent variables.
67
What is multicollinearity?
A situation where independent variables are highly correlated, leading to unreliable estimates.
68
What is logistic regression used for?
Predicting categorical outcomes (e.g., binary classification).
69
What is heteroscedasticity?
When the variance of residuals is not constant across all levels of an independent variable.
70
What is autocorrelation?
When residuals are correlated with each other over time, violating independence assumptions.
71
What is regression analysis?
A statistical method for modeling relationships between variables.
72
What is the dependent variable in regression?
The variable being predicted or explained.
73
What is the independent variable in regression?
The variable used to predict the dependent variable.
74
What is simple linear regression?
A model that explains the relationship between two variables using a straight line.
75
What is multiple linear regression?
A model that explains the relationship between a dependent variable and multiple independent variables.
76
What does R-squared represent?
The proportion of variance in the dependent variable explained by the independent variables.
77
What is multicollinearity?
A situation where independent variables are highly correlated, leading to unreliable estimates.
78
What is logistic regression used for?
Predicting categorical outcomes (e.g., binary classification).
79
What is heteroscedasticity?
When the variance of residuals is not constant across all levels of an independent variable.
80
What is autocorrelation?
When residuals are correlated with each other over time, violating independence assumptions.
81
What is regression analysis?
A statistical method for modeling relationships between variables.
82
What is the dependent variable in regression?
The variable being predicted or explained.
83
What is the independent variable in regression?
The variable used to predict the dependent variable.
84
What is simple linear regression?
A model that explains the relationship between two variables using a straight line.
85
What is multiple linear regression?
A model that explains the relationship between a dependent variable and multiple independent variables.
86
What does R-squared represent?
The proportion of variance in the dependent variable explained by the independent variables.
87
What is multicollinearity?
A situation where independent variables are highly correlated, leading to unreliable estimates.
88
What is logistic regression used for?
Predicting categorical outcomes (e.g., binary classification).
89
What is heteroscedasticity?
When the variance of residuals is not constant across all levels of an independent variable.
90
What is autocorrelation?
When residuals are correlated with each other over time, violating independence assumptions.
91
What is regression analysis?
A statistical method for modeling relationships between variables.
92
What is the dependent variable in regression?
The variable being predicted or explained.
93
What is the independent variable in regression?
The variable used to predict the dependent variable.
94
What is simple linear regression?
A model that explains the relationship between two variables using a straight line.
95
What is multiple linear regression?
A model that explains the relationship between a dependent variable and multiple independent variables.
96
What does R-squared represent?
The proportion of variance in the dependent variable explained by the independent variables.
97
What is multicollinearity?
A situation where independent variables are highly correlated, leading to unreliable estimates.
98
What is logistic regression used for?
Predicting categorical outcomes (e.g., binary classification).
99
What is heteroscedasticity?
When the variance of residuals is not constant across all levels of an independent variable.
100
What is autocorrelation?
When residuals are correlated with each other over time, violating independence assumptions.

Statistics for Machine Learning (9 decks)

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