Linear Regression: Correlation, Bivariate Regression; OLS Assumptions, Robust Standard Errors Flashcards

1
Q

Correlation

A

2 variables vary together: there can be positive correlation or negative correlation. Correlation is always between -1 and 1.

POSITIVE: (moves from bottom left to top right) DV increases as the IV also increases.

NEGATIVE: (moves from top left to bottom right) as the DV decreases the IV increases.

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2
Q

Perfect Correlation

A

r=1 means perfect correlation
r=-1 means imperfect correlation
r=0 means no correlation between variables

The closest to 0 the less relationship there is between variables

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3
Q

Covariance

A

Cov(X,Y) = Σ E((X – μ) E(Y – ν)) / n-1

X is a random variable
E(X) = μ is the expected value (the mean) of the random variable X and
E(Y) = ν is the expected value (the mean) of the random variable Y
n = the number of items in the data set.
Σ summation notation

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4
Q

Bivariate Regression

A

Finds the best fit for a line through data - the line of best fit is the one who minimizes the y distance from each observation to the line.

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5
Q

Correlation vs Regression

A

Correlation tells us how strongly associated two variables are;

Regression tells on average how much a one unit increases or decreases the predicted value of the variable.
Regression gives more precise information on the strength of a relationship

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6
Q

Vertical Deviations

A

Explain the DV (y) and why it is on the vertical axis, therefore vertical distance.

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7
Q

Ordinary Least Squares (OLS)

A
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8
Q

Coefficient

A
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9
Q

Hypothesis Testing for Regression

A
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10
Q

S.E. for Regression Root Mean

A
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11
Q

Null Hypothesis (H0)

A
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12
Q

Build t-value

A
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13
Q

Estimators

A
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14
Q

Estimators (Bias)

A
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15
Q

Estimators (Efficiency)

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16
Q

Estimators (Consistency)

A
17
Q

OLS Assumptions

A
  1. Linearity
  2. Mean Independence
  3. Homocedasticity
  4. Uncorrelated Distributions
  5. Normal Distributions
18
Q

Linearity (OLS)

A
19
Q

Mean Independence (OLS)

A
20
Q

Homocedasticity (OLS)

A
21
Q

Uncorrelated Distributions (OLS)

A
22
Q

Normal Distributions (OLS)

A
23
Q
A