Lecture 7 Flashcards

1
Q

What will we need to build regression models with multiple inputs?

A

linear algebra

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2
Q

What is r?

A

the correlation coefficient

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3
Q

What does r measure?

A

the strength of the linear association of two variables, x and y

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4
Q

What is the intuition behind r?

A

it measures how tightly clustered a scatter plot is around the straight line

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5
Q

What is the range for r?

A

between -1 and 1

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6
Q

What can we tell about a scatter plot if r is negative?

A

it has a negative association

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7
Q

What can we tell about a scatter plot if r is positive?

A

it has a positive association

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8
Q

What happens as r gets closer to ± 1?

A

the plot has a stronger correlation

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9
Q

How is the correlation coefficient, r, defined?

A

the average of the product of x and y, when both are in standard units

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10
Q

What is x_i in standard units?

A

x_i - xbar / σ_x

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11
Q

How do we express w_1* when using squared loss?

A

in terms of r; w_1* = (r) * (σ_y) / (σ_x)

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12
Q

What is the datasaurus dozen?

A

a collection of graphs that have the same mean, correlation, SD, but have significantly different visuals

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13
Q

What are the units of the slope?

A

units of y per units of x

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14
Q

What happens to our slope as the y values get more spread out?

A

σ_y increases and the slope gets steeper

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15
Q

What happens to our slope as the x values get more spread out?

A

σ_x increases and the slope gets shallower

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