Bivariate Data Flashcards

1
Q

Deductive the third variable problem.

A

There could be a common factor/process feeding into the 2 observed variables.

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2
Q

Describe concordant pairs of variables.

A

As X increases, Y increases.

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3
Q

Describe discordant pairs of variables.

A

As X increases, Y decreases.

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4
Q

What fire Goodman-Krystal gamma actually measure?

A

The number of concordant and discordant pairs.

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5
Q

Why is it so key to check the scatter plot when analysing covariance?

A

Covariance only detects straights line relationships, so you must check if any alternative relationships may be there.

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6
Q

What are the problems with covariance being affected by scale?

A

Comparisons between studies are very hard and evaluation of significance is very hard.

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7
Q

The distribution of Pearson’s r is (normal/skewed).

A

Skewed.

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8
Q

The distribution of Fischer’s transform is (symmetric/asymmetric).

A

Symmetric.

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9
Q

What is r^2?

A

The coefficient of determination.

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10
Q

What does r^2 convey?

A

The proportion of variance that one variable explains another.

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11
Q

How is Pearson’s r reported?

A

r(df) = x.xx, p = 0, r^2 = 0.xx

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12
Q

What is the main purpose of Fischer’s transformation?

A

To get meaningful confidence intervals.

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13
Q

In very brief terms, what is variance?

A

Distance squared.

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14
Q

What is correlation most effective for?

A

Exploration and description.

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15
Q

What is regression most effective for?

A

Explanation and prediction.

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16
Q

What is the consequence of regression assuming iid distributions of depends variables?

A

Not all error deviations are the same, and they can form a pattern, so we must look at a plot of the residuals.

17
Q

Give 2 situations when residuals show that regression is not appropriate?

A

When they do not lend themselves to a straight line of best fit and when Devil’s triangle occurs.

18
Q

What is Devil’s triangle?

A

As X increases, the variability of Y increases.