3 - Correlation & Regression Flashcards

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1
Q

List Pearson’s rule of thumb for effect sizes for r.

A

Small: .1 < r < .3 or -.1 > r > -.3
Medium: .3 < r .5 or -.3 > r >.5
Large: .5 < r < .7 or -.5 > r > -.7

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2
Q

What is the difference between Variability vs. Covariability

A

Variability: how much a given variable varies from
observation to observation

Covariability: how much two variables vary together

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3
Q

How is Sum of Squares calculated (variability)? How is Sum of Products calculated (covariability)?

A

SSx = Sum (Observed score x - Mean scores x) squared

SP = Sum (Observed score x - Mean scores x) (Observed score y - Mean scores y).

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4
Q

How is Pearson’s r calculated?

A

r = SP / SqrRoot (SSxSSy)

i.e. Covariability of X and Y / Variability of X and Y Separately.

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5
Q

What is regression toward the mean?

A

Extreme scores usually followed by a value closer to the average.

Extreme scores after due to chance, therefore, following score tends to be followed by less extreme score…

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6
Q

For correlation, what are the degrees of freedom (df)?

A

DF = n - 2.

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7
Q

How does Spearman’s correlation coefficient use rank order scores?

A

Deals with outliers & non-linear data

By converting ranks, i.e. 3, 2, 1… All values close to each other.

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8
Q

What is Cronbach’s Alpha?

A
  • A measure of reliability.
  • Reqs at least 3 items.
  • Ranges 0 to 1… where 1 = 100% reliable.

Influenced by number of items; increasing numbers can produce high reliability.

Rule of Thumb… 0.6 - 0.7 = questionable.

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9
Q

What is the regression formula & what are the error assumptions?

A

Y = a + bX + e

a is intercept.
b is slope
e is error, residuals; independent, normally distributed, & homoscedastic (equal error variance).

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10
Q

What is the least squares parameter estimates?

A

Regression prediction that minimises the error.

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11
Q

What is a standardised regression coefficient?

A

When X and Y scores are transformed into z-scores, aka Beta.

B/w -1 - 1.

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