Week 3 Flashcards

1
Q

What is variability in statistics?

A

A measure of the differences between scores in a distribution, it identifies how clustered or spread out scores are.
Scores/distributions with little variability are good for inferential statistics.

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2
Q

What is the range?

A

The range is the differences between the minimum score and the maximum score.
For discrete variables, range = Xmax - Xmin.
For continuous variables, range = URL for Xmax - LRL for Xmin.
The problem with the range is it’s susceptibility to extreme scores.

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3
Q

What are the three measures of variability?

A
  1. Range
  2. Standard deviation
  3. Variance
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4
Q

What is the deviation?

A

The distance from the mean for each individual score.

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5
Q

What is the variance?

A

The mean of the squared deviations.

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6
Q

What is the standard deviation?

A

The square root of the variance, it gives you the average distance from the mean.

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7
Q

What does SS represent?

A

Sum of squared scores.

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8
Q

What is the definitional formula for SS? what are it’s weaknesses?

A

SS = ∑(X - μ)².

Can become difficult to use or inaccurate with decimals and fractions.

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9
Q

What is the computational formula for SS?

A

SS = ∑X² - ((∑X)²/N).

This is better for dealing with decimals and fractions.

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10
Q

What does σ represent?

A

Population standard deviation.

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11
Q

What does σ² represent?

A

Population variance.

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12
Q

When is a sample statistic considered biased?

A

When it consistently overestimates or underestimates a corresponding population parameter.

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13
Q

What adjustments need to be made to the definitional and computation formulas for SS when used for samples?

A

N changes to n.

μ changes to M.

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14
Q

What does s represent?

A

Sample standard deviation (sometimes called the estimated population standard deviation).

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15
Q

What does s² represent?

A
Sample variance (sometimes called the estimated population variance). 
*VERY IMPORTANT* 
The equation for s² is: s²=SS/n-1 NOT SS/n (this accounts for the sampling error, specifically the tendency to underestimate the population variability)
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16
Q

What does n - 1 represent?

A

The degree of freedom; the amount of the scores that are allowed to vary. The remaining score is determined by the mean (M).

17
Q

What does using n -1 in calculating s² produce unbiased statistics whereas n produces biased statistics?

A

Because it takes into account the tendency for samples to have less variance than populations.

18
Q

What is the empirical rule in statistics?

A

A rule that states: (sometimes called the 68-95-99.7 rule)
Roughly 68% of the distribution scores with fall in the first standard deviation (34% each side of the mean).
Roughly 95% of the distribution scores will fall in the second standard deviation (13.5% each side of SD1, 47.5% each side of the mean).
Roughly 99.7% of the distribution scores will fall in the third standard deviation (2% each side of SD2, a little less than 50% each side of the mean).

19
Q

Why is variance important for inferential statistics?

A

When comparing two sets of scores, high variance in a set of scores makes it harder to identify meaningful differences between a set of scores.

20
Q

What steps should be taken in choosing the correct analysis for a single variable?

A
  1. Define the level of measurement

2. In SPSS use the frequencies procedure for categorical variables and the explore procedure for metric variables.

21
Q

Are grouped frequency tables metric or categorical?

A

Categorical, they become ordinal.

22
Q

What do outliers in boxplots represent?

A

It shows you the location for a particular score in the data sheet.

23
Q

When is it best to use the definitional formula for SS?

A

The definitional formula is best used when the mean is a whole number and there are relatively few scores. range is irrelevant

24
Q

What is it best to use the computational formula for SS?

A

The computational formula is best used when the mean is not a whole number or when there are many scores. range is irrelevant