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1

Standard Deviation

The ** context **typically varies by

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2

Percentile

__Percentile__ % of ** context** are less than or equal to

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3

z-score

__Specific value with __** context** is

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4

When describing a distribution, use

GSOCS: Gaps, shape, outliers, center, spread.

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5

Correlation (r)

The linear association between ** x-context **and

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6

Residual

The actual ** y-context** was

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7

Y-intercept

The predicted ** y-context** when

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8

Slope

The predicted __y-context____increases/decreases__ by __slope__ for each additional ** x-context**.

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Standard Deviation of Residuals (s)

The actual ** y-context ** is typically about

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10

Coefficient of Determination (rÂ˛)

About __rÂ˛__% of the variation in ** y-context** can be explained by the linear relationship with

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11

When describing the relationship, use

DUFS: Direction, unusual features, form, strength.

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12

Probability P(A)

After many many ** context**, the proportion of times that

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13

Conditional Probability P(A|B)

Given ** context B**, there is a

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14

Expected Value (mean, mew)

If the random process of ** context **is repeated for a very large number of times, the average number of

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15

Binomial Mean (mew subscript x)

After many, many trials the average # of ** success context** out of

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Binomial Standard Deviation (sigma subscript x)

The number of ** success context** out of

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17

Standard Deviation of Sample Proportions

The sample proportion of ** success context** typically varies by

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18

Standard Deviation of Sample Means

The sample mean amount of ** x-context** typically varies by

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19

Confidence Interval

We are __%__ confidence that the interval (__A, B) __captures P, the true __parameter context.__

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20

Confidence Level

If we take many, many samples of the same size and calculate a confidence interval for each, about __confidence le__v__el__ % of them will capture the true ** parameter in context**.

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21

p-value

Assuming ** Ho in context** is true, there is a

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22

Conclusion for a Significance Test

With a p-value of __p-value__, __less than/greater than__ __alpha__, we __reject/fail to reject__ Ho. We __do/do not__ have convincing evidence that ** Ha in context**.

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23

Type 1 Error

The ** Ho context** is true, but we find convincing evidence for

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Type 2 Error

The ** Ha context** is true, but we donâ€™t find convincing evidence for

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25

Power

If ** Ha context is true at a specific value** there is

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26

Standard Error of the Slope

The slope of the sample LSRL for ** x-context** and

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