# Interpretations - AP Statistics

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Standard Deviation

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## Description and Tags

for AP exam on may 7th!

### 26 Terms

1

Standard Deviation

The context typically varies by SD from the mean of mean.

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2

Percentile

Percentile % of context are less than or equal to value.

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3

z-score

Specific value with context is z-score standard deviations above/below the mean.

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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 y-context is weak/moderate/strong (strength) and positive/negative (direction).

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6

Residual

The actual y-context was residual above/below the predicted value when x-context = value.

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7

Y-intercept

The predicted y-context when x = 0 context is the y-intercept.

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8

Slope

The predicted y-context increases/decreases by slope for each additional x-context.

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9

Standard Deviation of Residuals (s)

The actual y-context is typically about s away from the value predicted by the LSRL.

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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 x-context.

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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 context A will occur is about P(A).

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13

Conditional Probability P(A|B)

Given context B, there is a P(A|B) probability of context 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 x-context we can expect is expected value.

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15

Binomial Mean (mew subscript x)

After many, many trials the average # of success context out of n is sample mean.

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16

Binomial Standard Deviation (sigma subscript x)

The number of success context out of n typically varies by sample std from the mean of sample mean.

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17

Standard Deviation of Sample Proportions

The sample proportion of success context typically varies by proportion std from the true proportion of p.

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18

Standard Deviation of Sample Means

The sample mean amount of x-context typically varies by mean std from the true mean of mean of x.

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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 level % 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 p-value probability of getting the observed result or less/greater/more extreme purely by chance.

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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 Ha context.T

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24

Type 2 Error

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

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25

Power

If Ha context is true at a specific value there is power probability the significant test will correctly reject Ho.

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26

Standard Error of the Slope

The slope of the sample LSRL for x-context and y-context typically varies from the slope of the population LSRL by about SE of slope.

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