Interpretations - AP Statistics

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for AP exam on may 7th!

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26 Terms

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Standard Deviation

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

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Percentile

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

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z-score

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

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When describing a distribution, use

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

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Correlation (r)

The linear association between x-context and y-context is weak/moderate/strong (strength) and positive/negative (direction).

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Residual

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

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Y-intercept

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

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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 s away from the value predicted by the LSRL.

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Coefficient of Determination (r²)

About % of the variation in y-context can be explained by the linear relationship with x-context.

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When describing the relationship, use

DUFS: Direction, unusual features, form, strength.

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Probability P(A)

After many many context, the proportion of times that context A will occur is about P(A).

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Conditional Probability P(A|B)

Given context B, there is a P(A|B) probability of context A.

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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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Binomial Mean (mew subscript x)

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

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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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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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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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Confidence Interval

We are % confidence that the interval (A, B) captures P, the true parameter context.

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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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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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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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Type 1 Error

The Ho context is true, but we find convincing evidence for Ha context.T

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Type 2 Error

The Ha context is true, but we don’t find convincing evidence for Ha context.

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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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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.