AP Stats Cookie Cutter Sentences

Shout out Mrs. Heitl!

Confounding Variables

The confounding variable is related to the explanatory variable and potentially influences the response variable

Interpret Dots in Context

When we assumed that the EV idint matter, there was/were ___ simulated random occurance(s) when the difference in means/proportions for the two groups was ____

Interpret % in Context

Assuming EV has no effect on RV, there is a ___% probability of getting a difference of SR or more purely by chance alone

Statistically Significant

Yes, it is statistically significant as ___% of the time we would get a different in means/proportions of SR or more purely by chance, which is highly unlikely to occur

NOT Statistically Significant

No, it is not statistically significant as ___% of the time we would get a difference in means/proportions of SR or more purely by chance alone, which is unlikely to occur

Interpret Standard Deviation

The context typically varfies by SD from the mean x-bar

Interpret Z-Score

Context is z-score standard deviations above/below the mean

Describe the relationship between 2-Variables

There appears to be a strength, direction, form relationship between context.

Note: DESCRIBE UNUSUAL FEATURES

Interpet the Sploe of a Line for LSRL

for every 1 unit increase in x, the y increases/decreases by slope units, on average

Interpet the y-intercept of a Line from LSRL

the y-hat is approximately y-intercept when x is 0

Interpet Residual

The actually y was Residual higher/lower than predicted by the LSRL when x= # x units

Intepret r

There is a strength, direction linear relationship between context

Interpret r²

r² % of the variation in y can be explained by the LSRL given x=x

Interpret s

The actual y is typically about s units away from the value predicted by the LSRL using x=x

Interpret Confidence Interval

We are C% Confident that the interval from A to B captures the true parameter with context

Interpret Confidence Level

In C% of all possible samples, the interval computed from the sample data will capture the true parameter in context

Inteprret P-Value

Assuming the H_o is true (H_o ), there is a P-Value probability of getting observed result or more extreme purely by chance alone. B

Interpret Power

If parameter is true at the specified value, there is a power probability of finding convincing evidence to reject H_o

Conclude

Because P-Value </> a(, we do/do not have convincing evidence for H_a in Context. Reject/Fail to Reject H_o