Symbol Interpretation
Purpose for Acronyms
How to find this number
Cautionary Tales
Interpretations and Conclusions
100

This measures the strength and direction of the linear relationship between the x variable and the y variable.

What is r?

100

We use this to make sure a scenario satisfies the Binomial Setting.

What is BINS?

Binary, INdependent, Normal, probability of Success

100

Degress of Freedom for a Test of Slope

What is n-2?

100

If you are comparing two distributions, you must do this to get credit.

Use comparison words in context.  Words like "more than", less than", "larger", etc.

(Example, the mean score of 85% in Mr. B's class is higher than the mean score of 78% in Mrs. Z's class.)

100

We can only infer about the population of interest if we do this. 

What is gather a large random sample take from the same population we hope to draw conclusions about?

200
The "estimated" or "predicted" y-value (state in context) for a given x-value (state in contact) 

What is y-hat?

200

Helps us describe univariate data?

 What is SOCS? (or SOCCS which reminds us to give context)

Shape, Outliers, Center, Spread

200

Degrees of Freedom of a test of homogeneity or association/independence.

What is (# of rows - 1)(# of columns - 1)?

200

We should never do this when predicticting with an LSRL.

What is extrapolate?

200

Interpret confidence interval

What is "I am ____% confident that the interval from ____ to _____ captures the true ______."

300

% of variation in y (context) is accounted for by the LSR line of y (context) on x (context)

What is r2?
300

Helps us to describe bivariate data.

What is DOFS?

Direction Outliers, Form, Strength

300

Degrees of Freedom for the differene of means if you are finding it manually.

What is the smaller of either n1 - 1 or n2 - 1?

300

You can never infer this unless you know you have a well controlled experiement with a large enough sample to show good replication.

What is infer causation?

300

Interpet confidence level

What is "Intervals produced with this method will capture the true population ______ (mean or proportion) in about _____% of all possible samples of this same size from this population.

400

This measures the standard deviation of the estimated slope for predicting the y-variable (context) from the x-variable (context).

 What is SEb?

400

Conditions for Inference on Slope

What is Liner?

Linear, Independent, Normal (histogram of residuals), Equal variance of residuals, Random

400

How do you satisfy the Large Sample Size Chi Square tests?

What are Expected Counts are at least 5?

400

These words are words that show that the numbers we find are not certain, they are only helping us infer what is true about the population (you only need one of these words.)

What is "estimates" or "predicts".  (We also use this posture of uncertainty when we conclude things.)

400

Explain P-Value

Assuming/given the null is true (in context), the P-value measures the chance of observing a statistic (or difference in statistics (context)) as large as or more extreme than the one actually observed.

500

It measures the typical distance between the actual y-values (context) and their predicted y-values (context).

What is s?

500

The Words that describe that when n is 30 or larger, the sampling distribution of the sample mean x-bar is approximately Normal.

What is CLT?

Central Limit Theorem

500

Find the z* manually using the table.

What is add the lower tail to the confidence level and look in the body of the table for that percentage.  Then find the appropriate z-score in the margins.

500

This word is taboo when concluding significance tests since we can't be certain of our conclusion.

What is "accept"?

Instead we reject or fail to reject.

Also, remember the idea that innocent until proven guilty, so we use the wording: 

"We don't have sufficient evidence to conclude that" indicates a failure to reject the null hypothesis 



500

The interpretation of an unbiased estimator

The data collected in such a way that there is no systematic tendency to overestimate or underestimate the true value of the population parameter.  (Also fine if you say that the mean of the sampling distibution equals the true value of the parameter being estimated.)

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