Top Banner
400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1 Mystery 2 Mystery 3
31

400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

Jan 21, 2016

Download

Documents

Paul Nash
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

400

600

800

1000

200

400

600

800

1000

200

400

600

800

1000

200

Mystery 1 Mystery 2 Mystery 3

Page 2: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

The axiom that states “sampling distributions of means will tend

toward Normality when n is large.”

Page 3: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is the Central Limit Theorem?

Page 4: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

A single value that predicts the value of the parameter.

Page 5: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is a point estimate?

Page 6: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

A range of values that attempts to capture a parameter.

Page 7: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is a confidence interval?

Page 8: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

This is the lower end of the confidence interval?

Page 9: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is the lower confidence limit?

Page 10: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

Half of the confidence interval length (quantifies precision).

Page 11: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is the margin of error?

Page 12: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

This is a test for which the alternative hypothesis considers values on both sides of the null.

Page 13: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is the two-sided test?

Page 14: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

This is what a statistician says when the population standard

deviation for the variable comes from a source outside the data.

Page 15: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is “when σ is known”?

Page 16: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

The test statistic used to conduct a test of a mean when σ is

known.

Page 17: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is a z statistic?

Page 18: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

The probability distributions that resemble Normal distributions

but with broader tails.

Page 19: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What are Student’s t distributions?

Page 20: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

Members of the t distribution family are defined by this

parameter.

Page 21: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What are their degrees of freedom ?

Page 22: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

The test statistic used to test two means when the population

standard deviation is not known.

Page 23: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is a t statistic?

Page 24: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

This is the upper end of the confidence interval.

Page 25: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is the upper confidence limit?

Page 26: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

The upper confidence limit minus the lower confidence limit;

twice the margin of error.

Page 27: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is the “confidence interval length”?

Page 28: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

The term that mean “the probability of less or equal to a

given value.”

Page 29: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is the cumulative probability?

Page 30: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

A value for a t random variable that is greater than p × 100% of

the other t values.

Page 31: 400 600 800 1000 200 400 600 800 1000 200 400 600 800 1000 200 Mystery 1Mystery 2Mystery 3.

What is a t percentile?