For a test of significance, you are simply looking at the difference in the population proportions. The null is that there is really no difference and the alternative suggests that there is a difference.

Standardize, using a z statistic for a difference in two proportions. The standard error is somewhat different here, you need to pool the samples to get the single estimate for the population parameter p. The pooled sample proportion is:

   p-hat = count of successes in both samples combined
           ___________________________________________
           count of observations in both samples combined

The z-statistic then will be the difference in the two sample proportions divided by a standard error constructed from this estimate of the pooled sample proportion.

The Final

1. Tuesday, December 10 from 11:30-2:30pm
2. Kinsey 51 (the lecture hall)

Please bring these to the examination room

1. 5"x8" crib sheet
2. Calculator with square root key at minimum
3. Writing instruments
4. Photo ID
5. Grade Card (optional)

I will provide these things:

1. Exam (you do not need a blue book/scantron/etc)
2. Tables A and C
3. Scratch paper

Test taking hints:

1. Problems vary in difficulty. If you can't do the first one, come back to it later
2. Get some rest
3. Read the questions carefully
4. Check your answers over
5. For some of you: draw pictures!
6. For others: practice doing problems
7. Still others: look at the formulas

Material Covered and Required for the Final

1. Chapter 1, sections 1.1, 1.2, 1.3 (omit *'d sections)
2. Chapter 2, sections 2.1, 2.2, 2.3
3. Chapter 3, sections 3.1, 3.2
4. Chapter 4, sections 4.1, 4.3, 4.5
5. Chapter 5, sections 5.1, 5.2, 5.3
6. Chapter 6, sections 6.1, 6.2

Bonus Material on the Final

1. Chapter 7, sections 7.1, 7.2 (worth 6 points)
2. Bonus points only allowed for people who scored less than 25 points on the midterm. But feel free to answer them if you choose. I will look at all answers.

Chapter 3

Observational Studies and Experiments

Controls and Treatments

Chapter 1

Graphical Summaries

Numerical Summaries: center & spread

Normal Distribution

Chapter 2

Correlation

Regression

Interpretation