Examining Distributions Checkpoint 2

1. 99.7% of data resides within 3 standard deviations of the mean.

2. Center and spread IQR and standard deviation. IQR = Q-Q1

3. Pie chart. One response variable-categorical.

4. Impossible to tell. Boxplots only show cities and annual income amounts. Does not mention number of responses.

5. Statstown Q1=40, Q3 =110

6. Medianville, IQR =110-60

7. Statstown, IQR = 110-40

Examining Relationships Checkpoint 2

1. Conditional row percentages in a two way table.

2. Remove outlier R increases because outlier is taken out of 5 number summary.

3. R=0 no linear relationship

4. Temp is a lurking variable. Low temp could cause more wood to be sold.

5. Scatterplot slopes left = negative correlation for males and females.

6. R and B always have the same sign.

7. Simpsons Paradox. City is a lurking variable because larger cities vs smaller cities can affect the outcome.

Sampling Checkpoint 1

1. B, random sample avoids bias.

2. Multi stage sampling, States – Universities – Students.

3. All students. Statistics department volunteered however all students could be enrolled in statistics.

4. The sampling frame should equal the sample population as much as possible.

5. Yes., it is representative because it was a random sampling.

6. Voluntary because anyone could mail a response.

7. D. The same sample size was chosen from each undergraduate class.

Designing Studies Checkpoint 1

1. Good experiment ensures that results are based on treatment given.

2. Observational study. Men were not told to be smokers.

3. Placebo = dummy pill.

4. A well designed study ensures that results are based on the treatment given.

5. Not blind. Students knew whether or not music was playing.

6. Double blind. Volunteers did not know which tea they were given and psychologist did not know which tea was given to which subject.

7. Lurking variable is the amount of country music played will vary by community.

Designing Studies Checkpoint 2

1. 6, 3 drugs X 2 diets.

2. Explanatory equals BP before, BP after and Comparison of BP.

3. Biased wording “ Huge National Deficit”.

4. Randomized response minimizes bias.

Probability Checkpoint 2

1. All 3 outcomes are equally probable.

2. P(A and B) = P(A) X P(B) = .12

3. Overweight + Obese

4. A and B are independent because of random selection.

5. P(N) X P(D)

6. .20 taken from example.

7. 1 – 15% or 85%

8. (.99)to the 4th

9. At least one responds 1 – (99) to the 4th.

10. Total guess. Wasn’t sure which rule to apply.

Conditional Probability Checkpoint 1

1. P(H) =.60, P(W) = .25, P(H and W) = .20

a. P(W/H)

2. P(W/H) or .25/.60 = .416 or .42

3. Independent events P(H) * P(W) .60 * .25

4. P(B) = .5 because A and B are independent.

5. P(Blue) = .31, P(Deaf) = .38 P (Blue and Deaf) = .42

a. P(B) and P(D) are independent therefore P(B) * P(D) does not equal .42

Conditional Probability Checkpoint 2

1. P(B) and P(D) are independent. Use multiplication rule for independent events .31*.38.

2. P(A) = .75, P(B) = .25, P(A and L) = .80, P(B and L) = .95

3. P(A) = .75 P(A and L) = .80

4. P(A)*P(L) divided by P(A) * P(L) + P(B) * P(L)