Name: ______

Homework #3: Due Friday Sept. 17, 2004

Homework answers should be typed or neatly printed (no cursive). If your answers are not legible, you will lose points. Use this form as a cover sheet for your homework. Print out these pages, fill in your name above, and staple the pages with your answers to them.

Remember: For problems that require calculations, SHOW YOUR WORK!

1. A developmental psychologist asked a group of 60 first graders (age 6) to complete a moral-reasoning test. The developmental psychologist recorded the kids’ performances on a scale where a score of 9 - 10 indicates “extremely developed” moral reasoning, 7 - 8 means “moderately developed” moral reasoning, 5 - 6 means “somewhat developed” moral reasoning, 3 - 4 means “slightly under developed” moral reasoning, and 1 - 2 means “extremely under developed” moral reasoning. Below is a frequency distribution of the scores. Use this table to answer the following questions.

X / f
8 / 1
7 / 2
6 / 5
5 / 11
4 / 15
3 / 18
2 / 5
1 / 3

a. What is the probability of a child scoring 6 or above on the test? (1 point)

There are 60 total children. 5 scored 6, 2 scored 7, and 1 scored 8. Therefore the probability of a child scoring 6 or above on the test = 8/60 = .133.

b. What is the probability of a child scoring 9 on the test? (1 point)

There are 60 total children, and zero of them scored 9 on the test. Therefore the probability of a child scoring 9 on the test = 0/60 = 0.0.

c. What is the probability of a child scoring in the “somewhat developed” category on the test? (1 point)

There are 60 total children. A child falls in the “somewhat developed” category if he or she scores 5 or 6. 11 children scored 5, and 5 children scored 6. Therefore the probability of a child scoring in the “somewhat developed” category = 16/60 = .267.

2. Based on a large-scale survey of American women, it is known that the average height of US women is 63.5 inches with a standard deviation of 2.5 inches. Use this information to answer the following questions.

a. Dr. Claypool is 61 inches tall. Convert her height to a z-score. (1 point)

z = z =

b. Susan’s height is represented by a z-score of +1.8. How tall is Susan? (1 point)

X =X =

c. What percentage of women are between 60 and 65 inches tall? (1 point)

z = z =

The area below a z-score of –1.40 is equivalent to the “smaller portion” of a z-score of +1.40, which from Table E.10 is .0808.

z = z =

The area below a z-score of +.60 is the “larger portion” from this z-score, which from Table E.10 is .7257.

To find the area between heights of 60 inches (z = -1.40) and 65inches (z = +0.60), we can take the smaller value and subtract it from the larger value.

Therefore, the proportionof US women who are between 60 and 65 inches tall is: .7257 - .0808 = .6449. Thus, the percentage of US women who are between 60 and 65 inches tall is 64.49%.

d. Angie’s height puts her at the 20th percentile. How tall is Angie? (1 point)

The 20th percentile corresponds to a z-value with .20 “below it.” This means we need a z-score with a smaller portion of .20. Note that this z-score will be NEGATIVE b/c the 20th percentile is below the mean.

A z-score of .84 is the one closest to having a smaller portion of .20. Thus, the desired z-score is -.84. Now, we need to plug this z-score into the following equation to find the raw score corresponding to this value:

X =X =

Angie is 61.4 inches tall.

e. Suppose that Janet’s height is equivalent to a z-score of +.50. What does this mean? (Note, I am not asking for a calculation. Just give an interpretation of this z-score). (1 point)

Since Janet’s height results in a positive z-score, we know that her height is above the average. The magnitude of her z-score (.50) indicates that she is specifically .50 standard deviations above the average.

3. The 68 students in PSY 293 take their first exam. Dr. Claypool converts each raw exam score to a z-score. What will be the mean, the standard deviation, and the shape of this z-distribution of exam scores? (3 points)

The mean of a z-distribution is ALWAYS zero. The standard deviation of a z-distribution is ALWAYS 1. And, the shape of a z-distribution will be the same shape as that of the raw scores. If the raw scores were normally distributed, the shape of a z-distribution of those raw scores will also be normal. If the raw scores were skewed, the shape of a z-distribution of those raw scores will also be skewed.

4. Greg and Dan are brothers. Greg is in his senior year of college and just took the GRE because he hopes to attend graduate school. Dan is in his senior year of high school and just took the ACT because he hopes to attend college. Scores on the GRE Verbal section have  = 500 and  = 20. Scores on the ACT Verbal section have  = 18 and  = 6. Greg scored 525 on the Verbal GRE, and Dan scored 23 on the Verbal ACT. Which brother has the better percentile rank? (2 points)

z = z =  Greg’s z-score

z = z =  Dan’s z-score

From Table E.10, a z-score of 1.25 has an area of .8944 below it. Therefore, Greg is at the 89th percentile (if rounded). A z-score of .83 has an area of .7967 below it. Thus, Dan’s percentile rank is 80th (if rounded). Greg performed better on the GRE (i.e., was at a higher percentile rank) than Dan did on the ACT.

5. A developmental psychologist constructed a questionnaire to assess “psychological maturity” among 10-year olds. Scores from this measure range from 0 – 56 with a  = 34 and  = 8. The developmental psychologist has decided to re-scale her measuring instrument so that it has a  = 200 and  = 50. Use this information to answer the following questions.

a. Cliff received a score of 17 (in original units) on the measure. What would Cliff’s score be in re-scaled ( = 200,  = 50) units? (2 points)

This problem requires us to use transformed standard scores (TSS).

TSS = new + z new

Before we can use the above formula, we must translate Cliff’s score into a z-score.

z = z =

Now…TSS = 200 + (-2.125)(50) =93.75

On the re-scaled measure, Cliff scored 93.75

b. Sally’s score on the re-scaled measure is 285. What was her score in the original units? (2 points)

First, we need to determine what z-score corresponds to this TSS.

TSS = new + z new285 = 200 + z(50)

If we solve for z we get:

285 - 200 = z(50)

z = 1.70

Now, we need to translate this z-score back to the original units:

X =X =

Thus, Sally’s score in original units is 47.6.

6. Imagine that you have two bags of marbles. In bag #1, you have 50 blue marbles and 50 yellow marbles. In bag #2, you have 80 blue marbles and 20 yellow marbles. Suppose you reach into one of the bags and pull out 10 marbles—3 blue and 7 yellow. From which bag is it more likely that you obtained your sample and why? [In your answer, be sure to mention how many blue and yellow marbles you would have expected in your sample had you drawn from Bag #1 and from Bag #2] (3 points)

If you had drawn from Bag #1, you would have expected how many of your 10 to be blue:

Total # of blue marbles in bag: 50

Total # of marbles in the bag: 100

Thus, we would have expected 50% of the marbles (5) to be blue.

If you had drawn from Bag #1, you would have expected how many of your 10 to be yellow:

Total # of yellow marbles in bag: 50

Total # of marbles in the bag: 100

Thus, we would have expected 50% of the marbles (5) to be yellow.

If you had drawn from Bag #2, you would have expected how many of your 10 to be blue:

Total # of blue marbles in bag: 80

Total # of marbles in the bag: 100

Thus, we would have expected 80% of the marbles (8) to be blue.

If you had drawn from Bag #2, you would have expected how many of your 10 to be yellow:

Total # of yellow marbles in bag: 20

Total # of marbles in the bag: 100

Thus, we would have expected 20% of the marbles (2) to be yellow.

To summarize: From Bag #1 we expect: 5 blue and 5 yellow

From Bag #2 we expect: 8 blue and 2 yellow

We actually drew: 3 blue and 7 yellow

The sample we obtained (3 blue; 7 yellow) is much more similar to the expected values from Bag #1. So, the likelihood is greater that our sample came from bag #1 than bag #2.