Aug 29, 2011 ... Chapter 6. Further Inference in the Multiple Regression Model ... Probability
Primer, Exercise Answers, Principles of Econometrics, 4e. 2. (e). A.
from. Probability and Stochastic Processes by R.D. Yates and D.J. Goodman ...
The probability of the event B = {Y < 3} is P[B] = 1 − P[Y = 3] = 1/2. From Theorem
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Answers to Exercises 5. Which of the ... of the examples are enthymemes that
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Which two daemons are part of the Samba suite? What does each do? 2. What
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PROBLEM SET 7 ANSWERS: Answers to Exercises in Jean Tirole's Theory of
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and ...
Answers to End-of-Chapter Exercises. 1. a. The marginal cost schedule would be
: Quantity of Gizmos. Marginal Cost. 1. $75. 2. $100. 3. $175. 4. $250.
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A Short Course in Intermediate Microeconomics with Calculus. Solutions to ... (b)
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11TH BY MARY ELLEN GUFFEY, CAROLYN M. SEEF PDF. Page 1 of 10 ... taught at the University of Illinois, Santa Monica Coll
9. was able to. Exercise 2. 1. b. 2. a. 3. a. 4. b. 5. b. 6. a. 7. b. 8. b. Exercise 3. 1.
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Room 13 and other ghost stories. M. R. JAMES. Macmillan Readers. Room 13 1.
This page has been downloaded from www.macmillanenglish.com.
Intermediate Level. Exercises Answers Key. The Speckled Band and other
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Answer Key for Exercises Exercises-Chapter 1 1.1 A variety of topics appear under ANOVA. A summary is below. You should look at some of the topics in more detail.
1
1.2 I found 2 sets of information: one for categorical or nominal data and another for continuous data. Clicking on either one gave me suggestions about appropriate types of analyses to run given these types of data.
1.3
This will change the view in the Data Editor. When it is checked each piece
of data is in a cell (surrounded by lines), when it is not checked, the cells are not divided by lines.
1.4
This is a matter of personal preference. There is no right answer.
1.5
This is a matter of personal preference. There is no right answer.
Exercises-Chapter 2 2.1
A sample of labels and values follows.
2.2
A sample of the correct data file follows.
2
2.3 Answers will vary depending on how you created your own data file. Remember to compare your file to Exercise2.2.sav on the CD.
2.4 To perform this exercise accurately, you would have used the merge/add cases option. The only way you would know this is by opening the 2 original files and looking at them. You can see both include the same variables, but include the data from different people. The merged file will include 90 cases.
2.5
To do this effectively, you would need to have noticed that the variable
names were included at the top of the file and that commas delimited the data. A sample of the correct data file follows.
3
2.6 All of the original variable names were longer than 8 characters, so I renamed them before reading them into EXCEL so they wouldn’t end up with generic or truncated names. A sample data file follows.
4
Exercises-Chapter 3 3.1
A histogram for ADDSC follows. ADD score in elementary school 30
20
Frequency
10
Std. Dev = 12.42 Mean = 52.6 N = 88.00
0 25.0
35.0 30.0
45.0 40.0
55.0 50.0
65.0 60.0
75.0 70.0
85.0 80.0
ADD score in elementary school
3.2
The box plots follow. It appears that students with social problems have
more ADD symptoms than students without social problems. The distribution appears more normally distributed for students with no social problems. The distribution for students with social problems appears positively skewed. Neither group has outliers.
5
90
80
ADD score in elementary school
70
60
50
40
30 20 N=
78
10
no social problems
yes, social problems
social problems in 9th grade
3.3 A sample scatter plot follows. There appears to be a negative association between GPA and ADD symptoms. 4.5 4.0
Grade point average in 9th grade
3.5 3.0
2.5
2.0 1.5
1.0 .5 20
30
40
50
ADD score in elementary school
6
60
70
80
90
3.4 A sample bar chart follows. It looks as if GPA differs between the 3 groups such that students in the college prep course have higher GPAs than students in general or remedial English, and students in general English have higher GPAs than students in remedial English. [Of course, we would need to compute some inferential statistics to see if these differences are statistically significant.] 3.2
Mean Grade point average in 9th grade
3.0 2.8 2.6
2.4
2.2 2.0
1.8 1.6 college prep
general
remedial
level of English in 9th grade
3.5 The 2 graphs follow. It looks like there is a main effect of type of English class as described above. It also looks like there is a main effect of gender such that females have higher GPAs than males. I would guess there is an interaction effect such that the gender difference in GPA is greatest among students in college prep English. I like the line graph better because I think it is easier to visualize interaction effects with a line graph than a bar graph.
7
Mean Grade point average in 9th grade
3.5
3.0
2.5
2.0
gender male female
1.5 college prep
general
remedial
level of English in 9th grade
Mean Grade point average in 9th grade
3.5
3.0
2.5
2.0
gender male
1.5
female college prep
general
level of English in 9th grade
8
remedial
Exercises-Chapter 4 4.1 The output follows. I used Analyze/Descriptive Statistics/Frequencies to calculate these descriptives because it includes all of the options including the histogram.
a. Multiple modes exist. The smallest value is shown
Histogram
9
anxiety score 14
12
10
8
6
Frequency
4 Std. Dev = .73
2
Mean = 3.86 N = 48.00
0 2.50
3.00
3.50
4.00
4.50
5.00
anxiety score
10
4.2 I calculated these frequencies using Analyze/Descriptive Statistics/Crosstabs. The results follow. gender * social problems in 9th grade Crosstabulation
gender
male female
Total
social problems in 9th grade no social yes, social problems problems 48 7 87.3% 12.7% 30 3 90.9% 9.1% 78 10 88.6% 11.4%
Count % within gender Count % within gender Count % within gender
Total 55 100.0% 33 100.0% 88 100.0%
4.3 The output follows. I calculated them by using Analyze/Compare Means/Means. Report Grade point average in 9th grade social problems in dropped out of 9th gradeproblems high school no social did not drop out dropped out of high school Total yes, social problems did not drop out dropped out of high school Total Total did not drop out dropped out of high school Total
Mean 2.5293
73
Std. Deviation .8744
Variance .764
1.5340
5
.6171
.381
2.4655 2.3500
78 5
.8915 .8023
.795 .644
2.4180
5
.4218
.178
2.3840 2.5178
10 78
.6054 .8662
.366 .750
1.9760
10
.6822
.465
2.4562
88
.8614
.742
11
N
Exercises-Chapter 5 5.1 The two-tailed correlations follow. Using a one-tailed versus a two-tailed test did not matter in this case because all of the correlations are statistically significant at the p
