1. Running head: PROBLEM SET 1 1
Problem Set 1: Chapter 15
Name
Professor
Institution
Course
Date

2. PROBLEM SET 1: CHAPTER 15 2
Chapter 15
Problem # 2,
What information is provided by the numerical value of the Pearson correlation?
The numerical value of the Pearson correlation reflects the real strength of the relationship. It indicates how
properly the points in approximates a linear line relationship. For example, in cases where there is a correlation
of -0.90, it can be inferred that there is a strong correlation of 0.90. It is also important to treat the sign before
the numerical values as a different entity as it only inmates that the correlation is an inverse relationship
Problem# 6b
deviation Squared deviation Products
x y X– MX X– MX x y (X – MX)(Y –
MY)
1 3 -1 0 1 0 0
3 5 1 2 1 4 2
2 1 0 -2 0 4 0
2 3 0 0 0 0 0
∑X=8 ∑Y=12 SSX=2 SSy=8 SP=2
SSX= SSY=
Compute the Pearson correlation
r=2/sqrt 2x8
r=2/4
r=0.4

3. PROBLEM SET 1: CHAPTER 15 3
Problem # 14;
Identifying individuals with a high risk of Alzheimer’s disease usually involves a long series of cognitive tests.
However, researchers have developed a 7-Minute Screen, which is a quick and easy way to accomplish the
same goal. The question is whether the 7-Minute Screen is as effective as the complete series of tests. To
address this question, Ijuin et al. (2008) administered both tests to a group of patients and compared the results.
The following data represent results similar to those obtained in the study.
Deviation Squared Deviation Products
Patient 7 Minute Cognitive X Y X Y (X – MX)(Y –
Screen Series MY)
A 3 11 -4 -6 16 36 24
B 8 19 1 2 1 4 2
C 10 22 3 5 9 25 15
D 8 20 1 3 1 9 3
E 4 14 -3 -3 9 9 9
F 7 13 7 -4 49 16 -28
G 4 9 -3 -8 9 64 24
H 5 20 -2 3 4 9 -6
I 14 25 7 8 49 64 56
∑X=63 ∑Y=153 SSX SSY=23 SP=99
=147 5
Compute the Pearson correlation to measure the degree of relationship between the two test scores.
=99/sqrt (147X235)
=99/185.862
=0.532

4. PROBLEM SET 1: CHAPTER 15 4
Chapter 16,
Problem # 10
Retrieve the descriptive statistics for each of the nine project variables you computed in Week 3.
N Range Minimum Maximum Mean Std. Deviation Variance
Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Statistic
Gender 216 1.00 1.00 2.00 1.4630 .03401 .49978 .250
Repeated Grade? 216 1.00 .00 1.00 .0926 .01977 .29053 .084
9th Grade English 216 2.00 1.00 3.00 2.0185 .03652 .53668 .288
Level
9th Grade English 216 4.00 .00 4.00 2.4954 .06191 .90988 .828
Grade
Social Adjustment 216 1.00 .00 1.00 .1157 .02182 .32066 .103
Problems in 9th
Grade?
Dropped out of High 216 1.00 .00 1.00 .0926 .01977 .29053 .084
School?
ADD-like behavior 216 52.00 24.67 76.67 52.8480 .71118 10.45221 109.249
score (mean of 3)
IQ Score 216 82.00 55.00 137.00 102.3542 .85444 12.55762 157.694
GPA in 9th Grade 216 3.75 .25 4.00 2.4386 .05750 .84507 .714
Valid N (list wise) 216
In the output from your Week 3 analysis, select the variables that you will use to perform your SPSS analysis
this week. You are asked to incorporate these descriptive statistics into the results of this week's Pearson
correlation calculation, following the example provided in this week's Study Notes.
Using the variables you selected, calculate a Pearson correlation in SPSS,
Correlations
ADD-like behavior score (mean of GPA in 9th Grade
3)
Pearson 1 -.542**
ADD-like behavior Correlation
score (mean of 3) Sig. (2-tailed) .000
N 216 216

5. PROBLEM SET 1: CHAPTER 15 5
**
Pearson -.542 1
Correlation
GPA in 9th Grade
Sig. (2-tailed) .000
N 216 216
**. Correlation is significant at the 0.01 level (2-tailed).
The research question examined was: “Is there a relationship between GPA in 9th Grade and ADD-like
behavior score (mean of 3)?” The hypotheses tested were:
Ho: = 0.0
H1: 0 α= .05.
Assumptions for a Pearson correlation are that a) observations are independent b) The variables are
bivariately normally distributed, c) the cases represent a random sample from the population and the scores on variables
for one case are independent of scores on the variables for other cases The results of the test were statistically
significant, r = -.542**p < .001. Thus the null hypothesis is rejected: There is a negative relationship between
GPA in 9th Grade and ADD-like behavior score (mean of 3). The strength of the relationship was moderate,
with 54% of the variance in GPA in 9th Grade and ADD-like behavior score. Thus, the results of the test found
GPA in 9th Grade is not affected by the ADD-like behavior score.
DISCRIPTIVES: APENDIX
Descriptive Statistics
N Range Minimu Maximu Mean Std. Variance Skewness
m m Deviation
Statisti Statistic Statistic Statistic Statistic Std. Statistic Statistic Statistic Std
c Error Err
Gender 216 1.00 1.00 2.00 1.4630 .03401 .49978 .250 .150 .
Repeated Grade? 216 1.00 .00 1.00 .0926 .01977 .29053 .084 2.831 .
9th Grade 216 2.00 1.00 3.00 2.0185 .03652 .53668 .288 .017 .
English Level
9th Grade 216 4.00 .00 4.00 2.4954 .06191 .90988 .828 -.211 .
English Grade

6. PROBLEM SET 1: CHAPTER 15 6
Social 216 1.00 .00 1.00 .1157 .02182 .32066 .103 2.419 .
Adjustment
Problems in 9th
Grade?
Dropped out of 216 1.00 .00 1.00 .0926 .01977 .29053 .084 2.831 .
High School?
ADD-like 216 52.00 24.67 76.67 52.8480 .71118 10.45221 109.249 -.049 .
behavior score
(mean of 3)
IQ Score 216 82.00 55.00 137.00 102.3542 .85444 12.55762 157.694 -.114 .
GPA in 9th 216 3.75 .25 4.00 2.4386 .05750 .84507 .714 -.267 .
Grade
Valid N (List 216
wise)

7. PROBLEM SET 1: CHAPTER 15 6
Social 216 1.00 .00 1.00 .1157 .02182 .32066 .103 2.419 .
Adjustment
Problems in 9th
Grade?
Dropped out of 216 1.00 .00 1.00 .0926 .01977 .29053 .084 2.831 .
High School?
ADD-like 216 52.00 24.67 76.67 52.8480 .71118 10.45221 109.249 -.049 .
behavior score
(mean of 3)
IQ Score 216 82.00 55.00 137.00 102.3542 .85444 12.55762 157.694 -.114 .
GPA in 9th 216 3.75 .25 4.00 2.4386 .05750 .84507 .714 -.267 .
Grade
Valid N (List 216
wise)