PSYC 510
HOMEWORK: RELATIONSHIPS AND REGRESSION TEMPLATE
This assignment is worth a total of 60 points.
•Content: point values vary but are indicated in the template and total 45 points.
•Format: point values vary but are indicated in the template for 10 pts. The remaining 5
pts are for placing answers in the correctly designated spots within the template in a
clear and easy to read format (e.g., all fit within the visible screen on the page) and
uploading it in an approved format (word or PDF). Thus, the maximum is 15 points for
format.
Research consistently shows that children are more likely to have behavior problems if they
have less support available in their family. A local developmental psychologist had 10 sets of
parents complete validated scales to measure family support and child behavior problems,
where higher numbers indicate more family support or behavioral problems. She wanted to
test whether her local community’s data are consistent with previous research (that
behavioral problems are related to less family support). The data appear below. Enter it into
SPSS to complete the first set of problems (#1-7). 29 pts content / 8 pts format
Family Support Behavioral Problems
9 3
8 6
5 4
9 3
7 4
5 7
3 5
8 4
5 4
2 7
#1 What is the research hypothesis (not the null hypothesis – the research hypothesis). State
whether it is one or two-tailed, and justify your answer. 3 pts
Children with more family support will have less behavioral difficulties. This is a one-tailed test
since the hypothesis seeks to determine the direction of the correlation between the two
variables.
#2 Calculate the appropriate statistical test using SPSS. Copy / paste all relevant output in the
space provided, making sure it is all viewable. 5 pts
PSYC 510
#3 Write a Results section for your findings. Include the type of statistical test and results of
the test (clearly stating whether results are significant or not), confidence interval, and
interpret the coefficient of determination. 5 pts content / 2 pts format
A Pearson’s r correlation revealed an negative relationship between the family support and
behavior problem children experience, r= -.623, p=0.27 (one-tailed). CI[-1.00, -.108], 38%
variability.
PSYC 510
#4 Regardless of the statistical results above, use SPSS to calculate a regression analysis to see
if family support can predict behavioral problems. (Note this statement tells you what the
predictor (IV) and what you want to predict (the DV) is in this analysis). Copy / paste all SPSS
output as images in the space below. 5 pts
Variables Entered/Removeda
Model
Variables
Entered
Variables
Removed Method
1 BehavioralProble
msb
. Enter
a. Dependent Variable: FamilySupport
b. All requested variables entered.
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
1 .623a.388 .312 2.04884
a. Predictors: (Constant), BehavioralProblems
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 21.318 1 21.318 5.078 .054b
Residual 33.582 8 4.198
Total 54.900 9
a. Dependent Variable: FamilySupport
b. Predictors: (Constant), BehavioralProblems
Coefficientsa
Model
Unstandardized Coefficients
B Std. Error
Standardized
Coefficients
Beta t Sig.
1 (Constant) 10.940 2.243 4.877 .001
BehavioralProblems -1.030 .457 -.623 -2.254 .054
a. Dependent Variable: FamilySupport
Model Description
Model Name MOD_1
Dependent Variable 1 FamilySupport
Equation 1 Linear
Independent Variable BehavioralProblems
Constant Included
Variable Whose Values Label Observations in Plots Unspecified
PSYC 510
Case Processing Summary
N
Total Cases 10
Excluded Casesa0
Forecasted Cases 0
Newly Created Cases 0
a. Cases with a missing value in any
variable are excluded from the
analysis.
Variable Processing Summary
Variables
Dependent Independent
FamilySupport
BehavioralProble
ms
Number of Positive Values 10 10
Number of Zeros 0 0
Number of Negative Values 0 0
Number of Missing Values User-Missing
System-Missing
0 0
0 0
Model Summary and Parameter Estimates Dependent
Variable: FamilySupport
Equation
Model Summary
R Square F df1 df2 Sig.
Parameter
Estimates Constantb1
Linear .388 5.078 1 8 .054 10.940 -1.030
The independent variable is BehavioralProblems.
#5 Create an appropriate figure for the regression (include the line of best fit). Present it
professionally below, numbering it as Figure 1 (and don’t forget all other components like a
title, et cet). 4 pts content / 3 pts format
Figure 1
Correlation Between Family Support and Behavioral Problems
PSYC 510
#6 Write a results paragraph for the regression analysis. Make sure to include the statistical
test results, regression equation, interpretation of the equation, and the standard error of the
estimate. Include a correctly formatted callout to Figure 1 as well! (Note this question
requires you to synthesize information from the lecture video, SPSS Workbook, and ebook
chapter from this week! Hint: See Application 9.3 (p. 272) and its related sections in chapter 9
for an example write-up based on SPSS output.) 5 pts content / 3 pts format
Family support ratings in the sample varied from 2 to 9, with a mean of 6.1 (SD =2.47). The
behavioral support scores for the sample of ten individuals varied from 3 to 7, with a mean of
4.7 (SD=1.49. A Pearson's r was calculated to see if there was a link between the two
variables, and a significant negative association was discovered (r= -6.23, p=.054, 95% CI
[-.900,.011]. Within this sample, the connection between the family support variable and
behavioral disorders explained X% of the variability.
Linear regression was performed with the variables family support and behavioral difficulties,
and the result was not significant, F(1,18) =, p=0.54. The regression equation (Y' = -
1.030+10.94) revealed a negative association between the two variables, and the standard
error of estimate was 2.049.
#7 Imagine a research lab published a significant linear regression in which family support can
predict behavioral problems. A local news team reported these findings by stating that
behavioral problems are caused by having no family support. In 2 – 3 sentences, briefly
discuss whether this is an appropriate claim, using terms and concepts from this course. 2 pts
This is not a true claim, as Figure 1 shows a weak association between family support and
behavioral difficulties in children. When attempting to forecast the chance of children
demonstrating bad conduct, the connection is negligible (r= -6.23).
PSYC 510
A developmental psychologist measured motor skills in two groups of seven-year-old children
– those with a diagnosis of Autism Spectrum Disorder (ASD) and those with no diagnosis
(“None”). He used the Test of Gross Motor Development (TGMD-3) to obtain an overall
composite score. This composite score is calculated by summing all performance criteria and
can range from 0 (complete absence of skills) to 100 (proficiency in all skills). Data are in the
table below. Enter the data into SPSS to complete problems #8-10. (16 pts content / 2 pts
format)
D M Skills
None 77
None 71
None 66
None 83
None 85
None 70
None 68
ASD 71
ASD 40
ASD 10
ASD 15
ASD 23
ASD 60
ASD 70
#8 What would be the most appropriate statistical test to examine whether there is a
relationship between having an ASD diagnosis and motor skills development? Why? State the
two variables and scale of measurement for each. (Hint: this is a test covered this week) 6 pts
The point-biserial correlation coefficient is the most appropriate statistical test since the
diagnostic variable is dichotomous and the motor skill variable is interval.
#9 Calculate the appropriate statistical test using SPSS. Copy / paste all relevant output in the
space provided, making sure it is all viewable. 5 pts
Figure 1
Correlation Between ASD diagnosis and Motor Skill Development
PSYC 510
Descriptive Statistics
Mean Std. Deviation N
Diagnosis .50 .519 14
MotorSkills 57.7857 25.13098 14
Correlations
Diagnosis MotorSkills
Diagnosis Pearson Correlation 1 -.681**
Sig. (2-tailed) .007
N 14 14
MotorSkills Pearson Correlation -.681** 1
Sig. (2-tailed) .007
N 14 14
**. Correlation is significant at the 0.01 level (2-tailed).
Confidence Intervals
Pearson
Correlation Sig. (2-tailed)
95% Confidence Intervals
(2tailed)a
Lower Upper
Diagnosis - MotorSkills -.681 .007 -.890 -.236
a. Estimation is based on Fisher's r-to-z transformation.
Correlations
Diagnosis MotorSkills
Spearman's rho Diagnosis Correlation Coefficient 1.000 -.657*
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Sig. (2-tailed) . .011
N 14 14
MotorSkills Correlation Coefficient -.657*1.000
Sig. (2-tailed) .011 .
N 14 14
*. Correlation is significant at the 0.05 level (2-tailed).
Confidence Intervals of Spearman's rho
Spearman's rho Significance(2tailed)
95% Confidence Intervals
(2tailed)a,b
Lower Upper
Diagnosis -
MotorSkills
-.657 .011 -.884 -.177
a. Estimation is based on Fisher's r-to-z transformation.
b. Estimation of standard error is based on the formula proposed by Fieller, Hartley, and
Pearson.
#10 Write a Results section for your findings. Include the type of statistical test and results of
the test (clearly stating whether results are significant or not), confidence interval, and
interpret the coefficient of determination. 5 pts content / 2 pts format
Interpreting the correlation as a weak or no association between ASD diagnosis and motor skill
development, this is statistically significant (p=.007), and we must maintain the null hypothesis
that there is no relationship between having ASD and motor skill development.
Note: Your assignment will be checked for originality via the Turnitin plagiarism tool.
