Data.savQuestion.docxOver the same period, determine wheth.docx

Data.sav
Question.docx
Over the same period, determine whether there is any difference
in the weight change trajectory for babies who meet their
nutritional goals versus babies who do not meet their nutritional
goals (all goals).
1.
Now that we've answered the question about whether there were
weight changes for all subjects (and then changes during the
two periods), we want to know whether there were any
differences between the two comparison groups (all nutrition
goals met versus not met) for the same periods (overall, birth to
28 days, and 28 days to discharge).
Formulate three null hypotheses to reflect these new questions
2.
Now let's look more closely at the separate periods.
As it turns out, the weight change trajectories were not
significantly different between the two groups of babies in all
periods.
During which period do we see significant differences in weight
change trajectories between the two nutritional groups?
What is the F statistic for the difference in weight change
trajectories of the two groups during the period in which the
trajectories were significantly different? Answer What is the p

value? Answer
What is the change in the means of the two groups during this
period:
· for the babies who met all their nutritional goals? Answer
grams
· for the babies who did NOT meet all their nutritional goals?
Answer grams
3.
Report and interpret the findings with respect to the difference
in weight changes for the two groups for the three hypotheses
above
Though we've determined that there is a significant difference
between nutrition groups in terms of weight change, we notice
that the two groups are different in terms of the length of stay.
So, we wonder whether our previous findings might be altered if
we take NICU length of stay (LOS) into account.
Now, we take the same model we built in the above questions,
add length of stay as a covariate.
4. After controlling for length of stay, we see that the difference
in the overall weight change trajectories between the two groups
has changed.
What is the F statistic for the overall weight change trajectory?
Answer
What is the p value? Answer
Which of the following is a reasonable conclusion regarding our
hypothesis that there is a difference in weight change
trajectories of the two nutritional groups after controlling for
length of stay?
We fail to reject the null and conclude that there is no

difference in weight change trajectories of babies who did and
who did not meet their nutritional goals after controlling for
length of stay
We reject the null and conclude that there is no difference in
weight change trajectories of babies who did and who did not
meet their nutritional goals after controlling for length of stay
We reject the null and conclude that even after controlling for
length of stay, babies who met their nutritional goals still had
significantly different weight change trajectories than babies
who did not meet their nutritional goals
5. We would like some explanation for why the results changed
as dramatically as they did before and after we controlled for
length of stay.
First, what is the mean number of days that babies who met all
their nutritional goals stayed in the NICU? Answer
What is the mean number of days that babies who did NOT meet
all their nutritional goals stayed in the NICU? Answer
What proportion of the variance is explained by length of stay?
54.3%
84%
.3%
78.3%
1%
6.
Briefly, why might controlling for LOS change the findings?
7.

Data.xlsx
Q1Aggressive1Aggressive1Aggressive1Aggressive1Aggressive1
Aggressive1Aggressive1Aggressive1Assertive4Assertive4Assert
ive4Assertive4Assertive4Assertive4Assertive4Assertive4Manip
ulative2Manipulative2Passive3Passive3
Q2SuspendedAggressiveManipulativePassiveAssertiveTotal11Y
es71111011No11171011Total8228201111111112131401020304
040404040404
Q3Suspension from
SchoolAssertiveOtherTotal11Yes191012No641012Total7132012
12121212121221212121212122222222
Output Question 1.spv
outputViewer0000000000.xml
Output Log <head><style type="text/css">p{color:0;font-
family:Monospaced;font-size:14pt;font-style:normal;font-
weight:normal;text-
decoration:none}</style></head><BR>NPAR TESTS
/CHISQUARE=Style
/EXPECTED=EQUAL
/MISSING ANALYSIS.
00000000011_lightNotesData.bin
0000000001211_lightTableData.bin
outputViewer0000000001_heading.xml
Output NPar Tests Title <head><style
type="text/css">p{color:0;font-family:SansSerif;font-

size:18pt;font-style:normal;font-weight:bold;text-
decoration:none}</style></head><BR>NPar Tests Notes
00000000011_lightNotesData.bin Chi-Square Test Title
<head><style type="text/css">p{color:0;font-
family:SansSerif;font-size:18pt;font-style:normal;font-
weight:bold;text-decoration:none}</style></head><BR>Chi-
Square Test Frequencies Title <head><style
decoration:none}</style></head><BR>Frequencies Style
0000000001211_lightTableData.bin Test Statistics
META-INF/MANIFEST.MF
allowPivoting=true
weight:normal;text-
decoration:none}</style></head><BR>CROSSTABS
/TABLES=Suspended BY Style
/FORMAT=AVALUE TABLES
/STATISTICS=CHISQ
/CELLS=COUNT EXPECTED
/COUNT ROUND CELL.

Output Crosstabs Title <head><style
decoration:none}</style></head><BR>Crosstabs Notes
00000000011_lightNotesData.bin Active Dataset <head><style
type="text/css">p{color:0;font-family:Monospaced;font-
size:14pt;font-style:normal;font-weight:normal;text-
decoration:none}</style></head><BR>[DataSet0]  Case
Processing Summary 00000000013_lightTableData.bin
Suspended * Style Crosstabulation
00000000014_lightTableData.bin Chi-Square Tests
allowPivoting=true
weight:normal;text-
decoration:none}</style></head><BR>CROSSTABS
/TABLES=Assertiveness BY Suspension
/FORMAT=AVALUE TABLES
/STATISTICS=CHISQ
/CELLS=COUNT EXPECTED
/COUNT ROUND CELL.

Output Crosstabs Title <head><style
decoration:none}</style></head><BR>Crosstabs Notes
00000000011_lightNotesData.bin Active Dataset <head><style
type="text/css">p{color:0;font-family:Monospaced;font-
size:14pt;font-style:normal;font-weight:normal;text-
decoration:none}</style></head><BR>[DataSet0]  Case
Processing Summary 00000000013_lightTableData.bin
Assertiveness * Suspension Crosstabulation
00000000014_lightTableData.bin Chi-Square Tests
allowPivoting=true
Question.doc
SPSS ASSIGNMENT #8
Chi-Square
SPSS instructions:
Chi-Square Test for Goodness of Fit:
Open SPSS
Remember that SPSS assumes that all the scores in a row are
from the same participant. In the study presented in #1, there
are 20 students, some of whom have been suspended for
misbehavior. The primary conflict-resolution style used by each
student is also entered. [Ignore the first variable in this
analysis.]
When you have entered the data for all 20 students, move to the
Variable View window and change the first variable name to
“SUSPEND” and the second to “STYLE”. Set the number of

decimals for both variables to zero.
Click Analyze ( Non-Parametric Tests ( Chi-Square
Click the variable “STYLE” and then the arrow next to the box
labeled “Test Variable List” to indicate that the chi-square for
goodness of fit should be conducted on the conflict-resolution
style variable.
Note that “All categories equal” is the default selection in the
“Expected Values” box, which means that SPSS will conduct
the goodness of fit test using equal expected frequencies for
each of the four styles, in other words, SPSS will assume that
the proportions of students each style are equal.
Click OK.
Chi-Square Test for Independence:
Open SPSS
For #2, you need to add the variable “SUSPEND” to the
analysis. Remember that in this problem, we are interested in
whether there was an association between conflict-resolution
style and having been suspended from school for misbehavior.
Since the analysis will involve two nominal variables, the
appropriate test is a chi-square test for independence.
Click Analyze ( Descriptive Statistics ( Crosstabs
Since “SUSPEND” is already selected, click the arrow next to
the box labeled “Rows.”
Click the variable “STYLE” and click the arrow next to the box
labeled “Columns.”
Click “Statistics” and click the box labeled “Chi-Square.”
Click Continue.
Click “Cells” and click the box labeled “Expected.”

Click Continue.
Click OK.
1. The following table includes the primary method of conflict
resolution used by 20 students.
Method
Aggressive
Manipulative
Passive
Assertive
N of Students
8
2
2
8
a. Following the five steps of hypothesis testing, conduct the
appropriate chi-square test to determine whether the observed
frequencies are significantly different from the frequencies
expected by change at the .05 level of significance. Clearly
identify each of the five steps.
b. Explain your response to some who has never had a course in
statistics.
2. Next, researchers categorized the students based on the
primary method of conflict resolution used and whether the
student had been suspended from school for misbehavior. These
data are presented below.
Method
Suspended
Aggressive
Manipulative

Passive
Assertive
Total
Yes
7
1
1
1
10
No
1
1
1
7
10
Total
8
2
2
8
20
b. Calculate the effect size.
c. Explain your response to someone who has never had a
course in statistics.
3. Believing that assertiveness is the most effective method of
conflict resolution, the researchers categorized students so that
the aggressive, manipulative, and passive categories were
combined. These data are presented in the table below.

Conflict Resolution
Suspension from School
Assertive
Other
Total
Yes
1
9
10
No
6
4
10
Total
7
13
20
b. Calculate the effect size.
c. Explain your results.
The deadline for this assignment is 11:59 PM EST on Sunday of
Week 8

Data.savQuestion.docxOver the same period, determine wheth.docx

Recommended

Recommended

More Related Content

Similar to Data.savQuestion.docxOver the same period, determine wheth.docx

Similar to Data.savQuestion.docxOver the same period, determine wheth.docx (20)

More from theodorelove43763

More from theodorelove43763 (20)

Recently uploaded

Recently uploaded (20)

Data.savQuestion.docxOver the same period, determine wheth.docx