MATH GURU ONLY

Due in 15 hours

cenario:

You are the new director of institutional research at a small state university, and you have been assigned the task of analyzing information for the dean of the School of Education regarding the performance of their undergraduate students on the often-controversial Graduate Record Exam (GRE). Many educators believe the GRE is a poor evaluator of undergraduate performance as well as a poor predictor of graduate school performance. The dean is considering eliminating the GRE from graduate school admissions requirements.

The dean has already collected data on four variables: 1) gender, 2) grade point average (GPA), 3) GRE score, and 4) graduate degree completion frequency. Your job is to develop a proposed analysis to assist the dean to make an informed decision regarding the future use of the GRE.

Using this information, develop the following foundational components for a proposed analysis:

1. A relationship research question involving GPA and GRE scores; corresponding null and alternative hypotheses; the type of statistical analysis to be employed to determine significance; explanations of fictitious outcomes identifying both non-significant and significant relationships as related to both null and alternative hypotheses; and recommendations based on non-significant and significant findings.

2. A relationship research question involving gender, GPA, and GRE scores; corresponding null and alternative hypotheses; the type of statistical analysis to be employed to determine significance; explanations of fictitious outcomes identifying both non-significant and significant relationships as related to both null and alternative hypotheses; and recommendations based on non-significant and significant findings.

3. An effect research question involving gender and GRE scores; corresponding null and alternative hypotheses; the type of statistical analysis to be employed to determine significance; explanations of fictitious outcomes identifying both a non-significant and a significant effect as related to both null and alternative hypotheses; and recommendations based on non-significant and significant findings.

4. An effect research question involving gender, GRE score, and degree completion frequency; corresponding null and alternative hypotheses; the type of statistical analysis to be employed to determine significance; explanations of fictitious outcomes identifying both a non-significant and a significant effect as related to both null and alternative hypotheses; and recommendations based on non-significant and significant findings.

5. Finalize your report with a written analysis of your results and recommendations for the dean based on your findings.

Support your assignment with at least five scholarly resources. In addition to these specified resources, other appropriate scholarly resources, including older articles, may be included.

10 pages

Assignment

2

: Tests of Signifi

c

ance

–

Tests

Mock Study

: t-Test for a Single Sample

(

20 points

)

1. Researches are interested in whether depressed people undergoing group therapy will perform a different number of activities of daily living after group therapy. The researchers randomly selected 12 depressed clients to undergo a 6-week group therapy program.

Use the five steps of hypothesis testing to determine whether the average number of activities of daily living (shown below in the table) obtained after therapy is significantly different from a mean number of activities of 17 that is typical for depressed people. (Clearly list each step).

Test the difference at both the .05 and .01 levels of significance.

As part of Step 5, indicate whether the behavioral scientists should recommend group therapy for

all

depressed people based on evaluation of the null hypothesis at both levels of significance (.05 and .01).

Data to be entered in SPSS (instructions below)

CLI

AFTER THERAPY

Step 1: Data managing

pen a blank SPSS data file: File New Data

2. In the blank SPSS data file, create your SPSS data set by entering the number of activities of daily living performed by the depressed clients (see above) in the Data View window.

3. In the Variable View window, change the variable name to “ADL.” Set the decimals to zero.

Step 2: SPSS execution

a. Click: Analyze Compare Means One-Sample T test use the arrow to move “ADL” to the Variable(s) window on the right.

b. Enter the population mean (17) in “Test Value”

c. Click OK.

Simple t test

Question research: To discover is the depressed people experiencing group therapy (treatment) will play out an alternate number of exercises of day by day living after group therapy

One-Sample Test

Test Value

Sig. (2-tailed)

Mean Difference

95% Confidence Interval of the Difference

Lower

Upper

ADL

2.165

.053

1.750

-.03

3.53

One-Sample Test

Test Value = 14

Sig. (2-tailed)

Mean Difference

99% Confidence Interval of the Difference

Lower

Upper

ADL

2.165

.053

1.750

-.76

4.26

Conclusion:

1) 0.53>0.05 fail to accept How, concluded that that the mean number activities after group therapy is different from 14

2) 0.53>0.05 fail to accept How, concluded that that the mean number activities after group therapy is different from 14

Mock Study 2: t- Test for Dependent Means (20 points)

2. Researchers are interested in whether depressed people undergoing group therapy will perform a different number of activities of daily living before and after group therapy. The researchers randomly selected 8 depressed clients in a 6-week group therapy program.

Use the five steps of hypothesis testing to determine whether the observed differences in the numbers of activities of daily living obtained before and after therapy are statistically significant at .05 level of significance. (Clearly list each step).

As part of Step 5, indicate whether the researchers should recommend group therapy for all depressed people based on evaluation of the null hypothesis.

Data to be entered in SPSS (instructions below)

CLIENT

BEFORE THERAPY

AFTER THERAPY

Step 1: Managing data

1. Open a blank SPSS data file: FileNewData

2. In the blank SPSS data file, create your SPSS data set by entering the number of activities of daily living performed by the depressed clients (see above) in the Data View window. Enter the “before therapy” scores in the first column and the “after therapy” scores in the second column.

3. In the Variable View window, change the variable name for the first variable to “ADLPRE” and the second variable to “ADLPOST.” Set the decimals for both variables to zero.

Step 2: SPSS execution

a. Click: Analyze Compare Means Paired-Samples t-Test use the arrow to move ADLPRE under “variable 1” inside Paired Variable(s) window and then use the arrow to move ADLPOST under “variable 2” inside Paired Variable(s) window.

b. Click OK.

t Test for Dependent Means

Paired Samples Test

Paired Differences

Sig. (2-tailed)

Mean

Std. Deviation

Std. Error Mean

95% Confidence Interval of the Difference

Lower

Upper

Pair 1

ADLPOST – ADLPRE

5.000

4.209

1.488

1.481

8.519

3.360

0.012

Conclusion:

1. 0.05 : as we can see that p value < 0.05, fail to accept Ho conclude that that mean number of activities performed by the depressed people before and after the group therapy are significantly different

2. 0.01 : as we can see that p value > 0.05, fail to accept Ho conclude that that mean number of activities performed by the depressed people before and after the group therapy are not significantly different

Recommendation: based on analysis the group therapy is recommendable for all the depressed people.

Mock Study 3: t-Test for Independent Samples (20 points)

3. Six months after an industrial accident, a researcher has been asked to compare the job satisfaction of employees who participated in counseling sessions with those who chose not to participate. The job satisfaction scores for both groups are reported in the table below.

Use the five steps of hypothesis testing to determine whether the job satisfaction scores of the group that participated in counseling session are statistically different from the scores of employees who chose not to participate in counseling sessions at .01 level of significance. (Clearly list each step).

As part of Step 5, indicate whether the researcher should recommend counseling as a method to improve job satisfaction following industrial accidents based on evaluation of the null hypothesis.

Data to be entered in SPSS (instructions below)

PARTICIPATED IN COUNSELING

DID NOT PARTICIPATE IN COUNSELING

Step 1: Data managing

1. Open a blank SPSS data file: File New Data

2. In the blank SPSS data file, create your SPSS data set by entering the number of activities of daily living performed by those who participated/did not participated in the counseling sessions (reported on previous page). Please create two columns. Column one is the test variable, where you enter ALL the 18 scores in the table. Column 2 is the grouping variable, where you use “1” to indicate if a score is from someone who participated in the counseling sessions; and “0” to indicate if a score is from someone who chose not to participate in the counseling sessions. The data set will look like this in SPSS Data View window:

36 1

49 1

…

…….

39 0

36 0

……….

3. After data entry, go to Variable View window, change the name of the first variable (test variable) to “ADL” and the second variable (grouping variable) as “group.” Set decimals for both variables to zero.

Step 2: SPSS execution

a. Click: Analyze Compare Means
Independent-Samples T Test use arrow to move ADL to “Test Variable” use arrow to move “group” to “Grouping Variable” when two (? ?) appear, click Define Groups. On the next pop up window, enter “1” for “Group 1” and “0” to “Group 2.”

b. Click OK.

. Restate the question as a research hypothesis and a null hypothesis about the populations.

Null Hypothesis: There is no difference between mean job satisfaction level of the employees who participated in counseling,
and those employees who did not participate in counseling.

Alternative Hypothesis: There is a significant difference between mean job satisfaction level of the employees who
Participated in counseling, and those employees who did not participate in counseling

2. Determine the characteristics of the comparison distribution.

Participated

Did not Participate

Sum

378

368

Mean

37.8

36.8

Estimated Pop variance (S² = Ʃ(X-M) ²/df)

4.84444

12.17778

Standard deviation √ S²

2.20101

3.489667

Pooled estimate of the pop variance S²pooled

6.39997

–

Pooled estimate standard deviation √ S²pooled

2.52982

–

Variance of distribution of means:
S²M1

0.639997

Variance of the distribution of differences between means S² difference

1.279994

–

Standard deviation of the distribution of differences between means S difference

1.131368198

–

t score

2.298

–

3. Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected.

4. Determine your sample’s score on the comparison distribution:

t = 2.298

5. Decide whether to reject the null hypothesis: Compare the scores from Steps 3 and 4 .

t= 2.298 is less than the critical value, accept null hypothesis. Conclude not

Evidence to suggest the researcher should recommend counseling as a method to improve job satisfaction following

Industrial accidents.

Estimated effect size = 1.02774 large effect

ANOVA (20 points)

Mock study 4

4. 15 clients are placed in three different groups. Clients in Group 1 receives 1 hour of therapy every 2 weeks; clients in Group 2 receives 1 hour of therapy every week; and clients in Group 3 receives 2 hours of therapy every week. Their number of daily activities are recorded in the table on the next page.

Use the five steps of hypothesis testing to determine whether the observed differences in the number of activities across three groups are statistically significant at .05 level of significance. (Clearly list each step).

As part of Step 5, indicate whether the researcher should recommend counseling based on evaluation of the null hypothesis.

Data to be entered in SPSS (instructions below)

GROUP 1

GROUP 2

GROUP 3

Step 1: Data managing

1. Open a blank SPSS data file: File New Data

2. In the blank SPSS data file, create your SPSS data set by entering the number of activities performed by the 15 clients. Please create two columns. Column one is the test variable where you enter ALL 15 scores in above table. Column 2 is the grouping variable, where you use “1” for “GROUP 1,” “2” for “GROUP 2,” and “3” for “GROUP 3.” The data set will look like this in SPSS Data View window:

16 1

15 1

……….

21 2

36 2

……….

24 3

21 3

……….

3. After data entry, go to Variable View window, change the name of the first variable (test variable) to “ADL” and the second variable (grouping variable) to “THERAPY.” Set decimals for both variables to zero.

Step 2: SPSS execution

a. Click: Analyze Compare Means One-Way ANOVA use arrow to move ADL to “Dependent Variable list” use arrow to move THERAPY to “Factor,” which instruct SPSS to conduct the analysis of variance on the number of activities performed by therapy type.

b. Click: Options Descriptive (to obtain descriptive statistics).

c. Click: Continue

d. Click: OK

Test Statistics: One Way ANOVA

Source of Variation

Sum of Square

d.f

Mean Sum of Square

P Value

Between

80.093

26.698

12.811

0.000

Within

41.679

2.084

Total

121.773

Effect Size = 0.5203

Conclusion: 0.001 < 0.05, reject null hypothesis conclude that there occurs a noteworthy variance among result of evidence by the behavioral scientists as supposed by the Judges, Attorneys, Jurors and Law Enforcement officials.

Additional question based on mock study 4

5. Describe the circumstances under which you should use ANOVA instead of t-Tests. Explain why t-Tests are inappropriate in these circumstances.

Chi-Square (20 points)

Mock study 5-1: Chi-Square Test for Goodness of Fit

6. The following table includes the primary method of conflict resolution used by 20 students.

Method

Aggressive

Manipulative

Passive

Assertive

N of Students

Following the five steps of hypothesis testing, conduct “goodness of fit” chi-square test to determine whether the observed frequencies in the four

cells

are significantly different from the expected frequencies at the .05 level of significance. (Clearly list each step).

As part of Step 5, indicate whether the observed frequency is significantly different from the expected frequency when equal number of students in each conflict resolution style (20/4=5) is assumed; and what does this mean in regard to this mock study.

Step 1: Data managing

1. Open a blank SPSS data file: File New Data

2. In the blank SPSS data file, please create just ONE column. This column stands for frequencies of different types of conflict resolutions. We’ll use “1” for “Aggressive,” “2” for “Manipulative,” 3 for “Passive,” and 4 for “Assertive.” The data set will look like this in SPSS Data View window:

1 (enter “1” for 8 times, since there are 8 observations)

…
2
2
3
3
4
4

…

3. After data entry, go to Variable View window, change the name of this variable to “STYLE.” Set decimal to zero.

Step 2: SPSS execution

a. Click: Analyze Non-Parametric Tests Legacy Dialogs Chi-Square use the arrow to move STYLE to “Test Variable list.”

· This procedure instruct SPSS that the chi-square for goodness of fit should be performed 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.

b. Click OK

Descriptive Statistics

Mean

Std. Deviation

Minimum

Maximum

Style

2.5000

1.39548

1.00

4.00

Style

Observed N

Expected N

Residual

Aggressive

5.0

3.0

Manipulative

5.0

-3.0

Passive

5.0

-3.0

Assertive

5.0

3.0

Total

Test Statistics

Style

Chi-Square

7.200a

Asymp. Sig.

.066

a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 5.0.

Mock study 5-2: Chi-Square Test for Independence

7. Next, researchers categorized the same group students in the previous study based on the primary method of conflict resolution used and whether that student had been suspended from school for misbehavior. These data are presented below.

Conflict Resolution Method

Suspended

Aggressive

Manipulative

Passive

Assertive

Total

Yes

Total

Following the five steps of hypothesis testing, conduct chi-square test for independence at the .05 level of significance. (Clearly list each step).

As part of Step 5, indicate whether the observed frequency is significantly different from the expected frequency; and what that means in regard to this mock study.

Step 1: Data managing

1. Continue to work on the data set created in Mock Study 5-1: goodness of fit Chi-square test

2. Add a second column to the data set. This column stands for whether or not a student was suspended from school due to misbehavior. We’ll use “1” for “Yes” and “2” for “No.” The data set will look like this in SPSS data view:

1 1

…

2 1

2 2

3 1

3 2

4 1

4 2

…

3. After data entry, go to Variable View window, change the name of this new variable to “SUSPEND.” Set decimal to zero.

Step 2: SPSS execution

a. Click: Analyze Descriptive Statistics Crosstabs use arrow to move “SUSPEND” to “Row(s)” use arrow to move “STYLE” to “Column(s).” (Recall in crosstab, DV is always in the row and IV is always in the column.)

b. Click: Statistics check “Chi-Square.”

c. Click: Continue.

d. Click: Cells check “Expected.”

e. Click: Continue.

f. Click: OK.

Additional question for mock study 5-2

8. Use SPSS to calculate the measure of association for variable “STYLE” and “SUSPEND.” Insert your SPSS output here. Use the concept of “Proportional Reduction of Error” to interpret your output.

–
=
cells
all
E
E
O
2
2
)
(
c

(A)

Myresearch questions

is: is to figure out what people in the particular social group think about suicide. In order for me to figure this out I had to look at social class and look.at both males and females in this claas.

(B)

1. 50 random people of the area

2. The general representation of the area

3. The much recourses required I can funding.

4. On the weekend at around the mall.

5. By meeting face to face and one by one

My IV(s): if you have multiple IVs, provide information for EACH IV using the format below.

IV Variable name in SPSS: I (Male) ii (female)

IV Question (as asked to the respondent verbatim) _____ Are you male or female?

IV Answer categories:

i) -male & ii – Female

IV Level of Measurement Nominal

My DV: only ONE DV is required for your final portfolio

DV variable name in SPSS: 0- Undecided, 1- Yes and 2- No

DV Question (as asked to the respondent verbatim)

Do you think a person has a right to end gender life if this person has an incurable disease?

DV Answer categories: Undecided, 1- Yes and 2- No

DV Level of Measurement: Nominal

(D)

Gender

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

29.0

56.90

58.00

Female

21.0

41.20

42.00

100.00

Total

50.0

98.00

100.00

Missing

System

2.0

Total

100.0

Suicide1

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Undecided

41.2

42.0

Yes

31.4

32.0

74.0

25.5

26.0

100.0

Total

98.0

100.0

Missing

System

2.0

Total

100.0

My respondents consisted of more males and females. Out of the 50 respondents, males were 29 while females were 21. Among all the respondents those undecided on whether people with incurable diseases should have a right to commit suicide or not were 21, those who said yes were 16 and those who said no were only 13.

]

(E)

Conclude form the graph above, plainly my respondents comprised of more male and females. Male were 58% while females were 42 % of aggregate respondents. Among every one of the respondents larger part were undecided on whether individuals with uncurable infections ought to have a privilege to confer suicide or not , this were nearly trailed by other people who said yes and the minority were the individuals who said no.

(F)

Option 1: Running measures of central tendency and dispersion

• [Running measures of central tendency and dispersion

i) Recoding

ii) Index construction

One should look over the procedures you explored about the topic you are thinking about in more greater detail. Outline your discoveries and glue all pertinent yield information here in this record.

My information that I provided is maximized and clearly coded and laid out I a way that we can enhance a conclusion by making a crossing and a arrangement to come out with data from both sides of the factors. The information that I provided here is ostensible by nature by saying that all measurements of focal inclination will have value

Be that as it may, for the variable suicide1 the modular class is undecided. This implies larger part of the respondents were undecided on whether individuals with incurable infections ought to have a privilege to confer suicide or not. For sex, the modular class was male, implying that dominant part of the respondents were male.]

(G)

Research hypothesis: My hypothesis is males and females regardless of social class differ on the topic of suicide

Null hypothesis: Are Males and females on the same page as it relates to the issues related specifically about suicide

___________________________________________________________

Your DV, Suicide1, will go into the ROW.

Your IV, Gender, , will go into the COLUMN.

[

Suicide1 * Gender Cross tabulation

Count

Gender

Total

Male

Female

Suicide1

Undecided

Yes

Total

According to the research above a particular class both male and female say that they are undecided if a person should terminate because of illness. In any case, with regards to the individuals who picked yes or no, a more noteworthy extent of females feel that at deaths door patients ought not have a privilege to submit suicide. This conclusion is not the same as the males since a more noteworthy bit of males trusts that the in critical condition patients ought to have a privilege to confer suicide. My hypothesis is hence right.

Epsilon

Epsilon abridges rate distinction in rows of crosstabs. It is figured by subtracting the biggest % and littlest %. Most analysts trust that a rate contrast of over 9 % demonstrates a solid connection between the factors being cross tabulated.

Suicide1 * Gender Cross tabulation

Gender

Epsilon

Male

Female

Suicide1

Undecided

% within Suicide1

52.4%

47.6%

% within Gender

37.9%

47.6%

9.7%

Yes

% within Suicide1

68.8%

31.3%

% within Gender

37.9%

23.8%

14.1%

% within Suicide1

53.8%

46.2%

% within Gender

24.1%

28.6%

4.5%

Total

% within Suicide1

58.0%

42.0%

% within Gender

100.0%

Average difference =9.43%

The distinction between rows is generally high and the normal contrast epsilon is high.

This implies there is a solid connection between the factors gender and Suicide1. This implies contemplations about suicide will be affected by ones gender orientation. My hypothesis is along these rows revise and is acknowledged. Conclusion: Males and females contrast on the issues related with suicide

My professor gave me an F on this paper. This is the one you had revised. I am on the verge of failing the course. Please help me. I need it in 1 hour time. See the attached paper you did. Plesae help me I give you all my work.

Professors feedback: “Hi Hussain, this is still not GSS data. Please redo your assignment using only GSS data that I showed you in lesson 1.

For assignment one: GSS DATASET 2012 info http://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M63&product_isbn_issn=9781285458854&chapter_number=0&resource_id=21&altname=2012%20GSS%20Data%20Sets Download it and it should be a whole lot easier. Don’t forget we’re on suicide and do a person social class determine their outlook on suicide.

Logins: Power2017 Login id: keelin.leger@mycampus.apus.edu login into: https://estore.onthehub.com/WebStore/Account/OrderDetails.aspx?o=5e429e3f-1fe0-e711-80fa-000d3af41938 Product key to get in is:415899f4f4b0e0abf028

This the link for GSS data. In it it shows the spss download as well. Make sure it’s 2012. Any. Questions I’m here to help. http://gss.norc.org/get-the-data

Please see the feedback from the professor: Hi Hussain, thank you for your second assignment. You forgot to attach your SPSS output. Are you using SPSS? Your assignment was not complete correctly”

See the paper attached that you did.

Download the spss with the following link for the following assignment please help me. I rely on you to do a lot of my assignments and more to come. This for assignment 2 Password: Power2017 Login id: keelin.leger@mycampus.apus.edu login into: https://estore.onthehub.com/WebStore/Account/OrderDetails.aspx?o=5e429e3f-1fe0-e711-80fa-000d3af41938 Product key to get in is:415899f4f4b0e0abf028

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