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December 9, 2023

Is there a relationship among the variables measuring different aspects of client satisfaction?

Psychology

 

Please download the Week 7 assignment file and the data file you used last week. There are 2 research questions. For each one, describe in your Word document the application of the seven steps of the hypothesis testing model. Be sure to spend most of your time writing up Step 7, as the results are the most important piece. Make sure your text, tables, and figures are all following APA format.

Submit your Word document with your answers as well as all relevant tables and figures pasted into the Word document. You should also attach your SPSS output (.spv) file as backup documentation

  • attachment

    RSM701_Week7Assignment1.docx

  • attachment

    RSM701LOA4.sav

  • attachment

    RSM701LOA3_Output1.spv

  • attachment

    Week6assignmentfinal1.docx

Week 7 Assignment

Use the same data file you used in Weeks 5 and 6.

Question 1: Is there a relationship among the variables measuring different aspects of client satisfaction?

1. Run a Pearson correlation matrix using Intake Experience, Individual Counseling, Group Counseling, Fairness of Sliding Scale, Usage Level, Overall Satisfaction in January, and Overall Satisfaction in June. Use the command: Analyze->Correlate->Bivariate. You can put all the variables in at once which will generate a big correlation matrix. The default type of correlation is Pearson’s, which is what we are dealing with in this question.

2. Create a Scatterplot for the following pairs: (1) Intake Experience – Overall Satisfaction in June; and (2) Individual Counseling – Overall Satisfaction in June. You can generate scatterplots using the chart builder tool (Graphs->Chart Builder->Scatter/Dot)

3. Report the descriptive statistics, assumptions tests, as well as tests of statistical significance.

4. Write up the results and your figure in APA format. Make sure to include the following:

· What type of test did you use?

· What variables did you examine?

· What were your findings (please include r and p value)? Degrees of freedom (N-2) should also be included.

· Is there a weak, moderate, or strong correlation?

· What is the strongest pair? What is the weakest pair?

· For each pair, is the correlation statistically significant?

· What direction is the correlation?

· What do these results suggest?

Question 2: Alternatives to Pearson Correlation

1. Identify two variables not identified in Question 1 and report what type of correlation analysis you could do with this pair of variables.

2. Run the analysis and report the results.

,

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>GET   FILE='D:RSM701LOA3.sav'. DATASET NAME DataSet1 WINDOW=FRONT. ONEWAY Usage BY Preexist   /STATISTICS DESCRIPTIVES HOMOGENEITY WELCH   /PLOT MEANS   /MISSING ANALYSIS   /POSTHOC=TUKEY ALPHA(0.05).

00000000011_lightNotesData.bin

00000000013_lightTableData.bin

00000000014_lightTableData.bin

00000000015_lightTableData.bin

00000000016_lightTableData.bin

000000000171_lightTableData.bin

0000000001721_lightTableData.bin

000000000181_8463198971907538946_chartData.bin

000000000181_8463198971907538946_chart.xml

Type of Treatment Mean of Usage Level

outputViewer0000000001_heading.xml

Output Oneway 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>Oneway 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>[DataSet1]&nbsp;D:RSM701LOA3.sav Descriptives 00000000013_lightTableData.bin Test of Homogeneity of Variances 00000000014_lightTableData.bin ANOVA 00000000015_lightTableData.bin Robust Tests of Equality of Means 00000000016_lightTableData.bin Post Hoc 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>Post&nbsp;Hoc&nbsp;Tests Multiple Comparisons 000000000171_lightTableData.bin Homogeneous Subsets 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>Homogeneous&nbsp;Subsets Usage Level 0000000001721_lightTableData.bin Means Plots 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>Means&nbsp;Plots Usage Level 000000000181_8463198971907538946_chartData.bin 000000000181_8463198971907538946_chart.xml

outputViewer0000000002.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>UNIANOVA satjan BY Newpatient Court   /METHOD=SSTYPE(3)   /INTERCEPT=INCLUDE   /PLOT=PROFILE(Newpatient*Court Court*Newpatient) TYPE=LINE ERRORBAR=NO MEANREFERENCE=NO YAXIS=AUTO   /PRINT DESCRIPTIVE   /CRITERIA=ALPHA(.05)   /DESIGN=Newpatient Court Newpatient*Court.

00000000031_lightNotesData.bin

00000000032_lightTableData.bin

00000000033_lightTableData.bin

00000000034_lightTableData.bin

000000000351_8463199040627015682_chartData.bin

000000000351_8463199040627015682_chart.xml

Type of Patient Estimated Marginal Means Estimated Marginal Means of Overall Satisfaction in January Court Ordered Treatment

000000000352_8463199040627081218_chartData.bin

000000000352_8463199040627081218_chart.xml

Court Ordered Treatment Estimated Marginal Means Estimated Marginal Means of Overall Satisfaction in January Type of Patient

outputViewer0000000003_heading.xml

Output Univariate Analysis of Variance 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>Univariate&nbsp;Analysis&nbsp;of&nbsp;Variance Notes 00000000031_lightNotesData.bin Between-Subjects Factors 00000000032_lightTableData.bin Descriptive Statistics 00000000033_lightTableData.bin Tests of Between-Subjects Effects 00000000034_lightTableData.bin Profile Plots 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>Profile&nbsp;Plots Type of Patient * Court Ordered Treatment 000000000351_8463199040627015682_chartData.bin 000000000351_8463199040627015682_chart.xml Court Ordered Treatment * Type of Patient 000000000352_8463199040627081218_chartData.bin 000000000352_8463199040627081218_chart.xml

META-INF/MANIFEST.MF

allowPivoting=true

,

Week 6 Assignment

A Survey of 50 Clients

Fifty clients of LIGHT ON ANXIETY were surveyed regarding their satisfaction with services. The clients filled out the survey on completion of treatment in January. In June, the clients were telephoned and re-surveyed and were asked to rate their overall satisfaction again.

Variables in the Working File

Variable

Position

Label

Measurement Level

Description

Participantid

1

ID

Scale

Participant ID number

Intake

2

Intake experience

Scale

On a scale of 1 to 10, how would you rate the intake experience?

Indcouns

3

Individual Counseling

Scale

On a scale of 1 to 10, how would you rate your satisfaction with the individual counseling sessions?

Groupcouns

4

Group Counseling

Scale

On a scale of 1 to 10, how would you rate your satisfaction with the group counseling sessions?

Pricefair

5

Fairness of sliding scale

Scale

On a scale of 1 to 10, how would you rate your satisfaction with the sliding scale method of payment?

NewPatient

6

Type of Patient

Ordinal

0 = first time 1 = repeat admission

Usage

7

Usage Level

Scale

What percent of your mental health services are provided by this center?

Satjan

8

Overall Satisfaction in January

Scale

On a scale of 1 to 7, rate your overall satisfaction with your MHMR experience.

Satjun

9

Overall Satisfaction in June

Scale

On a scale of 1 to 7, rate your overall satisfaction with your MHMR experience.

Court

10

Court ordered treatment

Nominal

Was your treatment court-ordered?

0 = No; 1 = Yes

Therapytype

11

Individual or family therapy

Nominal

0 = Individual; 1 Family

Preexist

12

Pre-existing Condition

Nominal

1 = Mental health; 2 = Substance Abuse; 3 = Both

INSTRUCTIONS:

For each research question , describe in your word document the application of the seven steps of the hypothesis testing model.

Step 1: State the hypothesis (null and alternate)

Step 2: State your alpha (unless requested otherwise, this is always set to alpha = .05)

Step 3: Collect the data (use one of the data sets).

Step 4: Calculate your statistic and p value (this is where you run SPSS and examine your output files).

Step 5: Retain or reject the null hypothesis. (This is where you report the results of your analyses t (df) = t value, p = sig. level).

Step 6: Assess the Risk of Type I and Type II Error (did the data meet the assumptions of the statistic; effect size; and sample size).

Step 7: State your results in APA style and format. Be sure to report whether any assumptions were violated. Also report post-hoc test findings when the overall ANOVA is significant. Be sure to also include relevant figures.

Research Questions

Question 1: Are there differences in satisfaction with the intake process of clients who admit with pre-existing mental health problems, substance abuse problems, or both?

1. Run the One-Way ANOVA. Click on ANALYZE/COMPARE MEANS/ONE-WAY ANOVA

2. Use Preexisting condition (Preexist) as the independent variable.

3. Use Usage Level (Usage) as the dependent variable.

4. Select descriptive statistics. Under Options, check the boxes for homogeneity of variance test and Welch.

5. We can also get a graph of the means of our groups, if we click on OPTIONS and then MEANS PLOT in the next dialog box (note: it is interesting to see how SPSS will automatically generate the y-axis range according to the data, this feature can make a nonsignificant result look significant and a significant result look nonsignificant depending on your data).

6. Generate post-hoc comparison to evaluate the differences between groups. Click on Post-hoc and check the box next to Tukey.

Step 1: State the hypothesis (null and alternate)

· Null Hypothesis (H0): Clients with a history of mental health issues, drug addiction issues, or both reports no discernible differences in their level of satisfaction with the intake procedure.

· Alternate Hypothesis (H1): Clients with a history of mental health issues, drug addiction issues, or both reports significantly different levels of satisfaction with the intake procedure.

Step 2: State your alpha (unless requested otherwise, this is always set to alpha = .05)

· Alpha (α): 0.05

Step 3: Collect the data (use one of the data sets).

· Use the provided data set with variables Preexisting condition (Preexist) as the independent variable and Usage Level (Usage) as the dependent variable.

Step 4: Calculate your statistic and p-value (this is where you run SPSS and examine your output files).

Oneway

[DataSet1] D:RSM701LOA3.sav

Descriptives

Usage Level

N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Mean

Minimum

Maximum

Lower Bound

Upper Bound

Mental Health

18

35.833

5.1478

1.2134

33.273

38.393

25.0

43.0

Substance Abuse

18

45.444

4.7801

1.1267

43.067

47.822

36.0

53.0

Both

14

54.786

5.3086

1.4188

51.721

57.851

47.0

65.0

Total

50

44.600

9.0959

1.2863

42.015

47.185

25.0

65.0

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Test of Homogeneity of Variances

Levene Statistic

df1

df2

Sig.

Usage Level

Based on Mean

.046

2

47

.955

Based on Median

.059

2

47

.943

Based on the Median and with adjusted df

.059

2

46.733

.943