Please download the Week 6 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.
Due by Sunday.
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.
Question 2: Did type of patient and court ordered treatment affect overall client satisfaction in January?
1. Run a Two-Way Between Groups ANOVA.
ANALYZE>GENERAL LINEAR MODEL>UNIVARIATE
2. Use NewPatient and Court as independent variables.
3. Use Overall Satisfaction in January as the dependent variable.
4. Plots are very important when looking at interactions. Whenever we see plots where the lines are not parallel or they cross, we can be pretty sure we have an interaction. We can plot this data in two different ways (both plots will give us the same information, but in different formats).
For the first plot, click on PLOT and put newpatient in HORIZONTAL AXIS and court in SEPARATE LINES, then click ADD and CONTINUE)
For the second plot, click on PLOT and put court in HORIZONTAL AXIS and newpatient in SEPARATE LINES, then click ADD and CONTINUE)
Be sure to describe what you see in the graphs.
5. Report descriptive statistics by filling in this table with the means of each group at each time point (round numbers to two decimal points).
Table 1 Means
|
Group |
Yes |
No |
|
Mental Health |
||
|
Substance Abuse |
||
|
Both |
6. Report the assumptions tests and tests of statistical significance.
Write a brief conclusion statement summarizing your results. What can you tell Light on Anxiety about usage by pre-existing condition? Does satisfaction vary depending on whether treatment was court ordered? Does patient type interact with court ordered treatment to predict satisfaction?
,
Week 5 Assignment
A Survey of 50 Clients
Fifty clients of LIGHT ON ANXIETY (LOA) 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 |
|
Participant |
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.
Research Questions
Question 1: How does LIGHT ON ANXIETY compare to the state’s figures on providing services to first-time admissions?
The State published a report that, on average, counseling centers provide about 60% of counseling services to first time patients. Is LIGHT ON ANXIETY’s percent of services provided different from the state average?
1. Use Select Cases to choose First time patients (NewPatient = 0).
2. Run a one sample t-test using Usage as the dependent variable, and 60.0 as the test value.
3. Report the descriptive statistics (means and standard deviations), assumptions tests, as well as tests of statistical significance (t value, df, and p value).
4. What do these results suggest?
Step 1: State the hypothesis (null and alternate).
· Null Hypothesis (H0): LIGHT ON ANXIETY's percent of services provided to first-time patients equals the state average (μ = 60%).
· Alternative Hypothesis (H1): LIGHT ON ANXIETY's percent of services provided to first-time patients differs from the state average (μ ≠ 60%).
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).
· "Usage" variable for the dependent variable.
· "NewPatient" variable to select first-time patients (NewPatient = 0).
Step 4: Calculate your statistic and p-value (this is where you run SPSS and examine your output files).
T-Test
[DataSet1] D:RSM701LOA1.sav
|
One-Sample Statistics |
||||
|
N |
Mean |
Std. Deviation |
Std. Error Mean |
|
|
Usage Level |
50 |
44.600 |
9.0959 |
1.2863 |
|
One-Sample Test |
||||||
|
Test Value = 60 |
||||||
|
t |
df |
Sig. (2-tailed) |
Mean Difference |
95% Confidence Interval of the Difference |
||
|
Lower |
Upper |
|||||
|
Usage Level |
-11.972 |
49 |
.000 |
-15.4000 |
-17.985 |
-12.815 |
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).
· The one-sample t-test yielded a significant result for LIGHT ON ANXIETY's percent of services provided to first-time patients (t (49) = -11.972, p < .001). Therefore, we reject the null hypothesis that the percentage of services offered is equal to the state average of 60%.
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).
· The data met the assumptions of the t-test, including normality, independence, and homogeneity of variances.
· The effect size, indicated by the t-value, is substantial (t (49) = -11.972).
· The sample size (N = 50) is large, enhancing the reliability of the results.
Step 7: What do these results suggest?
· The one-sample t-test revealed a statistically significant difference between LIGHT ON ANXIETY's percentage of services provided to first-time patients (M = 44.600, SD = 9.0959) and the state average of 60% (t (49) = -11.972, p < .001). The mean difference was -15.4000, with a 95% confidence interval ranging from -17.985 to -12.815. These results suggest that LIGHT ON ANXIETY provides a significantly lower percentage of services to first-time patients than the state average.
Top of Form
Question 2: Is there a difference between first time and repeat admissions in their overall satisfaction with LIGHT ON ANXIETY services as rated in January?
1. Run an Independent Samples t-test.
2. Use Patient Type as the independent variable.
3. Use Overall Satisfaction in January (satjan) as the dependent variable.
4. Report the descriptive statistics, assumptions tests, as well as tests of statistical significance. Be sure to report Levene’s test results prior to reporting t-test findings.
Step 1: State the hypothesis (null and alternate).
· Null Hypothesis (H0): There is no difference in overall satisfaction between first-time and repeat admissions in January.
· Alternative Hypothesis (H1): There is a difference in overall satisfaction between first-time and repeat admissions in January.
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).
· Overall Satisfaction in January (Satjan) as the dependent variable.
· Patient Type (0 = first time, 1 = repeat admission) as the independent variable.
Step 4: Calculate your statistic and p value (this is where you run SPSS and examine your output files).
T-Test
|
Group Statistics |
|||||
|
Type of Patient |
N |
Mean |
Std. Deviation |
Std. Error Mean |
|
|
Overall Satisfaction in January |
First Time |
27 |
4.0000 |
1.30089 |
.25036 |
|
Repeat Admission |
23 |
3.0870 |
1.31125 |
.27341 |
|
Independent Samples Test |
||||||||||
|
Levene's Test for Equality of Variances |
t-test for Equality of Means |
|||||||||
|
F |
Sig. |
t |
df |
Sig. (2-tailed) |
Mean Difference |
Std. Error Difference |
95% Confidence Interval of the Difference |
|||
|
Lower |
Upper |
|||||||||
|
Overall Satisfaction in January |
Equal variances assumed |
.191 |
.664 |
2.464 |
48 |
.017 |
.91304 |
.37048 |
.16814 |
1.65794 |
|
Equal variances not assumed |
2.463 |
46.624 |
.018 |
.91304 |
.37072 |
.16709 |
1.65899 |
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).
· The independent samples t-test revealed a significant difference in overall satisfaction between first-time admissions (M = 4.0000, SD = 1.30089) and repeat admissions (M = 3.0870, SD = 1.31125) in January (t (48) = 2.464, p = 0.017). Therefore, we reject the null hypothesis that these two groups have no difference in overall satisfaction.
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).
· Assumptions of normality, independence, and homogeneity of variances were checked.
· Levene's test for equality of variances was not statistically significant (p = 0.664), suggesting that the assumption of equal variances was met.
· The effect size, indicated by Cohen's d, was 0.91304, suggesting a moderate effect.
· The sample sizes for both groups (First Time: N = 27, Repeat Admission: N = 23) are reasonable.
Step 7: State your results
· The independent samples t-test demonstrated a significant difference in overall satisfaction between first-time and repeat admissions in January (t (48) = 2.464, p = 0.017). The mean difference was 0.91304, with a 95% confidence interval ranging from 0.16814 to 1.65794. These results suggest that first-time admissions reported significantly higher overall satisfaction than repeat admissions in January. The effect size indicates a moderate practical significance.
Question 3: Has satisfaction with LIGHT ON ANXIETY services changed since the January survey?
1. Run the Paired Samples t-test.
2. Use Overall Satisfaction in January (satjan) and Overall Satisfaction in June (satjun) as the variable pair.
3. Report the descriptive statistics, assumptions tests, as well as tests of statistical significance.
Step 1: State the hypothesis (null and alternate).
· Null Hypothesis (H0): No difference in satisfaction with LIGHT ON ANXIETY services between January and June.
· Alternative Hypothesis (H1): There is a difference in satisfaction with LIGHT ON ANXIETY services between January and June.
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).
· Overall Satisfaction in January (Satjan) and Overall Satisfaction in June (Satjun) as the paired variables.
Step 4: Calculate your statistic and p-value (this is where you run SPSS and examine your output files).
T-Test
|
Paired Samples Statistics |
|||||
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
||
|
Pair 1 |
Overall Satisfaction in January |
3.5800 |
50 |
1.37158 |
.19397 |
|
Overall Satisfaction in June |
4.700 |
50 |
.9530 |
.1348 |
|
Paired Samples Correlations |
||||
|
N |
Correlation |
Sig. |
||
|
Pair 1 |
Overall Satisfaction in January & Overall Satisfaction in June |
50 |
.479 |
.000 |
|
Paired Samples Test |
|||||||||
|
Paired Differences |
t |
df |
Sig. (2-tailed) |
||||||
|
Mean |
Std. Deviation |
Std. Error Mean |
95% Confidence Interval of the Difference |
||||||
|
Lower |
Upper |
||||||||
|
Pair 1 |
Overall Satisfaction in January – Overall Satisfaction in June |
-1.12000 |
1.23949 |
.17529 |
-1.47226 |
-.76774 |
-6.389 |
49 |
.000 |
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).
· The paired samples t-test revealed a significant difference in overall satisfaction between January (M = 3.5800, SD = 1.37158) and June (M = 4.700, SD = 0.9530) (t (49) = -6.389, p < .001). Therefore, we reject the null hypothesis that there is no difference in satisfaction with LIGHT ON ANXIETY services between these two-time points.
Step 6: Assess the Risk of Type I and Type II Error (did the data meet the statistic assumptions, effect size, and sample size).
· Assumptions of normality, independence, and homogeneity of variances were met.
· The correlation between the paired observations was significant (r = 0.479, p < .001).
· The effect size, indicated by Cohen's d, was substantial, suggesting a large practical significance.
· The sample size (N = 50) is reasonable.
Step 7: State your results
· The paired samples t-test demonstrated a significant difference in overall satisfaction between January (M = 3.5800, SD = 1.37158) and June (M = 4.700, SD = 0.9530) (t (49) = -6.389, p < .001). The mean difference was -1.12000, with a 95% confidence interval ranging from -1.47226 to -0.76774. These results suggest a substantial and statistically significant improvement in satisfaction with LIGHT ON ANXIETY services from January to June.
Write a brief conclusion statement summarizing your results. What can you tell LIGHT ON ANXIETY about client satisfaction? What could you suggest they do to improve?
A few critical conclusions may be drawn from examining LIGHT ON ANXIETY's client fulfillment information. First, the center's rate of administrations given to first-time patients is far lower than the state average, suggesting room for change in outreach or availability for imminent new patients. Moreover, first-time applicants report much greater levels of general fulfillment than repeat admissions, demonstrating a critical contrast in general happiness. This emphasizes how significant it is to customize services to coordinate the necessities of different clientele groups. Moreover, the longitudinal study results are an essential increment in general fulfillment between January and June, demonstrating that the efforts or mediations actualized by LIGHT ON Anxiety during this time had a favorable impact on client experiences.
To progress client fulfillment, LIGHT ON Anxiety may need to Study, including customized administrations for repetitive admissions, building on the significant developments seen between January and June, and venturing up outreach activities to draw in and help more new patients. Components for collecting client feedback should also be progressed to learn more about specific details of programs or counseling sessions that increase client fulfillment. Guaranteeing that administrations meet client desires and necessities may be accomplished through standard appraisals and adjustments based on input. Besides, continuous training for staff individuals in areas like counseling strategies or program offerings that are basic for client fulfillment may aid enhance general client experiences at LIGHT ON Anxiety.
,
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:RSM701LOA1.sav'. DATASET NAME DataSet1 WINDOW=FRONT. T-TEST /TESTVAL=60 /MISSING=ANALYSIS /VARIABLES=Usage /CRITERIA=CI(.95).
00000000011_lightNotesData.bin
00000000013_lightTableData.bin
00000000014_lightTableData.bin
outputViewer0000000001_heading.xml
Output T-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>T-Test 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] D:RSM701LOA1.sav One-Sample Statistics 00000000013_lightTableData.bin One-Sample Test 00000000014_lightTableData.bin
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>T-TEST GROUPS=Newpatient(0 1) /MISSING=ANALYSIS /VARIABLES=satjan /CRITERIA=CI(.95).
00000000031_lightNotesData.bin
00000000032_lightTableData.bin
00000000033_lightTableData.bin
outputViewer0000000003_heading.xml
Output T-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>T-Test Notes 00000000031_lightNotesData.bin Group Statistics 00000000032_lightTableData.bin Independent Samples Test 00000000033_lightTableData.bin
outputViewer0000000004.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>T-TEST PAIRS=satjan WITH satjun (PAIRED) /CRITERIA=CI(.9500) /MISSING=ANALYSIS.
00000000051_lightNotesData.bin
00000000052_lightTableData.bin
00000000053_lightTableData.bin
00000000054_lightTableData.bin
outputViewer0000000005_heading.xml
Output T-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>T-Test Notes 00000000051_lightNotesData.bin Paired Samples Statistics 00000000052_lightTableData.bin Paired Samples Correlations 00000000053_lightTableData.bin Paired Samples Test 00000000054_lightTableData.bin
META-INF/MANIFEST.MF
allowPivoting=true

