Psychology week 6 assignment

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.