Hypothesis Testing Samples: Evaluating Counseling and Therapy Effects

Problem Description

In this hypothesis testing assignment, Explore the significance of statistical hypothesis testing through real-world scenarios. Investigate the impact of counseling on job satisfaction and the efficacy of group therapy in improving daily living activities. These case studies employ SPSS to provide practical insights into research methodologies and decision-making processes. Discover the critical role of hypothesis testing in statistical analysis.

Part 1: Does Counseling Improve Job Satisfaction?

This part of the assignment deals with the question of whether counseling has a positive impact on job satisfaction among employees following industrial accidents.

Hypothesis Testing:

Null hypothesis (Ho): Counseling doesn't affect the mean job satisfaction among employees. Alternative hypothesis (H1): Counseling increases the mean job satisfaction among employees.
Significance level: 0.01
The result of the SPSS:

group	N	Mean	Std . Deviation	Std . Error Mean
Group 1	10	38	2.261	0.715
Group 2	10	35.8	3.393	1.073

Table 1: Group statistics- result of SPSS

		Levene's Test Variances	for Equality of				t-settor Equality	of Means
		F	Sig	1	of	Sig (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Difference Lower	Interval of the Upper
JOBSAT	Equal variances assumed	1,337	263	1,706	18	105	2,200	1.289	-509	4,909
	Equal variances not assumed			1,706	15,676	108	2,200	1,289	-538	4.938

Table 2: Independent Samples Test results

The p-value of the test is: 0.053
The decision: Based on the p-value (0.053) and a significance level of 0.01, there is not sufficient evidence to support the claim that researchers should recommend counseling to improve job satisfaction.

Part 2: Does Group Therapy Improve ADL in Depressed People?

This part of the assignment explores whether group therapy has a significant impact on the Activities of Daily Living (ADL) for depressed individuals.

Hypothesis Testing:
Null hypothesis (Ho): Average ADL before and after the therapy is the same. Alternative hypothesis (H1): There is a difference in average ADL before and after the therapy.
Significance level: 0.05

The result of the SPSS:

Paired Samples Statistics

Pair 1	Mean	N	Std. Deviation	Std. Error Mean
ADLPRE	10.60	10	2.066	.653
ADLPOST	14.90	10	3.143	.994

Table 3: Results of the SPSS for Paired Samples Test

Paired Differences

Pair 1	Mean	Std. Deviation	Std. Error Mean	Lower	Upper	t	df	Sig. (2-tailed)
ADLPRE-ADLPOST	-4.300	3.199	1.012	-6.588	-2.012	-4.251	9	.002

Table 4: Results of the SPSS for Paired Differences

Mean ADL before therapy: 10.60

Mean ADL after therapy: 14.90

The p-value of the test is: 0.002
The decision: Since the p-value (0.002) is less than the significance level of 0.05, we reject the null hypothesis. Researchers should recommend group therapy for all depressed individuals as there is a significant difference in the average ADL before and after therapy.

Part 3: Evaluating the Effect of Group Therapy on Depressed Individuals

In this section, the aim is to determine whether group therapy significantly impacts the Activities of Daily Living (ADL) among depressed individuals.

Hypothesis Testing:

Null hypothesis (Ho): Average ADL after therapy is 15. Alternative hypothesis (H1): Average ADL after therapy is different from 15.
Significance level: 0.05
The result of the SPSS:

One-Sample Statistics

Activity	N	Mean	Std. Deviation	Std. Error Mean
ADL	20	16.65	4.557	1.019

Table 5: One- Sample Test

Test-Value= 15

Mean ADL after therapy: 16.65

The p-value of the test is: 0.122
The decision: Since the p-value (0.122) is greater than the significance level of 0.05, we fail to reject the null hypothesis. There is no sufficient evidence to indicate that behavioral scientists should not recommend group therapy to depressed individuals.

Part 4: Five step of hypothesis testing:

This section explores the effects of a new workplace intervention. The problem at hand is whether this intervention leads to a significant improvement in employee performance. Hypothesis testing will be conducted to assess if the new intervention has a positive impact on workplace productivity and whether it is a recommended strategy for enhancing employee performance.

1. Null hypothesis (Ho):

Alternative hypothesis(H1):

2. Significance level:

3. The result of the SPSS:

4. The p-value of the test is:

5. The decision:

Part 5: Five step of hypothesis testing:

In Part 5, we investigate the impact of a specific educational program on student outcomes. The problem revolves around determining whether this program positively affects student performance. Hypothesis testing will be employed to assess whether the educational program leads to significant improvements in student outcomes, and whether it should be recommended for broader implementation in the education system.