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FINAL EXAM 9

Final Exam

Name

Institution

Date

Introduction

Research questions are often the starting point towards finding answers to a multitude of different problems. Through this final exam, the researcher has been given the opportunity to formulate research questions, analyze the data provided and interpret the results using statistical techniques. Conclusions will then be drawn based on the data analysis results.

Research Scenario

The research scenario provided in this case involves an organization looking to know whether participants with varying levels of expertise can improve their knowledge after completing a training program. These include professionals, paraprofessionals, and nonprofessionals. The data collected included gender, age, type of training (professional, paraprofessional, or nonprofessional), location of the worksite (on-site or off-site) and years of experience. Furthermore, a pre-training test of knowledge, a training program, and post-training test of knowledge was developed. All participants selected to take part in the study were tested, and led to participate in the three-week training program, and then were tested again afterwards. Once this was done, several data sets were collected including a measure of participant confidence in knowledge and a certification exam score.

Story Created

Based on the information provided on the codebook, the story that is generated in this case will have the following as the problem statement. I will want to identify how demographic factors including gender, age and qualification affect the level of knowledge acquired on training to become a technician or consultant.

Indeed, it is true that demographic factors play a role in determining whether a person is ready to learn and whether that learning has a positive impact on their ability to eventually teach as a technician. For instance, technical jobs are often associated with the male gender as opposed to female gender. Age also tends to affect the level of experience a technician has or a consultant has which subsequently affects their ability to perform well even after training. Finally, the level of qualification also plays a role in determining whether the person will be able to acquire more during training to have a positive impact on their knowledge after learning. It follows therefore, that the dependent variable in this case will be the level of knowledge acquired adoring training and whether it was positive or not.

Research Objectives

i. To investigate the effect of gender on the level of knowledge acquired during training to become a technician or consultant

ii. To analyze whether age is a factor in as far as he acquisitions of knowledge to become a consultant technician is concerned

iii. To ascertain whether qualification affects the level of knowledge acquired after training to become a consultant/technician

Research questions

i. Does gender affect the level of knowledge acquired during training to become a technician or consultant?

ii. Is age a factor in as far as he acquisitions of knowledge to become a consultant// technician is concerned?

iii. How does qualification affect the level of knowledge acquired after training to become a consultant/technician?

Sample Description

In order to answer the research questions above, the researcher will select a sample from whom to collect data. This sample will comprise of a total of 61 individuals. Based on the research question and the scenario, the only demographic information that will be collected include age, gender and qualification. The dependent variable that will be collected will include Knowledge1 (scale) and Knowledge2 (scale). The frequency distribution is as indicated in below;

Gender

The study found that 50% of the respondents were male while the remaining 50% were female. This indicated that there was gender parity in the study. This information is indicated in the pie chart in figure 1.

Figure 1: Pie Chart Distinguishing Gender

The study also sought the age of the respondents. The information obtained was plotted on histogram and presented in figure 2. The average age was found to be 37 years.

Figure 2: Histogram Distinguishing Age of Respondents

On inquiring about their qualification, it was established that there were 20 professionals, 20 paraprofessionals and 20 nonprofessionals. This information is represented in the bar graph in figure 3 below.

To answer the research questions, several tests were conducted as necessary

i. Does gender affect the level of knowledge acquired during training to become a technician or consultant?

Group Statistics
	Gender	N	Mean	Std. Deviation	Std. Error Mean
knowledge1	male	30	37.63	5.744	1.049
	Female	30	39.33	4.943	.903
knowledge2	male	30	39.13	5.138	.938
	Female	30	41.30	5.107	.932

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
knowledge1	Equal variances assumed	1.864	.177	-1.229	58	.224	-1.700	1.384	-4.470	1.070
	Equal variances not assumed			-1.229	56.739	.224	-1.700	1.384	-4.471	1.071
knowledge2	Equal variances assumed	.033	.856	-1.638	58	.107	-2.167	1.323	-4.814	.481
	Equal variances not assumed			-1.638	57.998	.107	-2.167	1.323	-4.814	.481

ii. Is age a factor in as far as he acquisitions of knowledge to become a consultant// technician is concerned?

iii.

ANOVA
	Sum of Squares	df	Mean Square	F	Sig.
knowledge1	Between Groups	1013.483	26	38.980	1.850	.048
	Within Groups	695.500	33	21.076
	Total	1708.983	59
knowledge2	Between Groups	809.267	26	31.126	1.312	.229
	Within Groups	782.917	33	23.725
	Total	1592.183	59

iv. How does qualification affect the level of knowledge acquired after training to become a consultant/technician?

Correlation analysis

Correlations
	Gender	age	qualification	knowledge1	knowledge2
Gender	Pearson Correlation	1	.245	-.082	.159	.210
	Sig. (2-tailed)		.059	.535	.224	.107
	N	60	60	60	60	60
age	Pearson Correlation	.245	1	-.254*	.182	.338**
	Sig. (2-tailed)	.059		.050	.164	.008
	N	60	60	60	60	60
qualification	Pearson Correlation	-.082	-.254*	1	-.363**	-.456**
	Sig. (2-tailed)	.535	.050		.004	.000
	N	60	60	60	60	60
knowledge1	Pearson Correlation	.159	.182	-.363**	1	.646**
	Sig. (2-tailed)	.224	.164	.004		.000
	N	60	60	60	60	60
knowledge2	Pearson Correlation	.210	.338**	-.456**	.646**	1
	Sig. (2-tailed)	.107	.008	.000	.000
	N	60	60	60	60	60
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).

Regression Analysis

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.748a	.560	.537	7.262
a. Predictors: (Constant), qualification, Gender, age

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	3760.496	3	1253.499	23.770	.000b
	Residual	2953.154	56	52.735
	Total	6713.650	59
a. Dependent Variable: exam
b. Predictors: (Constant), qualification, Gender, age

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
	B	Std. Error	Beta
1	(Constant)	40.838	5.645		7.234	.000
	Gender	8.579	1.934	.406	4.435	.000
	age	.552	.112	.465	4.933	.000
	qualification	-2.340	1.187	-.181	-1.971	.054
a. Dependent Variable: exam

Please do this part:::Part V. Summarize your findings.

Synthesize the results of your five analyses. Include a brief summary of the sample characteristics and the major findings. Interpret the findings so that the organization’s leaders will have an understanding of the similarities and differences in knowledge, and how effective the training program is in improving knowledge.