Using the research scenario and variables identified in the codebook, create a “story” that describes the purpose and focus of the study. In a few short paragraphs describe the intent of your investigation in the form of a problem background and purpose statement.

Part II. Describe your sample.

Generate and interpret descriptive statistics of central tendencies, variability, skewness, and kurtosis for all quantitative variables and generate frequency tables for all categorical variables. Conclude with a paragraph summarizing the demographic characteristics of this sample, including whether or not the assumption of normality appears to be satisfied for the variables and why or why not.

Part III. Describe relationships among the variables.

Select the variables that are measured on interval or ratio scales or are dichotomous. Create a correlation matrix. Identify and discuss the strongest and weakest correlations.

Part IV. Answer FIVE of the seven following research questions.

Based on the research scenario and the data, formulate the appropriate alternative and null hypotheses, conduct a proper analysis, and interpret the results for each of the following.

1. Are on-site workers more knowledgeable than off-site workers before the training begins? Asked another way, what is the difference in knowledge between on-site and off-site workers before they take the training (i.e., preintervention knowledge)?

2. Does participants’ knowledge increase as a result of going through the training?

3. Do participants of different qualifications (professional, paraprofessional, and nonprofessional) perform differently on the certification exam? Which group performs best?

4. What is the effect of gender and worksite location (on- or off-site) on level of confidence? In other words:

a. Are men or women more confident?

b. Does type of worksite experience impact confidence?

c. Is there an interaction between gender and worksite in their effect on confidence?

5. Which group shows the greatest improvement in learning (from before to after the intervention)—professionals, paraprofessionals, or non-professionals?

6. Does age have an impact (i.e., predict) performance on the certification exam?

7. In addition to age, do any of the other variables (years of experience or confidence) improve the ability to predict performance on the certification exam?

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.

IV. Project Grading: 300 points.

Ha : There is a difference between the level of knowledge for the offsite worker versus an onsite worker after training begins.

The independent test reflects that the mean is 38.10 for knowledge before training and 38.87 for knowledge after training, and the two-tailed significance results are the same at .586. Per the Independent t-test provided below, the results support there is no difference between the onsite workers not being more knowledgeable than offsite workers after the training begins. Because there is no significant difference in the outcomes for onsite and offsite after the training is complete, the p-value is .112, which is greater than the .005, indicating the null cannot be rejected.

2. Does participants’ knowledge increase as a result of going through the training?

H0 : There is no increase in knowledge as a result of training completion

Ha : There is an increase in knowledge as a result of training completion

The paired t-test supports the mean is 38.38 before training and 40.22 after training for increased knowledge after training; The completed paired independent t-test provided below helps that there is an increase in knowledge after training has been completed. The difference in the knowledge after training is supported by the p-value is .004, which is less than 0.05, allowing the rejection of the null.

3. Do participants of different qualifications (professional, paraprofessional, and nonprofessional) perform differently on the certification exam? Which group performs best?

H0 : There is no significant exam performance qualification difference between the three types of professionals.

The Factorial ANOVA test reflects a significate difference between groups. There is a difference between paraprofessional and Nonprofessional. Professional and nonprofessional, and professional and paraprofessional. The p-value for all groups is less than 0.05, which means the null can be rejected.

4. Does age have an impact (i.e., predict) performance on the certification exam?

H0 : Age is not a predictor of certification exam performance.

Ha : Age is a predictor of certification exam performance.

The simple regression test reflects the coefficient and the ANOVA at 0.00 and the p-value of 0.00, which supports a rejection of the null. The test supports age as a predicting factor on performance exams, with the mean at 35.38, the exam at 69.65, and the standard deviation at 8.988 for age and the exam at 10.667. 

5. In addition to age, do any of the other variables (years of experience or confidence) improve the ability to predict performance on the certification exam?

H0 : Age is not a predictor of certification exam performance.

Ha : Age is a predictor of certification exam performance.

H0 : Years of experience is not a predictor of certification exam performance.

Ha : years of experience is a predictor of certification exam performance.

The multi-regression test supports that in addition to age having an impact on exam performance, years of experience also have an impact on prediction performance on exams. The mean is 69.65 for exams, 37.38 for age, and 5.87 for years of experience. The standard deviation for the exam is 10.667, age is 8.988, and years of experience is 4,.438. The significance is 0.00, which supports the p-value being less than 0.05, allowing rejection of the null.

References

McClave, J., Benson, G., & Sincich, T., (2022). Statistics for Business and Economics (14th ed.). Boston: Pearson Education, Inc. 978-0-321-82623-7.