An organization wants to know if participants with varying levels of expertise (professionals, paraprofessionals, and nonprofessionals) improve their knowledge after completing a tra
I am only responsible for doing Part II. Well actually I said I would do the whole second page ask questions if necessary. The second attachment is the part that comes after mines so you can use this as a reference. The third attachment is the data.
DBA 736—Final Project |
5 |
DBA 736—Final Project
The purpose of this project is to give you the opportunity to formulate research questions, run the analyses, and interpret the results of the statistics that were covered in this class. The database is posted in the D2L file: DBA736Final.sav. This project should be submitted to me via the D2L Dropbox no later than 11:59 PM on Sunday of Module 7 as a single Microsoft Word document. The document must be in APA format (with the exception that you may just copy and paste tables from SPSS into this document, as long as you adjust them, if necessary to fit on the page).
Please read through the entire instructions before beginning.
The project is organized into three sections
I. The research scenario—to provide the context for the data. Please note that this is “content-neutral”, i.e., that it does not refer to a specific discipline or field.
II. The codebook—this identifies the variables (names, labels, and measurement scale) in the database.
III. The project instructions—for completing the project. Be sure to read each question carefully and answer each question completely.
I. Research Scenario:
An organization wants to know if participants with varying levels of expertise (professionals, paraprofessionals, and nonprofessionals) improve their knowledge after completing a training program.
The organization collected demographic information: gender, age, type of training (professional, paraprofessional, or nonprofessional), location of the worksite (on-site or off-site) and years of experience.
A pretraining test of knowledge, a training program, and posttraining test of knowledge was developed. Participants were tested, then participated in the three-week training program, and then were tested again.
The dataset also includes (1) a measure of participant confidence in knowledge and (2) a certification exam score.
The data are discipline-neutral. Therefore, part of your final project is to create a context for the research that is associated with your discipline or area of interest.
II. Codebook
Variable Information
Variable |
Label |
Measurement Scale |
Category Name |
ID |
N/A |
N/A |
N/A |
Gender |
Gender |
Nominal |
0 = Male 1 = Female |
age |
Age in Years |
Ratio |
|
qualification |
Professional Qualification |
Nominal |
0 = Professional 1 = Paraprofessional 2 = Nonprofessional |
worksite |
Location of Work |
Nominal |
0 = On-Site 1 = Off-Site |
knowledge1 |
Level of knowledge before Training |
Interval |
N/A |
knowledge2 |
Level of knowledge after Training |
Interval |
N/A |
years |
Years of Experience |
Ratio |
N/A |
confidence |
Confidence in knowledge |
Interval |
N/A |
exam |
Certification exam |
Interval |
N/A |
III. Project Instructions
Overview
Your task is to review the dataset, formulate a context, and then use your knowledge of statistics to answer the research questions and test hypotheses that will help the organization evaluate the effectiveness of the program.
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.
Points |
Part |
30 points 10 = problem background described 10 = purpose described 5 = relevance to field of study 5 = APA format and writing style |
Part I. Create your context. |
80 points 5 = Gender 10 = Age 5 = qualification 5 = worksite 10 = knowledge1 10 = knowledge2 10 = years 10 = confidence 10 = exam 5 = APA format and writing style |
Part II. Describe your sample. |
25 points 10 = identify and discuss strong positive and negative correlations. 10 = identify and discuss weak positive and negative correlations. 5 = APA format and writing style |
Part III. Describe relationships among the variables. |
125 points for five questions. Each question worth 25 points. 25 = Correct hypothesis 25 = Correct choice of statistical technique 25 = Correct tables 25 = Correct summary and interpretation 25 = APA format and writing style |
Part IV. Answer FIVE of the seven following research questions. |
40 points 5 = Summarize findings 15 = Describe and interpret sample characteristics and differences in knowledge 15 = Interpret results in terms of program effectiveness 5 = APA format and writing style |
Part V. Summarize your results |
,
Part III. Describe relationships among the variables.
According to the research, the general concept for relationship variables is the “science of collecting, classifying, analyzing, and interpreting information” (McClave et al., 2022. Pg 4).
However, according to the research, the relationship between variables can be described as limitless possible caparison using various scales and tests to provide information and support related to a hypothesis theory. Variable relationships can only be authentic and supported if the information solicited is vital and used correctly in its testing methods. According to the research, variable relationships can be considered a form of analytical theory concepts.
Create a correlation matrix. Identify and discuss the strongest and weakest correlations.
The variables selected for the correlation matrix are Scaled. The comparison used is a scale rating of 1 compared to the correlations related to week and most vital.
Based on the measured intervals for scales, there is a strong correlation between age and years of experience at the .639 interval, years of knowledge before training, and years of knowledge after training at the .646 interval. The weakest correlation presented using scales as the intervals are I.D. with confidence at a -.057 and I.D. and knowledge before training with a .007.
Part IV. (Answer FIVE) – 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)?
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.
Ha : There is a 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.
ANOVA |
||||||
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
1 |
Regression |
2498.802 |
1 |
2498.802 |
34.386 |
.000b |
Residual |
4214.848 |
58 |
72.670 |
|||
Total |
6713.650 |
59 |
||||
a. Dependent Variable: Certification Exam |
||||||
b. Predictors: (Constant), Age |
Coefficients |
||||||
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
B |
Std. Error |
Beta |
||||
1 |
(Constant) |
42.582 |
4.745 |
8.973 |
.000 |
|
Age |
.724 |
.123 |
.610 |
5.864 |
.000 |
|
a. Dependent Variable: Certification Exam |
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.
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