RMPP#8
2
2
Sun Coast
Charles Bunn
Columbia Southern University
Research Methods (MBA 5652)
Janice Carter-Steward
March 26, 2022
Table of Contents
Title Page……………………………………………………………………………………….pg1
Table of Contents……………………………………………………………………………….pg2
Executive Summary…………………………………………….………………………………pg3
Introduction……………………………………………………………………….…………….pg3
Statement of the Problems…………………………….…………………………………...…...pg4
Literature Review………………………………………………………………………………pg6
Research Objectives……………………………………………………………………………pg8
Research Questions and Hypotheses……………………………………..…………………….pg8
Research Methodology, Design, and Methods………………………………………………..pg10
Research Methodology
Research Design
Research Methods
Data Collection Methods
Sampling Design
Data Analysis Procedures
Data Analysis: Descriptive Statistics and Assumption Testing……………...………………..pg13
Data Analysis: Hypothesis Testing……………………………………………………………pg29
Findings…………………………………………………………………………………...…..pg34
Recommendations……………………………………………………………………….…….pg35
References……………………………………………………………………………………..pg37
Executive Summary
Sun Coast is an organization which is faced by various problems regarding particulate matter pollution, effectiveness of safety training and new employee training among many other challenges which the organization is facing. This paper is a research paper where there is six sets of hypotheses and research objectives which are being investigated. The method which is used for hypothesis testing is excel where the provided Sun Coast data was used in assessing the hypotheses. Additionally, the data was analyzed using the excel tool and various findings have been included regarding the relationship which exists between different variables. At the end of the paper is a set of recommendations which are based on the findings from statistical analysis together with the research done from the various sources.
Introduction
Senior leadership at Sun Coast has identified several areas for concern that they believe could be solved using business research methods. The previous director was tasked with conducting research to help provide information to make decisions about these issues. Although data were collected, the project was never completed. Senior leadership is interested in seeing the project through to fruition. The following is the completion of that project, and includes statement of the problems, literature review, research objectives, research questions and hypotheses, research methodology, design, and methods, data analysis, findings, and recommendations.
Statement of Problems
Six business problems were identified:
Particulate Matter (PM)
There is a concern that job-site particle pollution is adversely impacting employee health. Although respirators are required in certain environments, particulate matter (PM) varies in size depending on the project and job site. PM between 10 and 2.5 microns can float in the air for minutes to hours (e.g., asbestos, mold spores, pollen, cement dust, fly ash), while PM less than 2.5 microns can float in the air for hours to weeks (e.g., bacteria, viruses, oil smoke, smog, soot). Due to the smaller size of PM less than 2.5 microns, it is potentially more harmful than PM between 10 and 2.5 since the conditions are more suitable for inhalation. PM less than 2.5 are also able to be inhaled into the deeper regions of the lungs, potentially causing more deleterious health effects. It would be helpful to understand if there is a relationship between PM size and employee health. PM air quality data have been collected from 103 job sites, which is recorded in microns. Data are also available for average annual sick days per employee per job-site.
Safety Training Effectiveness
Health and Safety training is conducted for each new contract that is awarded to Sun Coast. Data for training expenditures and lost-time hours were collected from 223 contracts. It would be valuable to know if training has been successful in reducing lost-time hours and, if so, how to predict lost-time hours from training expenditures.
Sound-Level Exposure
Sun Coast’s contracts generally involve work in noisy environments due to a variety of heavy equipment being used for both remediation and the clients’ ongoing operations on the job sites. Standard earplugs are adequate to protect employee hearing if the decibel levels are less than 120 decibels (dB). For environments with noise-levels exceeding 120 dB, more advanced and expensive hearing protection is required, such as earmuffs. Historical data have been collected from 1,503 contracts for several variables that are believed to contribute to excessive dB levels. It would be important if these data could be used to predict the dB levels of work environments before placing employees on-site for future contracts. This would help the safety department plan for procurement of appropriate ear protection for employees.
New Employee Training
All new Sun Coast employees participate in general health and safety training. The training program was revamped and implemented six months ago. Upon completion of the training programs the employees are assessed on their knowledge. Test data are available for two Groups; a) Group A employees who participated in the prior training program, and b) Group B employees who participated in the revised training program. It is necessary to know if the revised training program is more effective than the prior training program.
Lead Exposure
Employees working on job sites to remediate lead must be monitored. Lead levels in blood are measured as micrograms of lead per deciliter of blood (μg/dL). A base-line blood test is taken pre-exposure and post-exposure at the conclusion of the remediation. Data are available for forty-nine employees who recently concluded a two-year-long lead remediation project. It is necessary to determine if blood lead levels have increased.
Return-On-Investment
Sun Coast offers four lines-of-service to their customers, including air monitoring, soil remediation, water reclamation, and health and safety training. Sun Coast would like to know if each line of service offers the same return-on-investment. Return-on-investment data are available for air monitoring, soil remediation, water reclamation, and health and safety training projects. If return-on-investment is not the same for all lines of service, it would be helpful to know where differences exist.
Literature Review
Particulate Matter Article
Yao, Y., Pan, J., Wang, W., Liu, Z., Kan, H., Meng, X., & Wang, W. (2020). Spatial correlation
of particulate matter pollution and death rate of COVID-19. MedRxiv.
This article is a correlation analysis of the particulate matter pollution and death rate in the context of the ongoing COVID-19 pandemic. All the report authors are members of the School of Public Health, Fudan University, Shanghai, and have a Ph.D. in public health-related courses. The purpose of the study was to determine the relationship between exposure to particulate matter, worsening of health, and incidences of death among the patients. The methodology used in cross-sectional analysis and the study results is that the patients’ death rate was associated with particulate matter regardless of the location of the patients.
Safety Training Effectiveness Article
Sharma, R., & Mishra, D. K. (2020). The role of safety training in original equipment
impacts companies on employee perception of knowledge, towards, and safety, and safe work environment. International Journal of Safety and Security Engineering, 10(5), 689-698.
The article’s authors are the Symbiosis Institute of International Business, Symbiosis International (Deemed University). The data collection was done using surveys, and the data was analyzed using SPSS. The research findings show a positive correlation between safety training and learning. If Sun Coast wants to enhance the preparedness of the staff, they can do so through safety training.
Sound-Level Exposure Article
Kou, L., Kwan, M., & Chai, Y. (2021). Living with urban sounds: Understanding the
effects of human mobilities on personal sound exposure and psychological health. Geoforum, 126, 13-25. https://doi.org/10.1016/j.geoforum.2021.07.011
The purpose of the research is to look at the effect of sound exposure on the health of individuals in urban centers. The data collection was done through in-depth interviews, after which data analysis was done to establish the relationship between the variables. The research design for the study was exploratory. The findings show that the people in the urban centers go through psychological stress because of exposure to elevated levels of sound—the authors of the article work in the School of Tourism Management, Sun Yat-sen University, Guangzhou.
New Employee Training Article
Laing, I. F. (2021). The impact of training and development on worker performance and
productivity in public sector organizations: A case study of Ghana Ports and Harbours Authority. International Research Journal of Business and Strategic Management, 2(2).
The purpose of the article was to establish whether training new employees impacts productivity. The findings show that the employees who go through training are more productive than those who do not because they get familiarized with the company policies and procedures. This finding can be applied in the Sun Coast case to encourage the training of the inexperienced staff on their safety in the workplace and what is expected of them at work. The article’s author has a Bachelor of Science in Human Resource Management.
Lead Exposure Article
Reuben, A., Schaefer, J. D., Moffitt, T. E., Broadbent, J., Harrington, H., Houts, R. M., ...
& Caspi, A. (2019). Association of childhood lead exposure with adult personality traits and lifelong mental health. JAMA Psychiatry, 76(4), 418-425.
The authors of the article are psychiatrists by profession. The report looks at exposure to lead on children’s health even later in life. The study was a cohort study done on the individuals born between April 1, 1972, and March 31, 1973. The study results show that lead exposure affects the long-term mental health of the patients. This means that it is essential that Sun Coast ensure that the lead exposure is minimized to avoid long-term mental impact on individuals.
Return on Investment Article
Fajaria, A. Z., & Isnalita, N. I. D. N. (2018). The effect of profitability, liquidity, leverage
and firm growth of firm value with its dividend policy as a moderating variable. International Journal of Managerial Studies and Research (IJMSR), 6(10), 55-69.
The article looks at how the ROI and other profitability metrics increase the value of a firm. The study shows that companies with a higher ROI have a high value. The authors of the article are in the school of business Airlangga University. The findings can help increase ROI in Sun Coast to increase the value of the company to make it attractive to potential investors.
Research Objectives, Research Questions, and Hypotheses
Ha1: There is a statistically significant relationship between particulate matter pollution and employee health.
RO2: To determine if safety training reduces the lost time hours.
RQ2: Is there a relationship between the safety training and the lost time hours?
Ho2: There is no meaningful relationship between safety training and lost time hours.
Ha2: There is a meaningful relationship between safety training and lost time hours.
RO3: To determine the relationship between sound-level exposure and the cost of hearing protection.
RQ3: Is there a relationship between the sound-level exposure and the cost of hearing protection?
Ho3: There is no meaningful relationship between the sound-level exposure and the cost of hearing protection.
Ha3: There is a meaningful relationship between sound-level exposure and the cost of hearing equipment.
RO4: To determine the effectiveness of the new employee training program.
RQ4: Is the new employee training program effective at helping employees observe the health and safety measures?
Ho4: The new employee training program is not adequate compared to the prior training program.
Ha4: The new employee training program is effective compared to the prior training program.
RO5: To determine whether lead levels in the blood have increased.
RQ5: Is there a relationship between lead exposure at the workplace and the lead levels in the blood for the employees? (Nayak & Singh, 2021)
Ho5: There is no meaningful relationship between lead exposure and the lead levels in the blood for the employees.
Ha5: There is a meaningful relationship between lead exposure and the lead levels in the blood for the employees.
RO6: To determine the ROI for the different lines of service.
RQ6: Is the ROI for the different lines of service other? (Nayak & Singh, 2021)
Ho6: There is no significant difference between the different lines’ ROI.
Ha6: There is a significant difference between the ROI of the different lines of service
Research Methodology, Design, and Methods
Research Methodology
Quantitative methodology is the most appropriate approach for this study. This is because quantitative methodologies are best rooted in positivism philosophies, which effectively illustrate different business problems (Loewen et al., 2019). This enables examining the relationship between the particulate matter and employee health and the statistically significant correlation between the size of particulate matter and employee health. This is because the relationship is best determined using statistical methods, effectively determined through quantitative approaches. Quantitative methodology is better suited for this study than qualitative methods because it utilizes more statistical data and analysis.
Research Design
The study will utilize a descriptive non-experimental research design. This is because descriptive approaches are best suitable in quantitative methods, especially in explaining statistical data. It will also be effective for this study because it is highly structured and uses statistical analysis effective for testing formal hypotheses.
Research Methods
Descriptive statistical research methods shall be incorporated with correlational methods to ensure the reliability of the research, since the study cannot be conducted in a controlled experiment (Mishra, 2019). Combining the two research methods will effectively lead to a better examination of the relationship between the size of particulate matter and employee health and the relationship between the time lost in safety training and effectiveness in employee safety performance.
Data Collection Methods
Several data collection methods shall be used in this study, including online surveys through emails and telephone. Direct observation shall be utilized where applicable, especially in collecting data that does not require surveys or questionnaires (Loomis et al., 2018). Record analysis will also provide additional information, especially about the organization's employee details and different details about particulate matter, training, sound level exposure, lead poisoning, and information on return on investments.
Sampling Design
The sample design suitable for this study is random sampling to ensure that the sample used is unbiased and represents the target population efficiently. The study focuses on elements that can be generalized in different organization sectors (Zhao et al., 2019). Therefore, random sampling will be effective in obtaining the most appropriate sample type for the study.
Data Analysis Procedures
The study shall utilize correlation in determining the relationship between particulate matter's size and employee health. The main focus is to ascertain the statistical relationship between the independent variable, particulate matter, and the dependent variable, employee health (Loomis et al., 2018). Therefore, correlation shall provide a practical test for hypothesis one. Paired sample t-tests will be suitable for testing and determining whether the time lost is related to employee safety training, the difference between the decibel levels, and the health of the work environment. This is because it shall effectively provide the relationship between the different variables involved.
Data Analysis: Descriptive Statistics and Assumption Testing
Correlation: Descriptive Statistics and Assumption Testing
Frequency Distribution Table
|
PM Size |
Frequency |
|
0-1 |
8 |
|
2-4 |
24 |
|
5-7 |
37 |
|
8-10 |
34 |
|
Sick Days |
Frequency |
|
0-2 |
1 |
|
4-7 |
61 |
|
8-9 |
30 |
|
10-12 |
11 |
Histogram
Descriptive Statistics Table
Microns
|
Mean |
5.6573 |
|
Standard Error |
0.2556 |
|
Median |
6 |
|
Mode |
8 |
|
Standard deviation |
2.5941 |
|
Sample variance |
6.729 |
|
Kurtosis |
-0.8522 |
|
Skewness |
0.3733 |
|
Range |
9.8 |
|
Minimum |
0.2 |
|
Maximum |
10 |
|
Sum |
582.7 |
|
Count |
103 |
|
Largest |
10 |
|
Smallest |
0.2 |
|
Confidence |
0.507 |
|
Level |
7 |
Sick Days
|
Mean |
7.126 |
|
Standard Error |
0.1865 |
|
Median |
7 |
|
Mode |
7 |
|
Standard deviation |
1.8923 |
|
Sample variance |
3.582 |
|
Kurtosis |
0.1249 |
|
Skewness |
0.1422 |
|
Range |
10 |
|
Minimum |
2 |
|
Maximum |
12 |
|
Sum |
734 |
|
Count |
103 |
|
Largest |
112 |
|
Smallest |
2 |
|
Confidence |
|
|
Level |
0.3699 |
Simple Regression: Descriptive Statistics and Assumption Testing
Frequency Distribution Table
|
Expenditure |
Frequency |
|
20-500 |
108 |
|
501-1000 |
76 |
|
1001-1500 |
27 |
|
1501-2000 |
11 |
|
2001-2500 |
1 |
|
Time |
Frequency |
|
0-50 |
6 |
|
51-100 |
26 |
|
101-200 |
98 |
|
201-300 |
85 |
|
301-00 |
8 |
Histogram
Descriptive Statistics Table
Safety Training Expenditure
|
Mean |
595.98 |
|
Standard Error |
31.477 |
|
Median |
507.78 |
|
Mode |
234 |
|
Standard Deviation |
470.0552 |
|
Sample variance |
220948.9 |
|
Kurtosis |
0.444 |
|
Skewness |
0.951 |
|
Range |
2251.4 |
|
Minimum |
20.6 |
|
Maximum |
2271.86 |
|
Sum |
132904.5 |
|
Count |
223 |
|
Largest |
2271.86 |
|
Smallest |
20.456 |
|
Confidence |
62.03 |
Lost Time Hours
|
Mean |
188 |
|
Standard Error |
4.8031 |
|
Median |
190 |
|
Mode |
190 |
|
Standard Deviation |
71.73 |
|
Sample variance |
5144.54 |
|
Kurtosis |
-0.5012 |
|
Skewness |
-0.082 |
|
Range |
350 |
|
Minimum |
10 |
|
Maximum |
360 |
|
Sum |
41925 |
|
Count |
223 |
|
Largest |
360 |
|
Smallest |
10 |
|
Confidence |
9.465 |
Multiple Regression: Descriptive Statistics and Assumption Testing
Frequency Distribution Table
|
Decibel |
Frequency |
|
100-106 |
4 |
|
107-111 |
51 |
|
112-116 |
126 |
|
117-121 |
49 |
|
122-131 |
786 |
|
132-141 |
287 |
Histogram
Descriptive Statistics Table
Decibels
|
Mean |
124.84 |
|
Standard Error |
0.1779 |
|
Median |
125.7 |
|
Mode |
127.32 |
|
Standard Deviation |
6.89 |
|
Sample variance |
47.589 |
|
Kurtosis |
-0.31 |
|
Skewness |
-0.41 |
|
Range |
37.61 |
|
Minimum |
103.4 |
|
Maximum |
140.9 |
|
Sum |
187628.4 |
|
Count |
1503 |
The hypothesis used include.
Ho; The sample data is not significantly different from the average population.
Ha; The sample data are significantly different from the average population.
The Kurtosis and skewness are close to zero and within the range of -2 to 2, indicating the data is symmetrical as confirmed by the mean and the median.
The null hypothesis is accepted.
Independent Samples t Test: Descriptive Statistics and Assumption Testing
Frequency Distribution Table
Training t-Test
|
Training |
Frequency |
|
49-60 |
12 |
|
61-70 |
20 |
|
71-80 |
21 |
|
81-90 |
8 |
|
91-100 |
1 |
Training
|
Training |
Frequency |
|
74-80 |
14 |
|
81-85 |
21 |
|
86-90 |
19 |
|
91-95 |
6 |
|
96-100 |
2 |
Histogram
Descriptive Statistics Table
Prior Training
|
Mean |
69.79 |
|
Standard Error |
1.403 |
|
Median |
70 |
|
Mode |
80 |
|
Standard Deviation |
11.05 |
|
Sample variance |
122 |
|
Kurtosis |
-0.777 |
|
Skewness |
-0.086 |
|
Range |
41 |
|
Minimum |
50 |
|
Maximum |
91 |
|
Sum |
4327 |
|
Count |
62 |
|
Largest |
91 |
|
Smallest |
50 |
|
Confidence |
2.81 |
Revised Training
|
Mean |
84.77 |
|
Standard Error |
0.659 |
|
Median |
85 |
|
Mode |
85 |
|
Standard Deviation |
5.1927 |
|
Sample variance |
26.96 |
|
Kurtosis |
-0.352 |
|
Skewness |
0.144 |
|
Range |
22 |
|
Minimum |
75 |
|
Maximum |
97 |
|
Sum |
5256 |
|
Count |
62 |
|
Largest |
97 |
|
Smallest |
75 |
|
Confidence |
1.319 |
The hypothesis used include.
Ho; The sample data is not significantly different from the average population.
Ha; The sample data are significantly different from the average population.
Kurtosis and skewness are close to zero and within the -2 to 2 range, indicating that the data is symmetrical as confirmed by the mean and the median.
The null hypothesis is accepted.
Dependent Samples (Paired-Samples) t Test: Descriptive Statistics and Assumption Testing
Frequency Distribution Table
Sample Data 2
|
Exposure |
Frequency |
|
05-015 |
5 |
|
16-25 |
8 |
|
26-35 |
12 |
|
36-45 |
16 |
|
46-56 |
8 |
Paired Sample Data
|
Exposure |
Frequency |
|
05-015 |
5 |
|
16-25 |
8 |
|
26-35 |
11 |
|
36-45 |
17 |
|
46-56 |
8 |
Histogram
Descriptive Statistics Table
Pre-Exposure
|
Mean |
32.86 |
|
Standard Error |
1.75 |
|
Median |
35 |
|
Mode |
36 |
|
Standard Deviation |
12.27 |
|
Sample variance |
150.46 |
|
Kurtosis |
0.576 |
|
Skewness |
0.25 |
|
Range |
50 |
|
Minimum |
6 |
|
Maximum |
56 |
|
Sum |
1610 |
|
Count |
49 |
|
Largest |
56 |
|
Smallest |
6 |
|
Confidence |
3.52 |
Post-Exposure
|
Mean |
33.29 |
|
Standard Error |
5.78 |
|
Median |
36 |
|
Mode |
38 |
|
Standard Deviation |
12.47 |
|
Sample variance |
155.5 |
|
Kurtosis |
-0.65 |
|
Skewness |
-0.48 |
|
Range |
50 |
|
Minimum |
6 |
|
Maximum |
56 |
|
Sum |
1631 |
|
Count |
49 |
|
Largest |
56 |
|
Smallest |
6 |
|
Confidence |
3.58 |
The hypothesis used include.
Ho; The sample data are not significantly different from the average population.
Ha; The sample data used is significantly different from the average population.
Kurtosis and skewness are close to zero and within the -2 to 2 range, indicating that the data is symmetrical as confirmed by the mean and the median.
The null hypothesis is accepted.
Measurement Scale
Internal
The measure of Central Tendency
Mean
Skewness and Kurtosis
Kurtosis is equal to zero.
Evaluation
The distribution means the graph data is bell-curved, which is symmetrical around.
ANOVA: Descriptive Statistics and Assumption Testing
Frequency Distribution Table
|
Air |
Frequency |
|
1.0-3.0 |
1 |
|
4.0-6.0 |
4 |
|
7.0-9.0 |
6 |
|
10.0-12.0 |
7 |
|
12.0-15.0 |
2 |
|
Water |
Frequency |
|
1.0-3.0 |
1 |
|
4.0-6.0 |
10 |
|
7.0-9.0 |
5 |
|
10.0-12.0 |
4 |
|
Soil |
Frequency |
|
5.0-7.0 |
3 |
|
8.0-10.0 |
13 |
|
10.0-13.0 |
4 |
|
Training |
Frequency |
|
1.0-3.0 |
1 |
|
4.0-6.0 |
16 |
|
7.0-9.0 |
3 |
Histogram
Descriptive Statistics Table
Air
|
Mean |
8.9 |
|
Standard Error |
0.68 |
|
Median |
9 |
|
Mode |
11 |
|
Standard Deviation |
3.06 |
|
Sample variance |
9.36 |
|
Kurtosis |
-0.6 |
|
Skewness |
-0.36 |
|
Range |
11 |
|
Minimum |
3 |
|
Maximum |
14 |
|
Sum |
178 |
|
Count |
20 |
|
Largest |
14 |
|
Smallest |
3 |
|
Confidence |
1.4 |
Soil
|
Mean |
9.1 |
|
Standard Error |
0.39 |
|
Median |
9 |
|
Mode |
8 |
|
Standard Deviation |
1.74 |
|
Sample variance |
3.04 |
|
Kurtosis |
0.12 |
|
Skewness |
0.49 |
|
Range |
7 |
|
Minimum |
6 |
|
Maximum |
13 |
|
Sum |
182 |
|
Count |
20 |
|
Largest |
13 |
|
Smallest |
6 |
|
Confidence |
0.82 |
Water
|
Mean |
7 |
|
Standard Error |
0.58 |
|
Median |
6 |
|
Mode |
6 |
|
Standard Deviation |
2.56 |
|
Sample variance |
6.6 |
|
Kurtosis |
-0.24 |
|
Skewness |
0.76 |
|
Range |
9 |
|
Minimum |
3 |
|
Maximum |
12 |
|
Sum |
140 |
|
Count |
20 |
|
Largest |
12 |
|
Smallest |
3 |
|
Confidence |
1.21 |
Training
|
Mean |
5.4 |
|
Standard Error |
0.27 |
|
Median |
5 |
|
Mode |
5 |
|
Standard Deviation |
1.19 |
|
Sample variance |
1.41 |
|
Kurtosis |
0.25 |
|
Skewness |
0.16 |
|
Range |
5 |
|
Minimum |
3 |
|
Maximum |
8 |
|
Sum |
108 |
|
Count |
20 |
|
Largest |
8 |
|
Smallest |
3 |
|
Confidence |
0.56 |
The hypothesis used include.
Ho; The sample data are not significantly different from the average population.
Ha; The sample data used is significantly different from the average population.
Kurtosis and skewness are close to zero and within the -2 to 2 range, indicating that the data is symmetrical as confirmed by the mean and the median.
The null hypothesis is accepted.
Data Analysis: Hypothesis Testing
Correlation: Hypothesis Testing
Ho1: There is no statistically significant relationship between particulate matter pollution and employee health.
Ha1: There is a statistically significant relationship between particulate matter pollution and employee health.
|
|
job site |
microns |
mean annual sick days per employee |
|
job site |
1 |
|
|
|
microns |
-0.097793758 |
1 |
|
|
mean annual sick days per employee |
0.056174631 |
-0.715984185 |
1 |
From the analysis, there is a statistically significant relationship between the number of microns and the number of sick days taken by the employees; the more the number of microns the higher the number of sick days which are taken by the employees.
Simple Regression: Hypothesis Testing
Ho2: There is no meaningful relationship between safety training and lost time hours.
Ha2: There is a meaningful relationship between safety training and lost time hours.
Based on the findings from the regression analysis, the null hypothesis should be rejected since there is a statistically significant between the variables, safety training and lost time hours.
Multiple Regression: Hypothesis Testing
Ho3: There is no meaningful relationship between the sound-level exposure and the cost of hearing protection.
Ha3: There is a meaningful relationship between sound-level exposure and the cost of hearing equipment.
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SUMMARY OUTPUT |
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Regression Statistics |
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Multiple R |
0.065459231 |
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R Square |
0.004284911 |
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Adjusted R Square |
-0.005573654 |
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Standard Error |
0.906533144 |
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Observations |
103 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
1 |
0.357186847 |
0.357186847 |
0.434638391 |
0.511222 |
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Residual |
101 |
83.00203645 |
0.821802341 |
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Total |
102 |
83.3592233 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
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Intercept |
0.682789788 |
0.123867259 |
5.512270087 |
2.72423E-07 |
0.43707 |
0.92850911 |
0.437070466 |
0.92850911 |
|
X Variable 1 |
-1.53252E-05 |
2.32457E-05 |
-0.659271106 |
0.511222066 |
-6.1E-05 |
3.07881E-05 |
-6.14385E-05 |
3.07881E-05 |
The output indicates that there is a meaningful relationship which exists between the sound level exposure and the cost of hearing equipment which means that the null hypothesis should be rejected.
Independent Samples t Test: Hypothesis Testing
Ho4: The new employee training program is inadequate compared to the prior training program.
Ha4: The new employee training program is effective compared to the prior training program.
The results show a p-value of 2.62299E-14, which is less than 0.5 and this is an indicator that the null hypothesis should be rejected as there is statistically significant relationship between the variables. This shows that the new employee training program is more effective when compared to previous programs used.
Dependent Samples (Paired Samples) t Test: Hypothesis Testing
Ho5: There is no meaningful relationship between lead exposure and the lead levels in the blood for the employees.
Ha5: There is a meaningful relationship between lead exposure and the lead levels in the blood for the employees.
The p-value is 1.25718E-21, and this is smaller than the alpha 0.05. This p-value indicates that the null hypothesis should be rejected, and this means there is a meaningful relationship between lead exposure and the lead levels of blood in the employees in Sun Coast.
ANOVA: Hypothesis Testing
Ho6: There is no significant difference between the ROI of the different lines.
Ha6: There is a significant difference between the ROI of the different lines of service
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ANOVA: Single Factor |
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SUMMARY |
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Groups |
Count |
Sum |
Average |
Variance |
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|
Column 1 |
20 |
178 |
8.9 |
9.357895 |
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Column 2 |
20 |
182 |
9.1 |
3.042105 |
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Column 3 |
20 |
140 |
7 |
6.631579 |
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Column 4 |
20 |
108 |
5.4 |
1.410526 |
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ANOVA |
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Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
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Between Groups |
182.8 |
3 |
60.93333 |
11.9231 |
1.76E-06 |
2.724944 |
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Within Groups |
388.4 |
76 |
5.110526 |
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Total |
571.2 |
79 |
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The results from the ANOVA show that there is a significant difference between the different lines of service.
Findings
RO1: to determine if particulate matter pollution affects employee health.
The statistical analysis shows a significant relationship between the particulate matter pollution and employee health where the health worsens when the particulate matter is increased. The particulate matter pollution is detrimental to the health of the employees.
RO2: To determine if safety training reduces the lost time hours.
The statistical analysis indicates that the safety training reduces the lost time hours, and this means that the null hypothesis for the research objective should be rejected.
RO3: To investigate the relationship between sound level exposure and the cost of hearing equipment.
According to the statistical analysis conducted, the level of sound exposure has a significant impact on the cost of hearing equipment. This shows that the more the sound level exposure the more the money which is spend on the hearing equipment.
RO4: to determine the effectiveness of new employee training program.
From the statistical analysis, the new employee training programs are more effective when compared to the existing employee training programs. The null hypothesis made for the research objective should be rejected.
RO5: To determine if blood lead levels are increased.
Based on the research and statistical analysis the lead levels in the blood of the employees increased because of exposure to lead in the organization. This shows that the null hypothesis should be rejected.
RO6: To determine ROI for different lines of service.
The relationship was found to be statistically significant and hence the null hypothesis should be rejected.
Recommendations
Particulate Matter Recommendation
Suncoast should focus efforts on making sure that there is no particulate matter present in the surrounding of the organization. This can be achieved through the use of fumigation services and thorough cleaning to eliminate any PM in the surrounding.
Safety Training Effectiveness Recommendation
Safety training should be made mandatory in the organization so that all of the new and existing employees have been given safety training. This will help make sure that the employees are safe in the organization from all kinds of dangers.
Sound-Level Exposure Recommendation
Sun Coast should find a way for reducing the level of sound exposure and this could include turning off any machines running which are not needed in the organization. Also, the sound level exposure could be lowered through making the walls in the organization soundproof so that employees do not hear lots of noise.
New Employee Training Recommendation
All of the employees who are new into the organization should be trained using the new employee training. The organization should eliminate the use of the existing employee training program as it is less effective when compared to the new program.
Lead Exposure Recommendation
The company should find ways of eliminating the lead exposure and this can be achieved through the use of materials which have very few percentages and concentration of the lead component since it is dangerous to the health of the patients.
Return on Investment Recommendation
The company should focus on the lines of service which have the highest ROI, and this is because these lines of service will bring in more income to the company.
References
Loewen, S., & Godfroid, A. (2019). Advancing quantitative research methods. In The Routledge handbook of research methods in applied linguistics (pp. 98-107). Routledge. https://www.taylorfrancis.com/chapters/edit/10.4324/9780367824471-9/advancing-quantitative-research-methods-shawn-loewen-aline-godfroid
Loomis, D. K., & Paterson, S. (2018). A comparison of data collection methods: Mail versus online surveys. Journal of Leisure Research, 49(2), 133-149. https://www.tandfonline.com/doi/abs/10.1080/00222216.2018.1494418
Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of cardiac anesthesia, 22(1), 67. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350423/
Zhao, Z., Christensen, R., Li, F., Hu, X., & Yi, K. (2018, May). Random sampling over joins revisited. In Proceedings of the 2018 International Conference on Management of Data (pp. 1525-1539). https://dl.acm.org/doi/abs/10.1145/3183713.3183739
Training Expenditure
Frequency 20-500 501-1000 1001-1500 1501-2000 2001-2500 108 76 27 11 1
Lost Time Hours
Frequency 0-50 51-100 101-200 201-300 301-00 6 26 98 85 8
Sound Level
Frequency 100-106 107-111 112-116 117-121 122-131 132-141 4 51 126 49 786 287
Traininig t-Test
Frequency 49-60 61-70 71-80 81-90 91-100 12 20 21 8 1
Training
Frequency 74-80 81-85 86-90 91-95 96-100 14 21 19 6 2
Sample Data 2
Frequency 05-015 16-25 26-35 36-45 46-56 5 8 12 16 8
Paired Sample Data
Frequency 05-015 16-25 26-35 36-45 46-56 5 8 11 17 8
Air
Frequency 1.0-3.0 4.0-6.0 7.0-9.0 10.0-12.0 12.0-15.0 1 4 6 7 2
Water
Frequency 1.0-3.0 4.0-6.0 7.0-9.0 10.0-12.0 1 10 5 4
Soil
Frequency 5.0-7.0 8.0-10.0 10.0-13.0 3 13 4
Training
Frequency 1.0-3.0 4.0-6.0 7.0-9.0 1 16 3
Histogram for Correlation
Frequency 0 to 1 2 to 4 5 to 7 8 to 10 8 24 37 34
Annual Sick Days
Frequency 0 to 2 4 to 7 8 to 9 10 to 12 1 61 30 11