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SunCoastRemediation.docx

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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 Engineering10(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 Management2(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 Psychiatry76(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.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.915446939

R Square

0.838043099

Adjusted R Square

0.836439565

Standard Error

17.56799095

Observations

103

ANOVA

 

df

SS

MS

F

Significance F

Regression

1

161299.2943

161299.2943

522.6227

1.02549E-41

Residual

101

31172.06491

308.634306

Total

102

192471.3592

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

Lower ninety-five%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

235.2032892

5.086012115

46.24512955

8.77E-70

225.1140093

245.2925691

225.1140093

245.292569

X Variable 1

-0.108413156

0.004742287

-22.86094267

1.03E-41

-0.117820578

-0.099005734

-0.117820578

-0.09900573

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.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.065459231

R Square

0.004284911

Adjusted R Square

-0.005573654

Standard Error

0.906533144

Observations

103

ANOVA

 

df

SS

MS

F

Significance F

Regression

1

0.357186847

0.357186847

0.434638391

0.511222

Residual

101

83.00203645

0.821802341

Total

102

83.3592233

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

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.

t-Test: Paired Two Sample for Means

 

Variable 1

Variable 2

Mean

69.79032258

84.77419

Variance

122.004495

26.96457

Observations

62

62

Pearson Correlation

0.060325473

Hypothesized Mean Difference

0

df

61

t Stat

-9.899218434

P(T<=t) one-tail

1.31149E-14

t Critical one-tail

1.670219484

P(T<=t) two-tail

2.62299E-14

t Critical two-tail

1.999623585

 

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.

t-Test: Paired Two Sample for Means

 

1

6

Mean

25.5

33.41667

Variance

196

137.9929

Observations

48

48

Pearson Correlation

0.983498243

Hypothesized Mean Difference

0

df

47

t Stat

-16.9236878

P(T<=t) one-tail

6.28591E-22

t Critical one-tail

1.677926722

P(T<=t) two-tail

1.25718E-21

t Critical two-tail

2.011740514

 

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

ANOVA: Single Factor

SUMMARY

Groups

Count

Sum

Average

Variance

Column 1

20

178

8.9

9.357895

Column 2

20

182

9.1

3.042105

Column 3

20

140

7

6.631579

Column 4

20

108

5.4

1.410526

ANOVA

Source of Variation

SS

df

MS

F

P-value

F crit

Between Groups

182.8

3

60.93333

11.9231

1.76E-06

2.724944

Within Groups

388.4

76

5.110526

Total

571.2

79

 

 

 

 

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 Research49(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 anesthesia22(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