SUN COAST REMEDIATION 1 Sun Coast Remediation Ariel Ramon Acosta Columbia Southern University SUN COAST REMEDIATION 2 Table of Contents Executive Summary ........................................................................................................................ 5 Introduction ..................................................................................................................................... 6 Statement of the Problems .............................................................................................................. 6 Particulate Matter (PM) ............................................................................................................... 6 Safety Training Effectiveness ..................................................................................................... 7 Sound-Level Exposure ................................................................................................................ 7 New Employee Training ............................................................................................................. 7 Lead Exposure ............................................................................................................................. 8 Return on Investment .................................................................................................................. 8 Literature Review............................................................................................................................ 8 Economic growth .......................................................................Error! Bookmark not defined. Safety training ............................................................................Error! Bookmark not defined. Lead Exposures ..........................................................................Error! Bookmark not defined. Decibel levels .............................................................................Error! Bookmark not defined. Research Objectives ........................................................................................................................ 8 Research Questions and Hypotheses ......................................................................................... 12 Research Methodology, Design, and Methods ............................................................................. 13 Research Methodology.............................................................................................................. 14 Research Design ........................................................................................................................ 14 Research methods. ..................................................................................................................... 14 Data collection methods. ............................................................................................................... 15 Sampling design ........................................................................................................................ 15 Data Analysis Procedure. .............................................................................................................. 15 Data Analysis: Descriptive Statistics and Assumption Testing ................................................ 16 Correlation: Descriptive Statistics and Assumption Testing ................................................. 16 Measurement scale. ................................................................................................................... 18 Measure of central tendency .................................................................................................. 18 Evaluation .............................................................................................................................. 18 Simple Regression: Descriptive Statistics and Assumption Testing ......................................... 19 Frequency distribution table. ................................................................................................. 19 Histogram. ............................................................................................................................. 20 Descriptive statistics table. .................................................................................................... 20 SUN COAST REMEDIATION 3 Measurement scale. ................................................................................................................... 21 Measure of central tendency. ................................................................................................. 21 Evaluation. ............................................................................................................................. 21 Multiple Regression: Descriptive Statistics and Assumption Testing ...................................... 22 Frequency distribution table. ................................................................................................. 22 Histogram. ............................................................................................................................. 23 Descriptive statistics table. .................................................................................................... 23 Measurement scale. ................................................................................................................... 24 Measure of central tendency. ................................................................................................. 25 Evaluation. ............................................................................................................................. 25 Independent Samples t Test: Descriptive Statistics and Assumption Testing .......................... 26 Frequency distribution table. ................................................................................................. 26 Histogram. ............................................................................................................................. 26 Descriptive statistics table. .................................................................................................... 27 Measurement scale. ................................................................................................................... 27 Measure of central tendency. ................................................................................................. 28 Evaluation. ............................................................................................................................. 28 Dependent Samples (Paired-Samples) t Test: Descriptive Statistics and Assumption Testing 29 Frequency distribution table .................................................................................................. 29 Histogram. ............................................................................................................................. 29 Descriptive statistics table. .................................................................................................... 30 Measurement scale. ................................................................................................................... 30 Measure of central tendency. ................................................................................................. 31 Evaluation. ............................................................................................................................. 31 ANOVA: Descriptive Statistics and Assumption Testing ........................................................ 32 Frequency distribution table .................................................................................................. 32 Histogram. ............................................................................................................................. 32 Descriptive statistics table. .................................................................................................... 32 Measurement scale. ................................................................................................................... 33 Measure of central tendency. ................................................................................................. 34 Evaluation. ............................................................................................................................. 34 Data Analysis: Hypothesis Testing ............................................................................................... 35 SUN COAST REMEDIATION 4 Correlation: Hypothesis Testing................................................................................................ 35 SUMMARY OUTPUT .......................................................................................................... 35 ANOVA ................................................................................................................................. 36 Simple Regression: Hypothesis Testing.................................................................................... 37 SUMMARY OUTPUT .......................................................................................................... 37 ANOVA ................................................................................................................................. 37 Multiple Regression: Hypothesis Testing ................................................................................. 38 SUMMARY OUTPUT .......................................................................................................... 38 ANOVA ................................................................................................................................. 39 Independent Samples t-Test: Hypothesis Testing ..................................................................... 41 Dependent Samples (Paired Samples) t-Test: Hypothesis Testing ........................................... 42 ANOVA: Hypothesis Testing ................................................................................................... 43 SUMMARY........................................................................................................................... 43 ANOVA ................................................................................................................................. 44 Findings......................................................................................................................................... 44 Recommendations ......................................................................................................................... 46 SUN COAST REMEDIATION 5 Executive Summary The leadership of Sun Coast through various means of research established six pertinent issues that affect the organization. It prompted instigation of a research process that aimed at establishing various solutions for the problems. The problems included particulate matter, safety training effectiveness, sound level exposure, new employee training, lead exposure and return on investment. During the research, the team used various techniques of investigations and data collection that included sampling and evaluation as well as descriptive and assumptive statistics. Through the above-mentioned methods, invaluable data was obtained and consequently analyzed and the inferences presented to formulate the findings of the survey. Various pictographic depictions of the data found establish the basis for the findings and recommendations that characterize the research. The findings then guided the team to provide recommendations on the best venues for solving the six problems. SUN COAST REMEDIATION 6 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 the statement of the problems, literature review, research objectives, research questions and hypotheses, research methodology, design, and methods, data analysis, findings, and recommendations. Statement of the 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, PM varies in size depending on the project and job site. PM that is 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 that is 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 that is less than 2.5 microns, it is potentially more harmful than PM that is between 10 and 2.5 since the conditions are more suitable for inhalation. PM that is less than 2.5 is 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 SUN COAST REMEDIATION recorded in microns. Data are also available for average annual sick days per employee per jobsite. 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 ear-plugs 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 tested on their knowledge. Test data are available for two groups: Group A employees who participated in the prior training program and Group B 7 SUN COAST REMEDIATION 8 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 baseline blood test is taken pre-exposure and postexposure at the conclusion of the remediation. Data are available for 49 employees who recently concluded a 2-year 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 Within our organization of Sun Coast, we have identified some areas of concern that may be solved or addressed with solutions to improve. Those problems identified are exposure to particulate matter, effectiveness of safety training, excess exposure to sound levels, training for new employees, excess lead exposure, and return on investment. I believe with the appropriate research we can improve our company and find solutions to problems or completely eliminate any concerns we might have. SUN COAST REMEDIATION 9 With the increasing industrialization and urbanization, there has been massive emission of toxic substances that have impacted both human health and climatic conditions. Studies have shown that economic activities resulting to massive production of volatile organic compounds such as sulphur oxides, oxides of nitrogen and carbon (II) oxides among other compounds have been the catalysts for global warming alongside health deterioration among humans (Guar , 2018). These compounds present to be some of the most known volatile organic compounds (VOC) causing gaseous pollution, especially in the developing countries. Importantly, it has been realized that out of 33 hazardous air pollutants, the majority (21) is realized from the motor vehicles which emits much CO2 and sulphur compounds. According to Guar (2018), VOC pollutants can be naturally occurring such as those that are emitted from the vegetation such as the isoprene, a- and b-pinene and methanol. Besides, studies have estimated the global VOC flux to consist of 44% isoprene, 22.5% reactive hydrocarbons 11% monoterpenes and another 22.5% other non-reactive hydrocarbons. While natural VOC discharge from vegetation has been considered to have a high impact on human health and the climate, the anthropogenic source has not been left out through its adverse effect on human health and the environment. In this case, anthropogenic sources of VOC pollution include emission from vehicles, bio-decomposition of wastes, exhaust and fuel evaporation, industrial processes, oil refining, and solvent usage. It is in cognition that these pollutants have affected human health largely in urban areas where they are highly concentrated. Despite measures put forth by the environmental regulatory authorities, less has been achieved as the menace of industrial growth have increased the use of heavy machines and extraction of minerals leading to the production of harmful organic compounds. SUN COAST REMEDIATION 10 While workers at Sun Coast can be said to have high potential exposure to these toxic substances, noise pollution is also presented as other health deteriorating factor affecting the company’s employees. It is obvious that exposure to loud noise affects hearing and impair the functioning of the ear. This evidence if presented by Aliabadia (2015) when they observed that noisy workrooms, duration of exposure to noise environment and the level of the noise produced as well as prolonged use of hearing protection devices are larger contributing factors to malfunction of the ear. Their findings were interestingly significant to this study of concern as their results showed a significant relationship between smoking, job type and use of ear protection devices with the loss of hearing among individual workers in noisy environments. Firdaus & Ahmad (2010) illustrated that the tremendous population increase, as well as the rise of industrial activities, unchecked rise in the number of vehicles and the rapid lifestyle changes, are the major contributing factors to increased noise pollution in urban areas. Ghuncha & Ahmad further illustrated that the resultant effect has been a disturbance, annoyance, communication interference as well as adverse effects on human health. In their study, Ghuncha & Ahmad also established an existing relationship between the intensity of the noise pollution and the occurrence of fatal diseases among individuals exposed to the menace. While this study also focused on the impact of lead exposure on sun coast employees, studies have been done showing a significant relationship between lead exposure and its impact on human health. For instance, Assi (2016) considered lead metal to be the most hazardous chemical that has caused environmental pollution as well as having an adverse effect on human biological systems. The chemical largely impacts human and the environment through its exposure to the air, food sources and water bodies. Mohammed further expounded that the toxicity nature of the chemical is largely experienced in the endocrine and kidney systems of SUN COAST REMEDIATION 11 individuals that causing life fatalities. Their evidence was also echoed by D’souza (2007) when he observed that the potential health hazards of lead poisoning still exist and are rising due to the lack of education regarding the dangers of working with lead. As employees become vulnerable to these toxic PM and other pollutants, the effects of training still remain an important factor of consideration when remedying the health outcome of workers. Ricci (2016) while studying the effectiveness of occupational health and safety training found that training offered to workers are important in assuring their occupational health outcome as well as imparting positive belief and attitude while undertaking their work. In addition, Ricci also illustrated that training becomes a medium for imparting knowledge among employees on issues concerning their occupational health as well as their behavior around work environment. Through this literature, it is evident that the menace of pollution at work environment have impacted most employees globally and thus the need to determine appropriate remedies of minimizing the impacts. Consequently, noise pollution and pollution from particulate matters have been realized to harm not only the environment but also employees exposed to these pollutants. This is the case at sun coast organization that called for adequate analysis and synthesis of information related to the health and safety of workers as a means of determining health and safety related issues within the organization. Research Objectives Within our organization of Sun Coast, we have identified some areas of concern that may be solved or addressed with solutions to improve. Those problems identified are exposure to particulate matter, effectiveness of safety training, excess exposure to sound levels, training for SUN COAST REMEDIATION 12 new employees, excess lead exposure, and return on investment. Objective of research studies are to see if Sun Coast is giving the proper protection to its employees according to OSHA guidance or are we exceeding it. If we are not meeting standards what do we need to do in order to get to minimum requirements or higher. RO1: Determine relationship between Particulate Matter (PM) size and employee health RO2: Determine if training has been successful in reducing time lost hours RO3: Determine decibels (dB) levels of different work environments for proper hearing protection RO4: Determine if revised training plan is more effective RO5: Determine if current lead levels change in blood post exposure RO6: Determine if return of investment (ROI) for services is same for each line Research Questions and Hypotheses RO1: Determine relationship between Particulate Matter (PM) size and employee health H01: There is no significant difference between PM and employee health HA1: There is a significant difference between PM and employee health RO2: Determine if training has been successful in reducing time lost hours H02: There is no significant relationship between training and time-lost hours HA2: There is a significant relationship between training and time-lost hours RO3: Determine decibels (dB) levels of different work environments for proper hearing protection SUN COAST REMEDIATION 13 H03: There is no significant difference between work environments in dB’s HA3: There is a significant difference between work environments in dB’s RO4: Determine if revised training plan is more effective H04: There is no significant relationship between revised training and employee effectiveness HA4: There is a significant relationship between revised training and employee effectiveness RO5: Determine if current lead levels change in blood post exposure H05: There is no significant difference between lead levels in blood post exposure HA5: There is a significant difference between lead levels in blood post exposure RO6: Determine if return of investment (ROI) for services is same for each line H06: There is no statistically significant difference on ROI for each service provided HA6: There is a statistically significant difference on ROI for each service provided RO1: Research Methodology, Design, and Methods Sun Coast provides remediation services to business and governmental organizations. Most of our contracts involve working within contamination sites where we remove toxic substances from soil and water. In addition to the toxicity of the air, water, and soil. Sun Coast genuinely cares about the health, safety, and well-being of their 5,500 employees, but they are also concerned about worker compensation costs and potential long-term litigation from injuries and illness related to employment. Sun Coast has since done some historical research and we have adopted a regression analysis. SUN COAST REMEDIATION 14 Research Methodology Statistically, research methodology is a process used by statisticians to collect information and valid data with the aim of coming up with a business decision (Kumar, 2019). Statisticians tend to base their research methodology on the distinction between qualitative and quantitative data. The difference between qualitative and quantitative data is that qualitative data assumes the form of descriptions which is based on languages and images while quantitative data assumes the kind of numbers. In every research paper, it is the research methodology section that enables the reader to evaluate the study’s validity and reliability critically. Therefore, for the case of this study, I have adopted a quantitative analysis methodology since the information given is justified by data or numerical analysis. Research Design According to the adopted research questions, it is evident that we used a historical research design since almost all data used was retrieved from archives (Quinlan, 2019). The research questions justify the causality of the study; this is because we have tried to explain the impact of a specific change over the existing norm. For example, in research question one, the research is out to identify the effects of particulate matter and the employee’s health. Research methods Based on the causality of the research questions, the research will specifically adopt a regression analysis as the most convenient and appropriate research method. This is because it only through the regression analysis will we understand the relationship between the dependent variable and the independent variables within the model. In the six statements of the problems identified, I will be able to use a regression analysis determine the relationship of the degree of SUN COAST REMEDIATION 15 significance at which each problem identified will impact the working condition and or the health of employees hence posing a threat to the business aim which is always to maximize the output. Data collection methods In a total solution to the six identified statement of the problems, we used secondary data which means that we used the second-hand data, the data was majorly retrieved from the archives of the company. It is through the recorded historical information of the company that we used to identify the statement of the problem that arose hence the study to find their solutions. Sampling design In this research, the sampling design used is the unrestricted sample design. This is because each sample element that was used was drawn individually from the population at large, that is, the all the employee’s records were sampled for the sake of identifying the statement of the problem. I saw it wise to apply this same sampling design to all states of the question since they tend to relate to each other and follow a similar pattern. Data Analysis Procedure Through the use of Excel-Tool Pak as a statistical tool of data analysis, it is convenient for us to conduct a regression analysis to identify the relationship between the employees as the dependent variables and the variables within the model (Pini & Vantini, 2016). Performing a regression analysis is more convenient because it gives convincing conclusions. It also provides room to give policy which might help the business in the future as well it is easy to undertake. SUN COAST REMEDIATION 16 Data Analysis: Descriptive Statistics and Assumption Testing Correlation: Descriptive Statistics and Assumption Testing Frequency distribution table Frequency - Mean Frequency- annual sick Class More Microns days 2 15 1 4 17 6 6 22 31 8 33 42 10 16 19 12 0 4 0 0 SUN COAST REMEDIATION 17 Histogram Frequency Histogram 40 30 20 10 0 Frequency Mcrons Frequency Histogram 50 40 30 20 10 0 Frequency Mean annual sick days per employee Descriptive statistics table mean annual sick days per microns employee Mean 5.66 7.13 Standard Error 0.26 0.19 Median 6 7 Mode 8 7 Standard Deviation 2.59 1.89 Sample Variance 6.73 3.58 SUN COAST REMEDIATION 18 Kurtosis (0.85) 0.12 Skewness (0.37) 0.14 Range 9.8 10 Minimum 0.2 2 Maximum 10 12 582.7 734 103 103 Sum Count Measurement scale The two variables are quantitative in nature and assume a ratio level of measurement. Measure of central tendency The measures of center include the mean, median, and the mode. The mean indicates the center of the data by revealing the most typical value in a group of data. The mean microns is 5.66 while the average mean annual sick days per employee is 7.13 days. The median indicates the center by revealing the middle most value in a group of data arranged in ascending order. The median microns is 6 while the median mean annual sick days per employee is 7. The mode shows the most frequent value. The modal microns is 8 while the modal mean annual sick days per employee is 7. Evaluation The standard deviation shows the dispersion of data from the mean. The standard deviation for microns is 2.59 while the standard deviation for the mean annual sick days per employee is 1.89. The variance indicates the mean square deviations of the data points from the mean. The variance for microns is 6.73 while the variance for the mean annual sick days per SUN COAST REMEDIATION 19 employee is 3.58 days. The coefficient of skewness reveals the shape of the distribution of the data relative to the normal curve. The skewness for microns is -0.37 implying that the data points are negatively skewed while the skewness for mean annual sick days is 0.14 implying that the data points are slightly positively skewed. The histogram for the two variable appears to approximately assume a normal distribution. Additionally, the frequency table indicates no presence of outliers. Lastly, the variables assume ratio scales of measurement. Assumptions for parametric statistical testing are met (Mooi, Sarstedt, & Mooi-Reci, 2018). Simple Regression: Descriptive Statistics and Assumption Testing Frequency distribution table Bin range Frequency More 40 5 80 15 120 27 160 32 200 51 240 44 280 28 320 15 360 6 0 SUN COAST REMEDIATION 20 Histogram 60 40 20 Frequency More 360 320 280 240 200 160 120 80 0 40 Frequency Histogram Lost time hours Descriptive statistics table safety training expenditure lost time hours Mean 595.98 188.00 Standard Error 31.48 4.80 Median Mode 507.772 190 234 190 Standard Deviation 470.05 71.73 Sample Variance 220,948.85 5,144.54 Kurtosis 0.44 (0.50) SUN COAST REMEDIATION Skewness 21 0.95 Range (0.08) 2251.404 350 Minimum 20.456 10 Maximum 2271.86 360 132904.517 41925 223 223 Sum Count Measurement scale The values for the two variables have an origin i.e. zero and as such assume a ratio scale of measurement. Measure of central tendency The measures of center include the mean, median, and the mode. The mean indicates the center of the data by revealing the most typical value in a group of data. The mean safety training expenditure is $595.98 while the mean lost time hours is 188 hours. The median indicates the center by revealing the middle most value in a group of data arranged in ascending order. The median safety training expenditure is 507.77 while the median lost time hours is 190. The mode shows the most frequent value. The modal safety training expenditure is 234 while the lost time hours is 190. Evaluation The standard deviation shows the dispersion of data from the mean. The standard deviation for safety training expenditure is 470.05 while the standard deviation for the lost time SUN COAST REMEDIATION 22 hours is 71.73. The variance indicates the mean square deviations of the data points from the mean. The variance for safety training expenditure is 220,948.85 while the variance for the lost time hours is 5,144.54 hours. The coefficient of skewness reveals the shape of the distribution of the data relative to the normal curve. The skewness for safety training expenditure is 0.95 implying that the data points are positively skewed while the skewness for lost time hours is 0.08 implying that the data points are slightly negatively skewed. The histogram for the dependent variable appears to approximately assume a normal distribution. Additionally, the frequency table indicates no presence of outliers. Lastly, the variables assume ratio scales of measurement. Assumptions for parametric statistical testing are met. Multiple Regression: Descriptive Statistics and Assumption Testing Frequency distribution table Bin range Frequency 105 4 110 32 115 108 120 216 125 332 130 436 135 304 140 69 145 2 SUN COAST REMEDIATION More 23 0 Histogram Frequency Histogram 600 400 200 Frequency 0 Decibel Descriptive statistics table Frequency Angle in Chord Velocity (Meters Displace Decib (Hz) Degrees Length per Second) ment el 0.011139 124.8 88 359 0.000339 0.177 199 945 0.004957 125.7 41 21 0.005295 127.3 14 15 0.013150 6.898 234 657 2886.3805 6.78230206 0.116140 Mean Standard Error Median Mode Standard Deviation 72 3 053 50.86074518 81.317811 0.15265283 0.001256 19 1600 2000 5 5.4 0 368 0.1176 0.0917 0.401686079 39.6 39.6 3152.5731 5.91812812 0.048707 37 5 555 15.5727844 SUN COAST REMEDIATION Sample 24 9938717.3 Variance 0.002372 84 35.0242405 426 - - 242.5116138 77 3 484 47.59 929 146 - 5.7086850 0.41295079 1.178196 Kurtosis 0.000172 -1.563951274 2.218903 0.314 124 19 - - 2.1370843 0.68916440 0.027537 Skewness 37 Range 19800 Minimum 200 Maximum 20000 2 22.2 0 22.2 436 0.1697 0.03 0.1997 0.235852414 39.6 31.7 71.3 1.702164 0.418 556 95 0.058010 37.60 618 7 0.000400 103.3 682 8 0.058411 140.9 3 87 16.74324 18762 Sum 4338230 Count 1503 10193.8 174.5585 1503 1503 76443.7 023 8.4 1503 1503 1503 Measurement scale All the variables; Frequency (Hz), Angle in Degrees, Chord Length, Velocity (Meters per Second), displacement, and decibel are quantitative in nature and assume a ratio scale of measurement. SUN COAST REMEDIATION 25 Measure of central tendency The mean indicates the center of the data by revealing the most typical value in a group of data (Mendenhall, Sincich, & Boudreau, 2016). The mean for Frequency (Hz), Angle in Degrees, Chord Length, Velocity (Meters per Second), displacement, and decibel is 2886.38, 6.78, 0.116, 50.86, 0.11, and 124.85, respectively. The median indicates the center by revealing the middle most value in a group of data arranged in ascending order. The median for Frequency (Hz), Angle in Degrees, Chord Length, Velocity (Meters per Second), displacement, and decibel is 1600, 5.4, 0.1176, 39.6, 0.00496, and 125.72, respectively. The mode shows the most frequent value in a group of data. The median for Frequency (Hz), Angle in Degrees, Chord Length, Velocity (Meters per Second), displacement, and decibel is 2000, 0, 0.0917, 39.6, 0.0053, and 127.32, respectively. Evaluation The standard deviation shows the dispersion of data from the mean. The standard deviation for Frequency (Hz), Angle in Degrees, Chord Length, Velocity (Meters per Second), displacement, and decibel is 3152.57, 5.91, 0.049, 15.57, 0.013, and 6.899, respectively. The variance indicates the mean square deviations of the data points from the mean. The coefficient of skewness reveals the shape of the distribution of the data relative to the normal curve. The skewness for Frequency (Hz), Angle in Degrees, Chord Length, Velocity (Meters per Second), displacement, and decibel is 2.14, 0.69, 0.028, -0.28, 1.70, and 0.419, respectively. The histogram for the dependent variable appears to approximately assume a normal distribution. Additionally, the frequency table indicates no presence of outliers. Lastly, the variables assume ratio scales of measurement. Assumptions for parametric statistical testing are met. SUN COAST REMEDIATION 26 Independent Samples t Test: Descriptive Statistics and Assumption Testing Frequency distribution table Bin range Frequency 78 7 81 10 84 12 87 14 90 11 93 5 96 2 99 1 More 0 Histogram 15 10 5 Frequency Bin range More 99 96 93 90 87 84 81 0 78 Frequency Histogram SUN COAST REMEDIATION 27 Descriptive statistics table Group A Prior Training Group B Revised Training Scores Scores Mean 69.79032258 84.77419355 Standard Error 1.402788093 0.659478888 Median 70 85 Mode 80 85 11.04556449 5.192741955 122.004495 26.96456901 Kurtosis -0.77667598 -0.352537913 Skewness -0.086798138 0.144084526 Range 41 22 Minimum 50 75 Maximum 91 97 4327 5256 62 62 Standard Deviation Sample Variance Sum Count Measurement scale SUN COAST REMEDIATION 28 The values for the two variables are quantitative in nature and have a point of origin i.e. zero. As such, they assume a ratio scale of measurement. Measure of central tendency The measures of center include the mean, median, and the mode. The mean indicates the center of the data by revealing the most typical value in a group of data. The mean Group A Prior Training Scores is 69.790 while the average Group B Revised Training Scores is 84.77. The median indicates the center by revealing the middle most value in a group of data arranged in ascending order. The median Group A Prior Training Scores is 70 while the median Group B Revised Training Scores is 85. The mode shows the most frequent value. The modal Group A Prior Training Scores is 80 while the Group B Revised Training Scores is 85. Evaluation The standard deviation shows the dispersion of data from the mean. The standard deviation for Group A Prior Training Scores is 11.04 while the standard deviation for the Group B Revised Training Scores is 5.19. The variance indicates the mean square deviations of the data points from the mean. The variance for Group A Prior Training Scores is 122 while the variance for Group B Revised Training Scores is 26.96. The coefficient of skewness reveals the shape of the distribution of the data relative to the normal curve. The skewness for Group A Prior Training Scores is -0.09 implying that the data points are slightly negatively skewed while the skewness for Group B Revised Training Scores is 0.144 implying that the data points are slightly positively skewed. The histogram for the dependent variable appears to approximately assume a normal distribution. Additionally, the frequency table indicates no presence of outliers. Lastly, the SUN COAST REMEDIATION 29 variables assume ratio scales of measurement. Assumptions for parametric statistical testing are met. Dependent Samples (Paired-Samples) t Test: Descriptive Statistics and Assumption Testing Frequency distribution table Bin range More Frequency 10 3 20 6 30 9 40 13 50 17 60 1 0 Histogram Frequency Histogram 20 15 10 5 0 Frequency Bin range SUN COAST REMEDIATION 30 Descriptive statistics table Pre-Exposure Post-Exposure μg/dL μg/dL Mean 32.85714286 33.28571429 Standard Error 1.752306546 1.781423416 Median 35 36 Mode 36 38 Deviation 12.26614582 12.46996391 Sample Variance 150.4583333 155.5 Kurtosis -0.576037127 -0.654212507 Skewness -0.425109654 -0.483629097 50 50 Minimum 6 6 Maximum 56 56 1610 1631 49 49 Standard Range Sum Count Measurement scale The values for the two variables are quantitative in nature and have a point of origin i.e. zero. As such, they assume a ratio scale of measurement. SUN COAST REMEDIATION 31 Measure of central tendency The measures of center include the mean, median, and the mode. The mean indicates the center of the data by revealing the most typical value in a group of data. The mean Pre-Exposure μg/dL is 32.857 while the average Post-Exposure μg/dL is 33.286. The median indicates the center by revealing the middle most value in a group of data arranged in ascending order. The median Pre-Exposure μg/dL is 35 while the median Post-Exposure μg/dL is 36. The mode shows the most frequent value. The modal Pre-Exposure μg/dL is 36 while the Post-Exposure μg/dL is 38. Evaluation The standard deviation shows the dispersion of data from the mean. The standard deviation for Pre-Exposure μg/dL is 12.266 while the standard deviation for the Post-Exposure μg/dL is 12.47. The variance indicates the mean square deviations of the data points from the mean. The variance for Pre-Exposure μg/dL is 150.458 while the variance for Post-Exposure μg/dL is 155.5. The coefficient of skewness reveals the shape of the distribution of the data relative to the normal curve. The skewness for Pre-Exposure μg/dL is -0.425 implying that the data points are negatively skewed while the skewness for Post-Exposure μg/dL is 0.144 implying that the data points are negatively skewed. The histogram for the dependent variable appears to approximately assume a normal distribution. Additionally, the frequency table indicates no presence of outliers. Lastly, the variables assume ratio scales of measurement. Assumptions for parametric statistical testing are met. SUN COAST REMEDIATION 32 ANOVA: Descriptive Statistics and Assumption Testing Frequency distribution table Bin range Frequency 3 1 4 3 5 7 6 6 7 2 8 1 More 0 Histogram Histogram Frequency 8 6 4 2 Frequency 0 3 4 5 6 7 8 More Bin range Descriptive statistics table A = Air B = Soil C= D= Water Training SUN COAST REMEDIATION Mean 33 8.9 9.1 7 5.4 Standard Error 0.68 Median Mode 0.39 0.58 0.27 9 9 6 5 11 8 6 5 Standard Deviation 3.06 1.74 2.58 1.19 Variance 9.36 3.04 6.63 1.41 Kurtosis (0.63) 0.12 (0.24) 0.25 Skewness (0.36) 0.49 0.76 0.16 Sample Range 11 7 9 5 Minimum 3 6 3 3 Maximum 14 13 12 8 178 182 140 108 20 20 20 20 Sum Count Measurement scale The data variables assume are quantitative in nature and assume a ratio scale of measurement. SUN COAST REMEDIATION 34 Measure of central tendency The measures of center include the mean, median, and the mode. The mean indicates the center of the data by revealing the most typical value in a group of data. The mean ROI in air is 8.9%, in soil is 9.1%, in water is 7% and in training is 5.4%. The median indicates the center by revealing the middle most value in a group of data arranged in ascending order. The median ROI is Air, Soil, Water and training is 9%, 9%, 6%, and 5%, respectively. The mode shows the most frequent value. The mode for ROI is Air, Soil, Water and training is 11%, 8%, 6%, and 5%, respectively Evaluation The standard deviation shows the dispersion of data from the mean. The standard deviation for ROI is Air, Soil, Water and training is 3.06%, 1.74%, 2.58%, and 1.19%, respectively. The variance indicates the mean square deviations of the data points from the mean. The variance for ROI is Air, Soil, Water and training is 9.36%, 3.04%, 6.63%, and 1.41%, respectively. The coefficient of skewness reveals the shape of the distribution of the data relative to the normal curve. The skewness for ROI is Air, Soil, Water and training is -0.36%, 0.49%, 0.76%, and 0.16%, respectively. As such, the ROI for Air is negatively skewed, while the ROI for soil, water, and training is positively skewed. The histogram for the dependent variable appears to approximately assume a normal distribution. Additionally, the frequency table indicates no presence of outliers. Lastly, the variables assume ratio scales of measurement. As such, assumptions for parametric statistical testing are met. SUN COAST REMEDIATION 35 Data Analysis: Hypothesis Testing Correlation: Hypothesis Testing Restate the hypotheses: Ho1: There is no statistically significant relationship between microns and mean annual sick days per employee. Ha1: There is a statistically significant relationship between microns and mean annual sick days per employee. Excel output SUMMARY OUTPUT mean annual sick days per microns microns employee 1 mean annual sick days per employee 0.715984185 1 Regression Statistics Multiple R 0.715984185 R Square 0.512633354 Adjusted R Square 0.507807941 SUN COAST REMEDIATION Standard Error 36 1.327783455 Observations 103 ANOVA Significance df Regression SS MS 1 187.2953239 187.2953 Residual 101 178.0638994 1.763009 Total 102 365.3592233 F F 106.2362 1.89059E-17 Standard Coefficients Intercept Error 10.08144483 0.315156969 Upper t Stat P-value 31.98865 0.522376554 0.050681267 95% 0.000 9.456258184 10.70663 microns Lower 95% -10.3071 1.89E-17 0.622914554 -0.42184 Notably, the Pearson correlation coefficient f r = -0.71598 indicating a strong positive correlation between microns and mean annual sick days per employee. This results in an r2 of 0.5126 explaining 51.26% of the variations between the two variables. Deploying a significance level of 0.05, the results show a p-value of 0.000 0.05 indicating that the coefficient is not statistically significant. The regression model is given by; Y =126.82 -240.506*(Displacement)+0.083*(Velocity)-5.495*(Chord length)+0.0473*(Angle degrees)-0.0011*Frequency Hypothesis testing looks for significant relationships between variables or significant differences between variables or groups. The t-Test is used to compare two means and is the SUN COAST REMEDIATION 41 simplest form of a test of differences. While, ANOVA is used to compare more than two means. Below are some samples of both t-test and ANOVA hypothesis testing. Independent Samples t-Test: Hypothesis Testing H0: There is no statistically significant difference in the mean values for the training scores between Group A (Prior) and Group B (Revised). Ha: There is a statistically significant difference in the mean values for the training scores between Group A (Prior) and Group B (Revised). Excel output t-Test: Two-Sample Assuming Unequal Variances Mean Variance Observations Hypothesized Mean Difference Df t Stat Group A Group B Prior Revised Training Training Scores Scores 69.79032258 84.77419355 122.004495 26.96456901 62 0 87 9.666557191 P(T
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