Unit VIII PowerPoint Presentation

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.

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 tested 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 49 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.

Particulate Matter (PM) Article

Air pollution is an important topic when studying health related fields. According to “Associations of Mortality with Long-Term Exposures to Fine” (Ostro et.at 2015), fine and ultrafine particulates matters have effect on health such that it causes mortality. This paper aims to evaluate the correlation between long exposure to particulate matters and mortality rate. The authors conducted qualitative research to determine the association between the two variables. The study revealed that individual component of ultrafine particulate matters contribute to mortality as a result of ischemic heart disease. This article will aid the Sun Coast project since it shows existence of possible relationship between exposer to ultrafine particle and health problem.

Safety Training Effectiveness Article

Occupation safety is important in organizations since it is conducted to ensure people understand the safety measures they should apply to minimize cases of getting harmed while at work. According to “Effectiveness of Participatory Training” (Yu, Li, Wan, & Xie, 2017), the aim of the study conducted was to investigate the effectiveness of participatory training in preventing occupation injuries. The finding of the quantitative study revealed that participatory safety training has significant impact on decreasing the number and degree of accidentals occupation injuries and re-injury. In addition, the training program should be conducted in short sessions by experts and the article will aid the Sun Coast project whereby participatory training has the potentiality to reduce the lost-time hours.

Sound-Level Exposure Article

Sound level exposure is another problem such that it becomes a challenge to predict noise exposure. According to “A Stochastic Simulation Framework for the Prediction” (Han, Yahya, Haron, & Domon, 2015), quantitative research, case-based design was conducted aiming to develop and test a model of predicting noise level. The results implied high prediction accuracy with low error margin which indicated that the developed model could be applied in predicting noise-level in Sun Coast or a similar method could be developed. This article is important to this project because it will enable identification of a mod; that should be used to predict sound levels and contribute to development of occupation safety practices in Sun Coast.

New Employee Training Article

New employees need to be trained and oriented to the organization. Organization leaders are mandated to ensure training of new employees so that they are aligned with organization goals. Training of new employees enables them to acquire information that will assist them in integrating in the system quickly and smoothly. According to “The Importance of Training and Development in Employee Performance and Evaluation” (Rodriguez and Walters, 2017), training of new employees enables them to be integrated into the attainment of overall goals such as improving their sense of security, improving morale, overall competency and employee’s engagement. This article will aid the project in determining the importance of training and development, as well as employee performance assessment approaches to ensure prior training is important in the revised training.

Lead Exposure Article

Lead exposure to employees is determined by testing the blood lead levels. The blood level of those who are not exposed to high level of lead is 25 μg/dL. Lead exposed individuals shows a result of over 30 μg/dL. According to “Evaluation and Management of Lead Exposure” Kim et.al, (2015), exposure to lead causes chronic and acute health effects. It affects various organs such as hematopoietic, nervous, and cardiovascular system among others. The study conducted revealed that lead is also carcinogenic and it can cause death in severe cases. This article will impact the Sun Coast project by showing the effects of lead exposure.

Return on Investment Article

Return on investment is used in making strategic decision of investment and form an integral part in organization policy. According to “Return on Investment – Indicator for Measuring the Profitability of Invested Capital” (Zamfir, Manea, and Uonesxu, 2016), The Return on Investment indicators are used to analyze investment projects. Return on investment size is influenced by assets valuation, and the method of calculating working capital. The results obtained in Return on investment enable the investor to determine projects that are profitable and those that are note. This article is important to Sun Coast projects since it provide strategies of analyzing Return On Investment to evaluate which line of serve among the four is profitable over others.

Six business problems were identified in this research, which developed various questions. Therefore, specific steps are taken to find the answers to these questions so as to achieve the aim of the research. As such, the following research objective, questions and hypotheses have been developed;

RQ1: Is there a connection between the size of particulate matter and health?

Ho1: Statistically no notable connection between the size of particulate matter and health.

Ha1: Statistically there is a notable connection between particulate size and health.

RO2: Find out if a safety training decreases lost-time hours.

RQ2: What is the connection between safety training and lost-time hours?

Ho2: Statistically no notable connection between safety training and lost-time hours.

Ha2: Statistically there is a notable connection between safety training and lost-time hours.

RO3: Determine if excess levels of decibels (dB) correlate with work environment noise variables

RQ3: Is there a correlation between levels of decibels (dB) and noise variables?

Ho3: Statistically no notable correlation between the levels of decibels (dB) and noise variables

Ha3: Statistically there is notable correlation between the levels of decibels (dB) and noise variables.

RO4: Find out if revised training program is more effective compared to the prior training program

RQ4: What are knowledge differences between revised training program (Group B) and prior training program (Group A)?

Ho4: Statistically no notable knowledge difference between revised training program (Group B) and prior training program (Group A)

Ha4: Statistically, there are notable knowledge differences between revised training program (Group B) and prior training program (Group A)

RO5: Find out if there is a connection of lead levels to remediation exposure.

RQ5: What is the connection between the levels of lead and remediation exposure?

Ho5: Statistically no notable connection between the levels of lead and remediation exposure.

Ha5: Statistically there is notable connection between the levels of lead and remediation exposure.

RO6: Determine the return on investment (ROI) contrasts that are between the four lines of customers (air monitoring, soil remediation, water reclamation, and health and safety training).

RQ6: What are contrasts in return on investment, which are between the four lines of customers?

Ho6: Statistically, no notable return on investment contrasts that are between health and safety training, soil remediation, water reclamation and air monitoring.

Ha6: Statistically, there are notable return on investment contrasts that are between health and safety training, soil remediation, water reclamation and air monitoring.

For the Sun Coast Project's aims and research questions, this article outlines the research strategy and methodology used. Notably, the research opponents and queries concern the impacts of pollutants, the performance of safety awareness, subject to extreme sound levels, the element of exercise and realigning new staff, the impacts of lead exposure and the payback period for the Sun Coast service areas of service. Designs and procedures are based on quantitative research carried out during the investigation. It also covers the data gathering methods used in the study, the sampling strategy, and the data processing protocols.

Research Methodology

Because of its applicability and objectivity to the research issues being studied, quantitative research technique is the major methodology utilized in the study. In part, this is because the study and analysis produced valid and trustworthy results. A bigger, generalized, or random sample can be used to guarantee the data is free of bias (Ishimoto, 2020).

Research Design

A quantitative approach and a philosophical outlook are both used in this particular form of research. The research design used in this work is a descriptive one, rather than an experimental one. Due to the design's ability to gather correlational and measurable data for the study analysis with respect to the data relevant to the research topics (Mantasiah, 2019).

Research Methods

These processes include those determined from the design and methodology. Case studies, observation, and surveys are among the research methodologies used in this study, which combines correlational and descriptive research approaches. Using the descriptive technique, you describe where things are right now in relation to the study questions or variables you've selected. Using the obtained statistical data and the correlational research method, researchers can figure out the link amongst two or more independent variables that are relevant to the study's research questions (Mofolo, 2019).

Data Collection Methods

If you're interested in learning more about the connection amongst particulates and health, lead poisoning, or being exposed to high degrees of sound, record analysis can help you gather the information you need. In order to answer the study doubts about the validity of safety awareness and the training of new employees, the techniques used have included survey of staff members.

Sampling Design

The convenient sampling design was the sampling strategy used in this case. Here, the samples are taken from a subset of a larger group that is more closely associated with a particular research subject under investigation (Falgore, 2019).

Data Analysis Procedures

Testing the RQ1 for a link between PM and employee health is best done through correlation analysis. Due to correlation determining if there is an association between variables, this can be said (independent and dependent). The RQ2 link between training expenditure and lost time is tested using a simple regression analysis. This is accomplished through the use of linear graphs. There are several factors on the RQ3 that have to do with exposure to sound levels. There are a variety of factors that go into determining dB levels at construction sites, such as angle, displacement, frequency, velocity, and the length of the sound's chord. As a result, the hypothesis is put to the test using multiple regression analysis (Thurber,2020). If the new training program is more effective, then RQ4 should be answered affirmatively; otherwise, Because of this, the hypothesis is tested by comparing the knowledge and performance of employees before and after training using an independent t-test data analysis. In order to check for levels of lead in the workers, RQ5 opted to make use of paired t-test analysis. To find the average difference between the two sets of data, each member of the sample was examined twice. The ANOVA analysis was used to assess the Return on Investment (RQ3) hypothesis (the analysis of variance). This includes figuring out if the means of the four Sun Coast services differed.

Frequency Distribution Table

Histogram

Descriptive Statistics Table

Measurement Scale

Job site is a nominal measurement of scale since the difference, addition, multiplication of variables cannot be established. Microns is an ordinal measurement of scale.

Measure of Central Tendency

The mean of the mean annual sick days per employee is 7.126, the median is 7 and the mode is 7.

Skewness and Kurtosis

The data is skewed to the right since it has a positive value.

Evaluation

The annual mean sick days for employee had a mean of 7.126. The mode was 7 and the median was also 7. The maximum sick days for employees was 12 and the minimum sick days was 2. The assumptions for parametric statistical were not met since data from multiple groups had different variance.

Frequency Distribution Table

Histogram

Descriptive Statistics Table

Measurement Scale

The measurement of scale used was nominal.

Measure of Central Tendency

The mean for lost hours was 188.0045, the median was 190 and the mode was 190. The less they spend in training the more employees get sick.

Skewness and Kurtosis

The lost time hour’s data is skewed to the left. The distribution is light tailed.

Evaluation

The distribution in this case indicates a summary of the frequency of individual values. The mean for lost hours was 188.0045, the median was 190 and the mode was 190. The standard deviation is 71.725 which means approximately 68% of the lost time hours fall within its mean. The assumption for parametric statistical testing were not met since the data did not have a normal distribution.

Frequency Distribution Table

Histogram

Descriptive Statistics Table

Measurement Scale

The measurement of scale used was nominal.

Measure of Central Tendency

The velocity mean was 50.86, the median was 39.6 while the mode was 39.6.

Skewness and Kurtosis

The data set is skewed to the right. The data has a heavy tailed distribution. Both the skewness and Kurtosis were within acceptable range.

Evaluation

The distribution in this case indicates a summary of the frequency of individual values. The mean for velocity was 50.86, the median was 39.6 and the mode was 39.6. The standard deviation is 15.57. The assumption for parametric statistical testing were not met since the data did not have a normal distribution.

Frequency Distribution Table

Histogram

Descriptive Statistics Table

Measurement Scale

The measurement of scale used was ratio since the sequence of variables, mode, median, mean, difference between variables, addition, subtraction, multiplication, and division can be established

Measure of Central Tendency

The mean for group A was 69.79 while that for group B was 84.77, the median for group A was 70 while that for group B was 85, while the mode for group A 80 and for group B was 85.

Skewness and Kurtosis

The data for group A is slightly skewed to the left while the data for group B is slightly skewed to the right. Both data sets have light tailed distribution.

Evaluation

The distribution in this case indicates a summary of the frequency of individual values. The mean, median, and mode of both data sets are nearly the same. The assumption for parametric statistical testing were met since the data have a normal distribution.

Frequency Distribution Table

Histogram

Descriptive Statistics Table

Measurement Scale

The measurement of scale used was nominal.

Measure of Central Tendency

The mean for pre-exposure was 32.86, and for post-exposure 33.29. The median for pre-exposure is 35, and for post exposure is 36. The mode for pre-exposure is 36 while that of post exposure is 38.

Skewness and Kurtosis

Both data sets are skewed to the left. The data has a heavy tailed distribution. Both the skewness and Kurtosis were within acceptable range.

Evaluation

The distribution in this case indicates a summary of the frequency of individual values. The mean, median, and mode of both data sets are nearly the same. The assumption for parametric statistical testing was met since the data have a normal distribution.

Frequency Distribution Table

Histogram

Descriptive Statistics Table

Measurement Scale

The measurement of scale used here was ratio

Measure of Central Tendency

The mean for return on investment on air was 8.9. The median was 9 while the mode was 11

Skewness and Kurtosis

All the data was skewed to the right. Both the skewness and Kurtosis were outside acceptable range.

Evaluation

The distribution in this case indicates a summary of the frequency of individual values. The mean, median, and mode of both data sets are nearly the same. The assumption for parametric statistical testing was met since the data have a normal distribution.

Correlation: Hypothesis Testing

RO1: Find out if the size of particulate matter (PM) has a connection with the health of the employees.

RQ1: Is there a connection between the size of particulate matter and health?

Ho1: Statistically no notable connection between the size of particulate matter and health.

Ha1: Statistically there is a notable connection between particulate size and health

As the microns increases, the mean annual sick days per employee reduces. The gradient is -0.5224.

Simple Regression: Hypothesis Testing

RO2: Find out if a safety training decreases lost-time hours.

RQ2: What is the connection between safety training and lost-time hours?

Ho2: Statistically no notable connection between safety training and lost-time hours.

Ha2: Statistically there is a notable connection between safety training and lost-time hours.

From the table above, it can be concluded that the equation is y= - 0.1433x + 273.45

Additionally, since the regression was carried out at the 95% confidence interval, there is a good relationship between the lost hours and the safety training expenditure not a coincidental since the p value is 7.7E-105 (Illowsky, Dean, & Illowsky, 2017).

The residues are as follows;

Multiple Regression: Hypothesis Testing

RO3: Determine if excess levels of decibels (dB) correlate with work environment noise variables

RQ3: Is there a correlation between levels of decibels (dB) and noise variables?

Ho3: Statistically no notable correlation between the levels of decibels (dB) and noise variables

Ha3: Statistically there is notable correlation between the levels of decibels (dB) and noise variables.

From the immediate above table, the y variable was the decibel. The equation from the above table is as follows;

Y=-0.00112x1 + 0.04734 x2 – 5.495x3 + 0.08324 x4 – 240.506 x5 + 126

Independent Samples t Test: Hypothesis Testing

RO4: Find out if revised training program is more effective compared to the prior training program

RQ4: what are knowledge differences between revised training program (Group B) and prior training program (Group A)?

Ho4: Statistically no notable knowledge difference between revised training program (Group B) and prior training program (Group A)

Ha4: Statistically, there are notable knowledge differences between revised training program (Group B) and prior training program (Group A)

Accepting the null hypothesis given the 95% confidence interval was used, one tailed test shows relationship between the variables because the p-value was 1.31E-14. The revised training program should be considered to replace the current training program.

Dependent Samples (Paired Samples) t Test: Hypothesis Testing

RO5: find out if there is a connection of lead levels to remediation exposure.

RQ5: what is the connection between the levels of lead and remediation exposure?

Ho5: Statistically no notable connection between the levels of lead and remediation exposure.

Ha5: Statistically there is notable connection between the levels of lead and remediation exposure.

The p-value is 0.059553 which rejects the alternative hypothesis and accepts the null hypothesis. There is no difference in lead levels in the blood between pre-exposure and post-exposure.

ANOVA: Hypothesis Testing

RO6: Determine the return on investment (ROI) contrasts that are between the four lines of customers (air monitoring, soil remediation, water reclamation, and health and safety training).

RQ6: What are contrasts in return on investment, which are between the four lines of customers?

Ho6: Statistically, no notable return on investment contrasts that are between health and safety training, soil remediation, water reclamation and air monitoring.

Ha6: Statistically, there are notable return on investment contrasts that are between health and safety training, soil remediation, water reclamation and air monitoring.

Seeing that the p-value is 1.76 × 10−6, it can be determined to reject the null hypothesis and accepts the alternative hypothesis. There is a return on the investment and the different service lines that Sun Coast offers.

The results of the statistical testing showed that an employee’s number of sick days averaged and there was no correlation to the particulate size and their health. We would, therefore, expect to see no difference in the number of sick days an employee takes versus another. This determination suggests there should be no conclusive data to show that the health of an employee is affect by the particulate matter.

RO2: Find out if a safety training decreases lost-time hours.

The results of the statistical testing showed that the lost-time hours decreases as there are more safety trainings. The assumption for parametric statistical testing were not met since the data did not have a normal distribution. We would, therefore, expect to see the relationship between the lost hours and safety training expenditure not coincidental. This determination suggests that the more safety training an employee has, the less time is lost.

RO3: Determine if excess levels of decibels (dB) correlate with work environment noise variables.

The results of the statistical testing showed that we can predict the approximate amount of decibel levels of the work environment before place employees on site. The assumption for parametric statistical testing were not met since the data did not have a normal distribution. We would, therefore, expect there is a notable correlation between the levels of decibels and noise variables. This determination suggests that the levels of decibels be decreased before the employees are on site.

RO4: Find out if revised training program is more effective compared to the prior training program.

The results of the statistical testing showed that the revised training program is more effective compared to the prior training program. The assumption for parametric statistical testing were met since the data have a normal distribution. We would, therefore, expect to see those employees who have taken the new training to have a greater success rate than those with the prior training. This determination suggests that the company replaces the current training program with the new training program.

RO5: Find out if there is a connection of lead levels to remediation exposure.

The results of the statistical testing showed that there is no connection of lead levels to remediation exposure and rejects the alternative hypothesis and accepts the null hypothesis. . The assumption for parametric statistical testing was met since the data have a normal distribution. There is no difference in lead levels in the blood between pre-exposure and post-exposure. We would, therefore, expect to see no change pre-exposure or after exposure to the lead levels.

RO6: Determine the return on investment (ROI) contrasts that are between the four lines of customers (air monitoring, soil remediation, water reclamation, and health and safety training).

The results of the statistical testing showed that the return on investment contrasts that are between the health and safety training, soil remediation, water reclamation, and air monitoring. The assumption for parametric statistical testing was met since the data have a normal distribution. We would, therefore, expect to see that the testing is completed. It can be determined to reject the null hypothesis and accepts the alternative hypothesis. There is a return on the investment and the different service lines that Sun Coast offers.

Recommendations

Particulate Matter Recommendation

The recommendation for Particulate Matter in this research would be a null to the hypothesis. This is suggested since as the number of particulate matter increases, the employees’ sick days’ decreases.

Safety Training Effectiveness Recommendation

The recommendation for safety training effectiveness would be to increase an employee’s training in order to lower time lost. This is suggested since as the number of safety training hour’s increases, the employees’ lost time hours decrease.

Sound-Level Exposure Recommendation

The recommendation for sound-level exposure would be to decrease the exposure to the decibel levels in the work environment. This is suggested since as the level of decibels levels increase, the sound exposure is higher and affects the employees.

New Employee Training Recommendation

The recommendation for new employee training would be to replace the current training with the new training. This is suggested due to accepting the null hypothesis given the 95% confidence interval.

Lead Exposure Recommendation

The recommendation for lead exposure would be no change in current procedures. This is suggested due to and rejects the alternative hypothesis and accepts the null hypothesis.

Return on Investment Recommendation

The recommendation for return on investment would be to proceed with the four lines of customers. This is suggested due to rejecting the null hypothesis and accepts the alternative hypothesis.

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th Ed.). SAGE.

Falgore, J. Y., Doguwa, S. I., & Isah, A. (2019). The weibull-inverse lomax (WIL) distribution with application on bladder cancer. Biometrics & Biostatistics International Journal, 8(5), 195-202.

Fisher, M. J., & Marshall, A. P. (2009). Understanding descriptive statistics. Australian critical care, 22(2), 93-97.

Han, L., Yahya, K., Haron, Z., & Domon, M. (2015). A stochastic simulation framework for the prediction of strategic noise mapping and occupational noise exposure using the random walk approach. PloS One 10(4), 1-28.

Illowsky, B., Dean, S. L., & Illowsky, B. (2017). Introductory statistics.

Ishimoto, M. (2020). Schoolscapes in Multicultural Centers in Finland: How Staff Members Perceive Multilingualism

Kim, H. e. (2015). R E V I E W Open AccessEvaluation and management of leadexposure. Annals of Occupational and Environmental Medicine , 27-30.

Mantasiah, R., Yusri, Y., Syaputra, A. F., Angreany, F., Hasmawati, H., & Anwar, M. (2019, December). Assessing Mistake Potential in Writing German Passive Sentences (An Approach of Language Error Analysis). In Seminar Nasional LP2M UNM.

Mofolo, M. A., Mosala, G., Al Halbusi, H., Ismail, M. N. B., Omar, S. B., Keyghobadi, A., ... & Abubakar, A. (2019). Arabian Journal of Business & Management Review (Kuwait chapter). Arabian Journal of Business &, 8(1).

Nick, T. G. (2007). Descriptive statistics. Topics in biostatistics, 33-52.

Ostro, B., & at., e. (2015). Associations of mortality with long-term exposures to fine and ultrafine particles, species and sources: Results from the California Teachers Study Cohort. Environmental Health Perspectives, 123(6), 549-556.

Rodriguez, J., & Walters, K. (2017). The Importance of Training and Development in Employee Performance and Evaluation. World Wide Journal of Multidisciplinary Research and Development 3(10), 206-212.

Thurber, K. A., Thandrayen, J., Banks, E., Doery, K., Sedgwick, M., & Lovett, R. (2020). Strengths-based approaches for quantitative data analysis: A case study using the Australian Longitudinal Study of Indigenous Children. SSM-population health, 12, 100637.

Yu, I., Li, Z., Wan, S. W., & Xie, S. (2017). Effectiveness of participatory training in preventing accidental occupational injuries: A randomized-controlled trial in China. Scandinavian Journal of Work, Environment & Health 43(3), 226-233.

Zamfir, M., Manea, M., & Uonesxu, L. (2016). Return On Investment – Indicator for Measuring the Profitability of Invested Capital . Valahian Journal of Economic Studies, 1-9.

Histogram

Velocity

Frequency

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Prior training Scores

Frequency

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Employee Exposure

Frequency

Histogram

Consulting Project Return on investment

Frequency

Mean Annual Sick Days per Employee

mean annual sick days per employee

4 6.5 8 8 4 7 2 5.5 5 4 4.5 8.5 7 5 9.5 7 9.5 9.5 5 6 8 7.5 8.5 9 3 6 7.5 7.5 2.7 2 7.5 9 6 3 8 1 8.5 0.7 0.5 8.5 2 4.5 6 7 5 2.5 5 4 8 5 3.5 8 5 4.9000000000000004 7.5 2.5 6.5 8 5 7 4 8 1 2 4 4 7 5.2 5 6 8 6 6.5 1.5 8.5 2 8 10 10 8 1 7 10 7 7 6.5 7.5 8.5 3 0.5 1 9 7 2 8.5 3.5 3 7 5.5 7.5 0.2 4 5 11 7 5 5 10 7 11 9 7 10 8 4 7 8 3 7 5 7 10 6 5 6 5 4 7 7 7 5 7 9 6 4 6 8 5 8 5 8 8 4 8 9 7 7 10 12 9 7 5 7 9 6 5 10 9 7 7 6 6 6 9 5 8 8 10 9 7 10 7 6 6 7 6 8 6 8 5 4 5 8 8 6 2 8 6 7 6 6 8 9 8 6 7 9 7 9 8 6 7 7 12 8 9

microns

Mean annual sick days per employee

Histogram

Mean annual sick days per employee

Frequency

Histogram

Lost time hours

Frequency