Analysis Executive Summary 2022

Running head: ANALYSIS 1
Health and Safety Maintenance Analysis
Insert Your Name Here
Insert University Here

ANALYSIS 2
Table of Contents
Executive Summary.....................................................................................................................................3
Introduction.................................................................................................................................................4
Statement of the Problems.........................................................................................................................5
Particulate Matter (PM)...........................................................................................................................5
Safety Training Effectiveness...................................................................................................................5
Sound-Level Exposure.............................................................................................................................6
New Employee Training...........................................................................................................................6
Lead Exposure.........................................................................................................................................6
Return on Investment..............................................................................................................................7
Literature Review........................................................................................................................................7
Research Objectives....................................................................................................................................8
Research Questions and Hypotheses..........................................................................................................9
Research Methodology, Design, and Methods..........................................................................................10
Research Methodology..........................................................................................................................11
Research Design....................................................................................................................................11
Research Methods.................................................................................................................................12
Data Collection Methods...........................................................................................................................12
Sampling Design........................................................................................................................................12
Data Analysis Procedures..........................................................................................................................13
Data Analysis: Descriptive Statistics and Assumption Testing...................................................................14
Correlation: Descriptive Statistics and Assumption Testing...................................................................14
Simple Regression: Descriptive Statistics and Assumption Testing........................................................15
Multiple Regression: Descriptive Statistics and Assumption Testing.....................................................15
Independent Samples t Test: Descriptive Statistics and Assumption Testing........................................17
Dependent Samples (Paired-Samples) t Test: Descriptive Statistics and Assumption Testing...............17
ANOVA: Descriptive Statistics and Assumption Testing.........................................................................18
Data Analysis: Hypothesis Testing.............................................................................................................18
Correlation: Hypothesis Testing.............................................................................................................18
Simple Regression: Hypothesis Testing..................................................................................................18
Multiple Regression: Hypothesis Testing...............................................................................................19
Independent Samples t Test: Hypothesis Testing..................................................................................19
Dependent Samples (Paired Samples) t Test: Hypothesis Testing.........................................................19

ANALYSIS 3
ANOVA: Hypothesis Testing...................................................................................................................19
Findings.....................................................................................................................................................19
Recommendations.....................................................................................................................................20
References.................................................................................................................................................21

ANALYSIS 4
Executive Summary
Before getting to the actual background of the company, there needs to be the actual
understanding on what the whole report will have to carry. As the health and the safety director
of the Sun Coast Remediation company, there will be the requirement of me to conduct analysis
on the dataset that is supposed to be collected on matters health and safety of the employees of
the same company. The company is health related as it involves specific radiation activities that
actually have the actual removal of toxic substances from water as well as soil. So for this fact
the employees come into contact with toxic air and water and all that and therefore in the long
run implicate their visions, hearing capabilities and all. To aid prevent these, there will be data
collected on all the 5500 workers that are involved in the organization and all that be used to
draw different inferences that range from ANOVA tests to t-tests, hypothesis tests, regression
analyses as well as correlation analysis. After the inferences aw drawn, since all that will be
considered will be revolving around, compensation training time, returns and health effects to the
employees, there will be the understanding on how to handle different employees after all the
results that will have been deduced in the long run. Later on there will be a report developed on
all the needed analytical results that will have been developed through excel data analysis tool
Pak.

ANALYSIS 5
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.
Senior leadership as it stands is logically responsible for the safety of all its employees
and for this fact requires that the desires and the welfare of all the employees if its firm is well
taken care of. Looking at the nature of the firm, there needed to be an understanding of what
exactly the environment the workers were working in looked like (Bielinis et al. 2020). This is
clearly spelt out by doing analysis on particulate matter, safety training effectiveness, sound level
exposure, new employee training, lead exposure and return on investment. All the effects that all
these have and the reason for looking into them have all been discussed in the subsections that
will have to follow afterwards (AYADI, 2019).
All companies and not only this one are required to have analytical tabs and knowledge
on matters that affect their employees. This is because, when matters that are of great effect are
known numerically, then definitely, quantitative measures can be planned and executed in the
long run hence making sure that all the interest of employees as well as of the organization are
taken into consideration in all (Dawod & Abdel-Aziz, 2020). In as much as the employees are
always taken into consideration ethically, by most employers, it is very important to note the fact
that employers by default, put the business or the company forward and the actual returns that
there can be realized over time (Bynigeri et al. 2020). The employees therefore, are in all well
taken care of as they are the only ones that will have or help the involved company reach its said

ANALYSIS 6
potential. This is the reason for all the hustle revolving the safeness of all the said employees that
a company might have in a specific time (Bebic, Stazic & Komar, 2019).
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
recorded in microns. Data are also available for average annual sick days per employee per job-
site (Do, 2019).
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

ANALYSIS 7
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 (Do, 2019). 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 (Guerrero,
2019).
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
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 (Laugerman & Saunders,
2019).

ANALYSIS 8
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 post-exposure 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 (Li et al. 2019).
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
Business research analytics has been there for the longest and the name has changed over
time from market research analytics to business analytics and now to data science which largely
involves visualizations and all. Looking at this research study, there is a need for there to be an
analysis of all the dataset that was collected by an earlier health and safety director that left to go
and chase other occupational dreams (Fatima, Shahzadi & Shah, 2020). The datasets that were
collected in the long run were inclusive of all the subsections that have been discussed in the
earlier sub-sections. Like in each and every company, when a role is vacant, especially a role that
drives most of the decisions that are made in an organization, there will always be the need for
the that role to be active to help continue the drive that comes from that role as far as decisions

ANALYSIS 9
that are made are concerned. For this reason, I was employed to have a look into the datasets that
had been formulated but had not been analyzed, this therefore would later aid in the categorical
decision making when looking at how the health of employees are affected as well as how the
determining the return on investments that are to be involved and realized (Fragala-Pinkham et
al. 2020).
The above paragraph has given the pronunciation and the listings of what are needed to
be done for this research project. This section though is a literature review and for this fact there
will be a requirement of the topics and different scenarios of business analytics research to be
discussed in depth in this case. Research analytics covers a broad area and is inclusive of market
research, operations research as well as industry research. A market researcher in most cases is
tasked with the duty of studying the market in a bid of helping the organizations understand what
type of products or organizations are required by the market (Hassan et al. 2020). An operations
research analyst on the other hand, studies all the processes that there are in a business and looks
for the relevant means to improve them if by any chance they are not at all in anyway improved
and are lagging behind when it comes to the production as well as the actualization of the said
activities (Ho et al. 2020). For this case, my work in this area will be more of a looking at the
aspects of the functions that are there in an organization and what needs to and what needs not to
be improved in the long run. that is why there needs to be an analysis of all the dataset that were
collected by the predecessor. Industry researchers on the other hand, as the name suggests work
for specific industries and these include banks amongst others and they largely only tend to look
at trends after which they advise accordingly (Linnes et al. 2019).

ANALYSIS 10
Research Objectives
Research objectives, looking at the name and what suggests only describes what to expect in the
whole study and research. Where there are no hypotheses, the objectives can be directed as
sentences which will then serve as statements of objectives. On others cases, the statement of
objective is usually linked with hypothesis. The objective statements are usually being made to
be the simplest statements in the long run and this is because a researcher might be addressing a
layman (Young et al. 2020). The fact that the layman is incorporated, higher considerations are
required to aid in the actual connotation and the understanding of other people who might be
having shallower understanding of what is being pursued. In this case, there will be the health
and safety manager addressing the top management and therefore by all means will be required
to have a use of the simplest words that can be understood by the top management as they are not
in a highly specialized zone as the health and safety manager who actually will be involved with
the analysis of datasets and the actual interpretation of the deduced results (Savolainen, 2019).
In this case the objectives that were listed as below;
RO1: To Determine the relationship between particulate matter sizes and the employees’ health.
RO2: To determine the success of training by reducing the lost time in hours.
RO3: To plan the appropriate ear protection for employees by determining sound level exposure
in the environment of work.
RO4: To determine the effectiveness of revised training to prior training in the long run.
RO5: To determine if blood lead levels have gone up are bound to go up by the environment in
which students work in.
RO6: To determine the return on investment on all the services that are conducted by the
company as well as the differences degrees if there are any.

ANALYSIS 11
Research Questions and Hypotheses
The research questions that will be developed in this case are those questions that will be set out
to be answered in this case and therefore will be set out to be answered both qualitatively as well
as quantitatively. Because of this, data will be collected and be analyzed
RQ1: What is the relationship between particulate matter and the employees’ health?
H01: There is a no positive relationship between the particulate matter and the employees’ health.
HA1: There exists a positive relationship between the particulate matter and health of the
employees.
RQ2: Will there be success on training when lost time is hours is reduced?
H02: There is definitely going to be a success on training when the lost time in hours is reduced.
HA2: There is never going to be a success on training when the lost time is hours is reduced.
RQ3: Will there be appropriate protection for different levels of sound?
H03: There are appropriate protection levels for different sound levels.
HA3: There are no appropriate protection levels for different sound levels.
RQ4: Will there be effectiveness of revised training over prior training in the long run?
H04: There will be no effectiveness of revised training over prior training.
HA4: There will be effectiveness of revised training over prior training.
RQ5: Are the environments that students work in making blood levels to go up?
H05: Blood levels will definitely rise by the environment in which students work in.

ANALYSIS 12
HA5: There is a definite bound of the blood levels dropping as per the environment in which
students work in.
RQ6: Are there positive return on investments as well as significant differences?
H06: There are no positive return on investments and no significant differences.
HA6: There are positive return on investments and significant differences.
Research Methodology, Design, and Methods
Research methodology are the procedures and techniques that actually get to identify a
whole group, select samples of interest, process the selected samples that have been selected to
put them in a better way that can be analyzed and therefore finally analyze the well planned
dataset. In this place we will evaluate the studies validity and reliability. Validity in this case will
be to find out how the study is automatically relevant and how it relates to the real world in the
long run (Iyengar, Acharya & Kadam, 2020). Reliability of the study should be indicative in the
sense that if at all the results can be used to make changes on the various parts of study,
especially those that have issues, then there definitely can be the changes that are needed and
with positive results, making all these very reliable in the long run (Stowe, Paulsen, Hill &
Schaffer, 2019).
Research Methodology
In this research case, there was an identification of a sun remediation company that handled lots
and lots of activities for both government as well as the private organizations. As it was indicated
that there will be handling of toxic substances both in water as well as in air. This therefore,
since it is an issue that basically was directed to the company of study that is in question, will
need the inclusion of the company’s workers as well as the data that lies on each and every one
else’s head (Iyyanki & Jayanthi, 2020). As the management therefore, there was a directive of

ANALYSIS 13
me actually going to the line managers and the supervisors in a bid of the collection of the
corresponding dataset entries on each and every employee and that will be used in the different
analysis and parameter determinations (Yin et al. 2020).
Research Design
The strategies for integrating and incorporating different pieces of study into a coherent and
logical manner hence logical way to address the research problem that has been build up.
Research studies can be divided into three different sub categories and these include;
exploratory, descriptive and casual. All of these without any exception do involve the stages of
data collection, measurement and finally analysis (Karlsson, Sanku & Svensson, 2020). For our
case, there needs to be a knowledge that the study design that will be looked into in this case will
be an exploratory as well as a descriptive research study design. The exploratory design comes in
through the explanation of the descriptive datasets that have been made and of the results that are
deduced in the tool of analysis by the health and safety management (Kishi et al. 2020).
Research Methods
Research methods are ways of data collection and they basically include stuff like interviews,
experiments, surveys, questionnaires, case studies, observations and observational traits. In this
case research, the research methods that were use included; observations and observational traits.
Observational traits come in during the observation on how the particulate matter would affect
the breathing system of all the workers that are there in the firm. The observations would come
in when the other financial data points are picked by observations from the records and later
transferred to the actual tool of analysis and later analyzed for inferential results (Kosmidou et al.
2020).

ANALYSIS 14
Data Collection Methods
Data collection and research methods are more of the same when it comes to research study. By
this, there is a clear understanding of the fact data collection methods involve the methods that
are there in the research methods too and these include methods such as questionnaires,
interviews, focus groups, observations and case studies. In this case as was mentioned,
observations will be used in data collection (Krolo et al. 2020).
Sampling Design
Sampling is the method of selecting smaller and reliable portions from a population to create
what is called a sample or samples. The sole reason for using sampling design is actually the fact
that population cannot be easily analyzed as a whole and therefore needs for smaller groups,
called samples to be analyzed instead and derivation to be drawn for the general population.
Sampling is the core of each and every research and the actual sampling methods that we do
have in this case include; simple random sampling and stratified sampling (Loshchenova et al.
2020). According to the analytical methods that are supposed to be carried out, there is need to
actually have all the sampling design and methods used and according to the analysis method
that is to be employed when testing a specific hypothesis and when answering as specific
research question as well as pointing out the solutions to an objective (Mega et al. 2020).
Data Analysis Procedures
The analytical procedures are as provided by the analytical activities that should be carried out
fir the organization and as indicated by the actual parameters that are to be measured for the
company in question. The tool of analysis that will be used is the excel and the tool that will be
used for actual execution of all the analysis will be the analysis tool pak (Pathakoti, Manubolu &
Hwang, 2020). The analysis tool pak, for any excel tool that is not usually having this already

ANALYSIS 15
installed, gets it installed through the excel add in tab. After the add in in complete, then from the
tool pak, one can definitely go ahead and choose the analysis method that is to be run as one
specific point in time. There will be correlation between prior training group and the revised
training groups (Pahriah & Hendrawani, 2020). There will be simple regression data between
lost time in hours as well as safety training expenditure. Multiple regression as well will be
conducted on velocity, displacement and decibel. Independent sample t test, paired sample t test
as well as anova test will also be conducted to help direct and address each and every objective
that will be there in question (Olson & Wu, 2020).
Data Analysis: Descriptive Statistics and Assumption
Testing
As mentioned in the step above, there will be the conducting of the ANOVA test, linear and
multiple regression but with different data variables, correlation test, independent t test and
paired sample t test.
Correlation: Descriptive Statistics and Assumption Testing
This part will be requiring the actual illustration of the results and the actual discussion of the
same results that have been deduced in the long run. starting from the correlation analysis we do
have;
Between microns and mean annual sick days, there is a clarity of there being a stronger negative
correlation. There are only two type of correlation values, those that are negative like in our case

ANALYSIS 16
and they range from below zero up to -1 and the positive ones range from above zero to 1. The
strong correlations are from 0.5 to 1 and -0.5 to -1 (Anderson et al. 2012).
Simple Regression: Descriptive Statistics and Assumption Testing
Starting off at the R-squared value it is very evident that the percentage of variability between
the variables that are being taken into consideration stands at an all-time high and is at 88%. This
is a true representation that there is a positive correlation between the dependent variable and the
independent variable in this case (Sun et al. 2020). Checking at the statistical significance of the

ANALYSIS 17
two variables that have been taken into consideration, we will have a look at the P value. The P
value in this case in both cases are highly negligible as they are way below 0.05 which is the
value of significance. The variables that are being used therefore are statistically significant. This
case has only one independent variable with one dependent variable (Anderson et al. 2012).
Multiple Regression: Descriptive Statistics and Assumption Testing
In this case though there will be two independent variables and one dependent variable as
indicated at the problems identified section.
From the above it is very evident to see the fact that there is a lower degree of variability as the R
square and the Adjusted R square both stand at 36%. This is way lower of variability and the
variable that have been used for the sake of independent variables are seen to be appearing fewer
when it comes to the formulation of the predicted values for the response variable (Tordön et al.
2020).
The p-values for the variables, Frequency, Velocity and Displacement are all statistically
significant as their values are below 0.05 and the last two have their values higher than 0.05
making the two values less statistically significant (Caras, V. (2019).

ANALYSIS 18
Independent Samples t Test: Descriptive Statistics and Assumption
Testing
all the values for the above case are all statistically significant as we have the value of 1.93983E-
15 for the tow-tail p-value.

ANALYSIS 19
Dependent Samples (Paired-Samples) t Test: Descriptive Statistics and
Assumption Testing
The variables used in this case are all statistically significant because of the fact that the p-value
of the two tail stands at 0.05. The mean though are not so far apart and this contributes to the fact
that the two are statistically significant (da Silva & Borges, 2019).

ANALYSIS 20
ANOVA: Descriptive Statistics and Assumption Testing
Data Analysis: Hypothesis Testing
From the tabled results above, it is very clear and evident to see that there are some p-values that
are more or less than 0.05 and all that are what will be used in the assessment of and proof of the
tested hypotheses (Walijee et al. 2020).
Correlation: Hypothesis Testing
The correlational hypothesis testing, makes sure that we keep the null hypothesis that states that
there is at all no positive relationship between the two variables that were being correlated at all.
Simple Regression: Hypothesis Testing
The p-values and the f-value are all below 0.05 and this by far indicates the fact that there is
some reasonable fact that there will be a success if at all the wasted time in hours is reduced in
the long run.

ANALYSIS 21
Multiple Regression: Hypothesis Testing
From the mixed up values of significance as presented by the p –values for different variables,
we have some that are below the values of significance which is 0.05 and there are those that are
way higher than this value in all. This therefore is enough to make us state that there will only be
the need for there to be a holding on the fact that in as much there are enough ear protection
equipment that are being provided to workers there will definitely be an uphill task because of
the fact that workers shift from station of low noise to station of high noise and this makes this so
hard in provision of enough protective gears for them to shift accordingly (Dahunsi & Oluponna,
2019).
Independent Samples t Test: Hypothesis Testing
The two variables for the independent sample t test are all significant and this by far indicates
that there is an effectiveness of revised training over prior training.
Dependent Samples (Paired Samples) t Test: Hypothesis Testing
The significance on the variables that are used for this case indicates the fact that there is a
chance of the blood levels rising as per the stations of work.
ANOVA: Hypothesis Testing
P-value is less than 0.05 confirming a positive statement on the hypothesis stated here indicates
that there is a positive return on return on investments realized.
Findings
RO1: The particulate matter as per the human health, were found to be taking long and staying
for the longest when they are of larger particles and therefore there was the need for each and
every worker to be provided with the relevant breath protection gears. Those who in any way had
their blood still affected by the particles in one way or the other should be by all means be
covered medically.

ANALYSIS 22
RO2: It was found out that by reduction of wasted time for training would contribute to success
in training and the sole reason for this is due to the fact that there is a very big concentration
levels that there are usually there when there is more surface time that there is for concentration
on a project’s understanding.
RO3: The are no enough ear protection elements for protection against working between different
environments and this is the sole reason for the fact that there needs to be more provided to each
worker and for the reason of shifting environments.
RO4: There is effectiveness in training when it comes to revised training as opposed to prior
training and the reason is the fact that there will be more skills and more understanding of what
needs to be done in the long run and makes it easier on the handling of the subsequent classes.
RO5: Blood levels gone up because of the substances that are consumed.
RO6: There are more positive results on the return on investments and the reason is because of
the fact that there are up to two categories and these include the government as well as the
private sector and this therefore in the long run provides the company with the ability to offer
different price quotations to different people and therefore can mint highly for this (Jonathan,
2019).
Recommendations
The fact that there is more time that is lost during training may be because of the fact that
there are more hours that are handled by the trainers and for this fact, this implicates their ability
greatly and due to this fact there needs to be more trainers that are employed to help aid with the
shift between trainers and help reduce time that is taken by other trainers when taking rest (Wani
& Shiraz, 2020).

ANALYSIS 23
More revised training should be handled as what is repeated sticks more and ensures
more skills than what is done once and forgotten for that matter.

ANALYSIS 24
References
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2020). Modern
business statistics with Microsoft Excel. Cengage Learning.
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2020).
Essentials of modern business statistics with Microsoft Excel. Cengage Learning.
AYADI, F. D. (2019). TECHNICAL REPORT ON STUDENT INDUSTRIAL WORK
EXPERIENCE SCHEME (SIWES) (Doctoral dissertation, UNIVERSITY OF IBADAN,
IBADAN).
Bebic, D., Stazic, L., & Komar, I. (2019). SHIPS SHORE SERVICE OPTIMIZATION USING
THE QUEUEING THEORY. International Journal of Simulation Modelling (IJSIMM),
18(4).
Bielinis, E., Jaroszewska, A., Łukowski, A., & Takayama, N. (2020). The Effects of a Forest
Therapy Programme on Mental Hospital Patients with Affective and Psychotic Disorders.
International Journal of Environmental Research and Public Health, 17(1), 118.
Bynigeri, R. R., Mitnala, S., Talukdar, R., Singh, S. S., & Duvvuru, N. R. (2020). Pancreatic
stellate cell‐potentiated insulin secretion from Min6 cells is independent of interleukin 6‐
mediated pathway. Journal of cellular biochemistry.
Caras, V. (2019). Team Work and Strategic Skills Development through the Use of the General
Management 2 Business Simulation. In The International Scientific Conference
eLearning and Software for Education (Vol. 3, pp. 57-63). " Carol I" National Defence
University.
da Silva, R. S., & Borges, E. M. (2019). Quantitative Analysis Using a Flatbed Scanner: Aspirin
Quantification in Pharmaceutical Tablets. Journal of Chemical Education.
Dahunsi, F. M., & Oluponna, S. O. (2019). Analysis of Energy Usage Pattern of a Nigerian
University Digital Resource Center (DRC). FUTA JOURNAL OF ENGINEERING AND
ENGINEERING TECHNOLOGY, 13(2), 243-256.
Dawod, G. M., & Abdel-Aziz, T. M. (2020). Utilization of geographically weighted regression
for geoid modelling in Egypt. Journal of Applied Geodesy, 14(1), 1-12.
Do, V. P. T. (2019). Demand Forecasting For Bought-in Materials Using Time-Series Methods.
Fatima, Z., Shahzadi, U., & Shah, A. (2020). Financial Management Competence of Selected
and Promoted School Heads: A Demographic Comparison.
Fragala-Pinkham, M. A., Miller, P. E., M. Dumas, H., & Shore, B. J. (2020). Development and
Validation of Equations to Link Pediatric Evaluation of Disability Inventory (PEDI)

ANALYSIS 25
Functional Skills Scores to PEDI-Computer Adaptive Test Scores for Youth with
Cerebral Palsy. Physical & occupational therapy in pediatrics, 40(1), 106-120.
Guerrero, H. (2019). Analysis of Quantitative Data. In Excel Data Analysis (pp. 59-101).
Springer, Cham.
Hassan, A., Huang, D., Mustafa, E. K., Mahama, Y., Damos, M. A., Jiang, Z., & Zhang, L.
(2020). Statistical inference and residual analysis for the evaluation of datum
transformation models developed on 3D coordinate data. Journal of Applied Geodesy,
14(1), 65-75.
Ho, P. V. P., Phung, L. T. K., Oanh, T. T. T., & Giao, N. Q. (2020). Should Peer E-Comments
Replace Traditional Peer Comments. International Journal of Instruction, 13(1), 295-
314.
Iyengar, S. P., Acharya, H., & Kadam, M. (2020). Big Data Analytics in Healthcare Using
Spreadsheets. In Big Data Analytics in Healthcare (pp. 155-187). Springer, Cham.
Iyyanki, M., & Jayanthi, P. (2020). Machine Learning for Health Data Analytics: A Few Case
Studies of Application of Regression. In Challenges and Applications for Implementing
Machine Learning in Computer Vision (pp. 241-270). IGI Global.
Jonathan, E. O. (2019). Forecasting on Electrical Power Distribution Transformers. ATBU
Journal of Science, Technology and Education, 7(1), 286-294.
Kishi, M., Yamada, Y., Katayama, T., Matsuyama, T., & Toda, T. (2020). Carbon Mass Balance
in Arthrospira platensis Culture with Medium Recycle and High CO2 Supply. Applied
Sciences, 10(1), 228.
Karlsson, H. K., Sanku, M. G., & Svensson, H. (2020). Absorption of carbon dioxide in mixtures
of N-methyl-2-pyrrolidone and 2-amino-2-methyl-1-propanol. International Journal of
Greenhouse Gas Control, 95, 102952.
Kosmidou, I., Crowley, A., Macedo, L., Ben-Yehuda, O., Gersh, B. J., Boonstra, P. W., ... &
Stone, G. W. (2020). Usefulness of Discharge Resting Heart Rate to Predict Adverse
Cardiovascular Outcomes in Patients With Left Main Coronary Artery Disease
Revascularized With Percutaneous Coronary Intervention vs Coronary Artery Bypass
Grafting (from the EXCEL Trial). The American journal of cardiology, 125(2), 169-175.
Krolo, A., Gilic, B., Foretic, N., Pojskic, H., Hammami, R., Spasic, M., ... & Sekulic, D. (2020).
Agility Testing in Youth Football (Soccer) Players; Evaluating Reliability, Validity, and
Correlates of Newly Developed Testing Protocols. International Journal of
Environmental Research and Public Health, 17(1), 294.

ANALYSIS 26
Laugerman, M. R., & Saunders, K. P. (2019). Supporting Student Learning through Instructional
Videos in Business Statistics. Decision Sciences Journal of Innovative Education, 17(4),
387-404.
Li, Z. X., Wong, K. P. L., Wong, J. L. Y., Lim, K. B. L., & Mahadev, A. (2019). The utility of
mini C-arm in the fixation of unstable paediatric supracondylar humeral fractures. Injury,
50(11), 1992-1996.
Linnes, J. C., Hoilett, O. S., Twibell, A., Lee, H., Srivastava, R., Ummel, J., & Linsawy, R.
(2019). U.S. Patent Application No. 16/159,007.
Loshchenova, P. S., Sergeeva, S. V., Limonov, D. V., Guo, Z., & Dianov, G. L. (2020). Sp1-
independent downregulation of NHEJ in response to BER deficiency. DNA repair, 86,
102740.
Mega, A., Nilsen, M. H., Leiss, L. W., Tobin, N. P., Miletic, H., Sleire, L., ... & Enger, P. Ø.
(2020). Astrocytes enhance glioblastoma growth. Glia.
Olson, D. L., & Wu, D. (2020). Basic Forecasting Tools. In Predictive Data Mining Models (pp.
21-44). Springer, Singapore.
Pahriah, P., & Hendrawani, H. (2020). Efektivitas Modul Inkuiri Dengan Strategi Konflik
Kognitif Dalam Meningkatkan Keterampilan Berpikir Kritis Mahasiswa. Hydrogen:
Jurnal Kependidikan Kimia, 7(2), 62-72.
Pathakoti, K., Manubolu, M., & Hwang, H. M. (2020). Mechanistic Insights into TiO 2 and ZnO
Nanoparticle-Induced Metabolic Changes in Escherichia coli Under Solar Simulated
Light Irradiation. Water, Air, & Soil Pollution, 231(1), 1-9.
Sanchez, G. M. (2020). Indigenous stewardship of marine and estuarine fisheries?:
Reconstructing the ancient size of Pacific herring through linear regression models.
Journal of Archaeological Science: Reports, 29, 102061.
Savolainen, M. (2019). Adapting game content with a player typology.
Stowe, G. N., Paulsen, R. B., Hill, V. A., & Schaffer, M. I. (2019). A Retrospective Analysis of
Selected Opioids in Hair of Workplace Drug Testing Subjects. Journal of analytical
toxicology.
Sun, J., Ding, Y., Zhao, K., Xu, H., Zhang, Y., & Gao, B. (2020). Predicting Alzheimer's Disease
Based on Network Topological Latent Representations. Journal of Medical Imaging and
Health Informatics, 10(3), 667-671.
Tordön, R., Bladh, M., Svedin, C. G., & Sydsjö, G. (2020). Challenging intellectual, behavioral
and educational prerequisites for interventions aimed at school aged children in foster

ANALYSIS 27
care. A compilation of Swedish test results. Children and Youth Services Review, 108,
104598.
Walijee, H., Sood, S., Markey, A., Krishnan, M., Lee, A., & De, S. (2020). Is nurse-led
telephone follow-up for post-operative obstructive sleep apnoea patients effective? A
prospective observational study at a paediatric tertiary centre. International journal of
pediatric otorhinolaryngology, 129, 109766.
Wani, T. A., & Shiraz, M. (2020). Electricity Demand Forecasting Using Regression
Techniques. In Advances in Energy and Built Environment (pp. 111-121). Springer,
Singapore.
Yin, D., Wang, Y., Xiang, Y., Xu, Q., Xie, Q., Zhang, C., ... & Wang, D. (2020). Production and
migration of methylmercury in water-level-fluctuating zone of the Three Gorges
Reservoir, China: Dual roles of flooding-tolerant perennial herb. Journal of hazardous
materials, 381, 120962.
Young, I., Waddell, L. A., Wilhelm, B. J., & Greig, J. (2020). A systematic review and meta-
regression of single group, pre-post studies evaluating food safety education and training
interventions for food handlers. Food Research International, 128, 108711.