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Sun Coast Data Analysis

“Sun Coast Data Analysis”

“Descriptive Statistics and the assumption testing”

The “Sun Coast remediation was meant to determine whether the normal distribution of data” shown will be a need for assuming the parametric statistical tests. The research questions have assumptions that they do not comprise of the ratio data that could be categorized and have some sensible distances between the data values and the true zero.

A ratio measurement scale would be used to measure the data. Furthermore, the central tendency was carried out so that you can determine the way the data points have been disbursed around the midpoint of the histogram curves. The details include modes, median, and the mean for all the research questions. The assumptions for the normal distribution are met so that the parametric statistical procedures can be used.

“Correlation

Descriptive statistics and the assumption testing

The frequency distribution table”

“Sick days	Frequency
2	1
3	1
4	5
5	13
6	18
7	24
8	18
9	12
10	7
11	2
More	2”

The “histogram” for the correlation

“The descriptive statistics table”

“Mean annual sick days per employee
Mean	7.1
Standard error	0.19
Median	7
Mode	7
Standard deviation	1.9
Sample variance	3.6
Kurtosis	0.1
Skewness	0.1
Range	10
Minimum	2
Maximum	12
Sum	734
Count	103”

The measurement Scale.

To determine the data details is vital to understand the measurement level. The Sun Coast Remediation correlation data, which is associated with Research question 1, is about the particle matter size that affects the health of the employee, which is taken as the ratio scale data for measurement level.

The data that can be quantified ought to meet the characteristics of the ratio scale of measurement.

· Every value can be ordered and categorized, that is the frequency rates and the number of sick days.

· The frequency and the number of days can be ranked in an orderly manner, that 0 to 999

· In between the values (0-999), the units are equal.

· There exists the “true value of zero (that the sick days cannot be less than zero)”

“Central tendency measure

This refers to a method that would measure the data points in terms of the dispersion and the central location of the data points from the central location as asserted by (Ali & Sudheesh), 2019). The central tendency can be measured in three different ways, mode, median and mean. The means will be the calculation of the summation of all the data values and the total divided by the number of data values that are determining the central location”. The median is always calculated as the difference gotten between the maximum and the minimum values (Ali & Sudheesh, 2019). The mode refers to the determination of the data values that happen most frequently regardless of data points order. The research question comprises the data values used in calculating the central tendency measures that include the mode at 7, median at 7, and the mean at 7.1. The mode, the median, and the mean are all the “same for research question 1 and show almost a perfect distribution”.

“Evaluation”

The “statistical research needs the data assumption on whether the data is comparatively free from errors and accurate. The descriptive statistics brings about the confidence that the data is as expected in terms of the standard deviations and the means that there are data entries that have gone beyond the expected range (Garson, 2012). The data for research question 1 does have the normality assumption.

This decision is virtually based on the visual review of the descriptive statistics table evaluation and the histogram. The histogram has a bell curve which portrays a normal distribution. The descriptive statistics table would show that the mode, the median, and the mean suggest normal data distribution data. The standard deviation and the standard error lie within the central tendency which also shows the normal data distribution. For the sake of the Sun Coast Remediation, the parametric testing was met, and the data is suitable for advanced statistical testing”.

“Simple Regression

Descriptive statistics and the assumption testing

Frequency distribution table”

“Lost time hours	Frequency
10	1
35	1
60	9
85	9
110	17
135	18
160	24
185	27
210	37
235	24
260	21
285	15
310	12
335	4
More	4”

The simple regression “histogram”

The “descriptive statistics table”

“Lost time hours
Mean	188.00
Standard error	4.80
Median	190
Mode	190
Standard deviation	71.73
Sample variance	5144.54
Kurtosis	0.50
Skewness	0.082
Range	350
Minimum	10
Maximum	360
Sum	41925
Count	223”

“Scale measurement”

The “scale measurement for research question 2, which is the training expenditures vs the lost time hours is a ratio. The values of data have a sensible distance between the values, which 50 days, 30days, and 10 days, and the true zero existence because there is no employee who has fewer than zero-time hours”.

“Central tendency measures”

The “central tendency measure tries to identify the most typical score in the score’s distribution. The central tendency measure for research question 2 includes a mean of 188.00, the mode 190, and the mean 190. The values are nearly identical which portrays a perfect distribution”.

“The evaluation”

The descriptive statistics, the “histogram, and the frequency distribution table, Histogram, and Descriptive Statistics depict the information in the investigation of preparing uses and worker lost work hours. The information is significant for finishing up deciding the circulation and regularity of information. The Frequency Distribution Table shows the recurrence of worker lost work hours. The table demonstrates a typical conveyance of information around a focal number, and this information is outwardly shown as an unmistakable ringer bend on the Histogram. The mean, middle, and mode on the Descriptive Statistics Table are comparative numbers and the mean (188) is just two away from the middle and mode (190). For the motivations behind the Sun Coast Remediation, the parametric testing was met, and the information is appropriate for additional measurable testing”.

“Multiple regression

Descriptive statistics and the assumption testing

Frequency distribution table”

“Decibel	Frequency
103.35	1
104.37	2
105.36	1
106.35	3
107.34	6
108.33	6
109.32	9
110.31	12
111.30	18
112.29	17
113.28	26
114.27	22
115.26	27
116.25	47
118.24	36
119.23	44
120.22	47
121.20	53
122.19	61
123.17	60
124.16	62
125.15	74
126.14	70
127.13	81
128.12	93
129.11	73
130.10	105
131.09	80
132.08	88
133.07	67
134.06	50
135.05	56
136.04	35
137.03	30
138.02	19
139.01	7
140.00	8
140.01	5
More	2”

“The multiple regression histogram”

The “descriptive statistics table”

“Decibel
Mean	124.84
Standard error	0.18
Median	125.72
Mode	127.32
Standard deviation	6.90
Sample variance	47.59
Kurtosis	-0.31
Skewness	-0.42
Range	37.61
Minimum	103.38
Maximum	140.99
Sum	187628.42
Count	1503”

“Scale Measurement”

The “research question 3 data, which is about the prediction of the dBA levels at the work environments do use the ratio measurement scale. The data can be ordered, classified, and have meaningful differences between the values of data and has unique zero origins. The level of decibel would never go below zero”.

The “central tendency measures”

The “data central tendency can be used to describe data accurately. The even appropriation of information is demonstrated when the mean, middle, and mode are near one another in esteem. Examination Question 3 (foreseeing dBA levels at workplaces) have a comparable mean, middle, and modes – 124.83 (mean), 125.72 (middle), and 127.31 (mode) which means a nearby conveyance of information”.

“Evaluation”

The rundown measurements for “decibel levels at Sun Coast Remediation workplaces demonstrate a regularity of information. The histogram outwardly shows a chime bend with a tail focuses to one side of the mode. The mean and middle are not exactly the model demonstrating a negative slant. The information shows up ordinarily conveyed even with a negative slant. George and Mallery (2010) state skewness scores between - 2 and +2 are viewed as palatable outcomes to acknowledge ordinary conveyance. For the motivations behind the Sun Coast Remediation, the parametric testing was met, and the information is appropriate for additional factual testing”.

The “Independent samples T-test

Descriptive statistics and the assumption testing

Frequency Distribution Frequency table”

“

The “independent sample T-test”

“Group A Prior Training Scores
Mean	69.79
Standard error	1.40
Median	70
Mode	80
Standard deviation	11.04
Sample variance	122.00
Kurtosis	-0.78
Skewness	-0.09
Range	41
Minimum	50
Maximum	91
Sum	4327
Count	62”

“Group A Prior Training Scores
Mean	74.77
Standard error	0.66
Median	85
Mode	85
Standard deviation	5.19
Sample variance	26.96
Kurtosis	-0.35
Skewness	0.14
Range	22
Minimum	75
Maximum	97
Sum	5256
Count	62”

“Measurement scale”

The “data measured is for research question 4 which is about the comparison of the training program scores is considered the ratio measurement scale. The scores for both revised training and the prior training programs do not go below zero and thus meets the needs of the ratio measurement scale”.

“Central tendency measurement”

This shows the “normal distribution of data for every one of the instructional classes. Albeit the mean, middle, and mode are distinctive between the instructional classes, inside singular courses the scores are comparable demonstrating an almost awesome.”

“Evaluation”

The “descriptive statistics table for group A training scores has a tiny negative kurtosis and skewness but the median and the mean are almost the same which shows the data normalcy. The difference with the mode shows a large standard deviation because the data is loosely clustered around the mean. The Descriptive Statistics Table for Group B training scores is nearly a perfect bell curve with the mean at 84.77, median at 85, and mode at 85. For the purposes of the Sun Coast Remediation, the parametric testing was met, and the data is suitable for further statistical testing”.

References

Ali, Z., Bhaskar, S., & Sudheesh, K. (2019). Descriptive statistics: Measures of central tendency,

dispersion, correlation, and regression. Airway, 2(3), 120. Retrieved from https://link-gale-com.libraryresources.columbiasouthern.edu/apps/doc/A613183975/AONE?u=oran95108&sid=AONE&xid=62a3f963

George, D., & Mallery, P. (2010). SPSS for Windows step by step: A simple guide and

reference, 17.0 update (10th ed.). Boston, MA: Pearson.

Garson, G. (2012). Testing Statistical Assumptions. Statistical Associates Publishing. Asheboro,

NC. 2012 Edition. Retrieved from http://www.statisticalassociates.com/assumptions.pdf.

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