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Contents

TOC \o "1-3" \h \z \u Descriptive Data and Assumptions: Correlation PAGEREF _Toc20661579 \h 3

Frequency Distribution Table PAGEREF _Toc20661580 \h 3

Histogram PAGEREF _Toc20661581 \h 3

Descriptive Statistics Table PAGEREF _Toc20661582 \h 3

Kolmogorov-Smirnov Test PAGEREF _Toc20661583 \h 4

Measurement Scale PAGEREF _Toc20661584 \h 4

Measure of Central Tendency PAGEREF _Toc20661585 \h 4

Evaluation PAGEREF _Toc20661586 \h 4

Descriptive Data and Assumptions: Simple Regression PAGEREF _Toc20661587 \h 5

Frequency Distribution Table PAGEREF _Toc20661588 \h 5

Histogram PAGEREF _Toc20661589 \h 5

Descriptive Statistics Table PAGEREF _Toc20661590 \h 6

Kolmogorov-Smirnov Test PAGEREF _Toc20661591 \h 6

Measurement Scale PAGEREF _Toc20661592 \h 6

Measure of Central Tendency PAGEREF _Toc20661593 \h 6

Evaluation PAGEREF _Toc20661594 \h 6

Descriptive Data and Assumptions: Multiple Regression PAGEREF _Toc20661595 \h 7

Frequency Distribution Table PAGEREF _Toc20661596 \h 7

Histogram PAGEREF _Toc20661597 \h 7

Descriptive Statistics Table PAGEREF _Toc20661598 \h 8

Kolmogorov-Smirnov Test PAGEREF _Toc20661599 \h 8

Measurement Scale PAGEREF _Toc20661600 \h 8

Measure of Central Tendency PAGEREF _Toc20661601 \h 8

Evaluation PAGEREF _Toc20661602 \h 8

Descriptive Data and Assumptions: Independent Samples t Test PAGEREF _Toc20661603 \h 9

Frequency Distribution Table PAGEREF _Toc20661604 \h 9

Histogram PAGEREF _Toc20661605 \h 9

Descriptive Statistics Table PAGEREF _Toc20661606 \h 10

Kolmogorov-Smirnov Test PAGEREF _Toc20661607 \h 10

Measurement Scale PAGEREF _Toc20661608 \h 10

Measure of Central Tendency PAGEREF _Toc20661609 \h 10

Evaluation PAGEREF _Toc20661610 \h 10

Descriptive Data and Assumptions: Dependent Samples t Test PAGEREF _Toc20661611 \h 11

Frequency Distribution Table PAGEREF _Toc20661612 \h 11

Histogram PAGEREF _Toc20661613 \h 11

Descriptive Statistics Table PAGEREF _Toc20661614 \h 12

Kolmogorov-Smirnov Test PAGEREF _Toc20661615 \h 12

Measurement Scale PAGEREF _Toc20661616 \h 12

Measure of Central Tendency PAGEREF _Toc20661617 \h 12

Evaluation PAGEREF _Toc20661618 \h 13

Descriptive Data and Assumptions: ANOVA PAGEREF _Toc20661619 \h 13

Frequency Distribution Table PAGEREF _Toc20661620 \h 13

Histogram PAGEREF _Toc20661621 \h 13

Descriptive Statistics Table PAGEREF _Toc20661622 \h 14

Kolmogorov-Smirnov Test PAGEREF _Toc20661623 \h 15

Measurement Scale PAGEREF _Toc20661624 \h 15

Measure of Central Tendency PAGEREF _Toc20661625 \h 15

Evaluation PAGEREF _Toc20661626 \h 15

References PAGEREF _Toc20661627 \h 16

Descriptive Data and Assumptions: Correlation

Frequency Distribution Table

PM size

Frequency

0-1

8

2-4

24

5-7

37

8-10

34

Sick Days

Frequency

0-2

1

4-7

61

8-9

30

10-12

11

365371926726500Histogram

Descriptive Statistics Table

Microns

Sick day

Mean

5.65728155

Mean

7.126214

Standard Error

0.25560014

Standard Error

0.186484

Median

6

Median

7

Mode

8

Mode

7

Standard Deviation

2.59405814

Standard Deviation

1.892605

Sample Variance

6.72913764

Sample Variance

3.581953

Kurtosis

-0.8521619

Kurtosis

0.124923

Skewness

-0.37325713

Skewness

0.14225

Range

9.8

Range

10

Minimum

0.2

Minimum

2

Maximum

10

Maximum

12

Sum

582.7

Sum

734

Count

103

Count

103

Largest(1)

10

Largest(1)

12

Smallest(1)

0.2

Smallest(1)

2

Confidence Level(95.0%)

0.50698167

Confidence Level(95.0%)

0.36989

Kolmogorov-Smirnov Test

H01: There is no statistically significant relationship between particulate matter size, and employee annual sick days.

HA1: There is a statistically significant relationship between particulate matter size, and employee annual sick days.

Measurement Scale

Ordinal

Measure of Central Tendency

Mean

Evaluation

An alpha of 0.05 is an indication that the p-values are <0.05 alpha; thus, the null hypothesis (H01) is rejected, and the (HA1) hypothesis is accepted that there is a statistically significant relationship between particulate matter size, and employee annual sick days. This correlation analysis shows that the authors are comfortable with making a Type I error (Creswell & Creswell, 2018). They indicate the p-value 1.89059E-17 (1.89059*10-17) < 0.05.

The size of the particulate matter is strongly correlated with and negatively related to the number of annual employees' sick days according to Pearson's correlation coefficient, with r = 0.715 and R2 = 51. This illustrates that the variability in employee sick days is 51%, which will be explained by the size of the particulate matter.

Descriptive Data and Assumptions: Simple Regression

Frequency Distribution Table

Expenditure

Frequency

20-500

108

501-1000

76

1001-1500

27

1501-2000

11

2001-2500

1

Time

Frequency

0-50

6

51-100

26

101-200

98

201-300

85

301-400

8

Histogram

Descriptive Statistics Table

safety training expenditure

lost time hours

Mean

595.9843812

Mean

188.0045

Standard Error

31.4770075

Standard Error

4.803089

Median

507.772

Median

190

Mode

234

Mode

190

Standard Deviation

470.0519613

Standard Deviation

71.72542

Sample Variance

220948.8463

Sample Variance

5144.536

Kurtosis

0.444080195

Kurtosis

-0.50122

Skewness

0.951331922

Skewness

-0.08198

Range

2251.404

Range

350

Minimum

20.456

Minimum

10

Maximum

2271.86

Maximum

360

Sum

132904.517

Sum

41925

Count

223

Count

223

Largest(1)

2271.86

Largest(1)

360

Smallest(1)

20.456

Smallest(1)

10

Confidence Level(95.0%)

62.03197147

Confidence Level(95.0%)

9.465484

Kolmogorov-Smirnov Test

H02: There is no statistically significant relationship between safety training programs, expenditure, and lost-time hours.

HA2: There is a statistically significant relationship between safety training programs, expenditure, and lost-time hours.

Measurement Scale

Nominal

Measure of Central Tendency

Median

Evaluation

When observing the above data, the simple regression analysis uses an alpha 0.05. It also states a p-value of 7.7E-105 (7.6586* 10-105) < 0.05. The null hypothesis (H02) is rejected, and the alternative hypothesis (HA2) is accepted; there is a statistically significant relationship between safety training programs, expenditure, and lost hours.

The correlation coefficient is r = 0.94, and a very strong negative relationship was found between safety training programs, expenditure, and a decrease in lost hours. This correlates to an R2 of 0.884, which explains the 88.4 percent of the variance between safety training programs, expenditure, and reducing lost hours.

The lost time hours equations are performed by a linear formula: Y = m + bX, which is equivalent to coefficients 1753.60 + (-6.158) (safety training programs, expenditure, and reducing lost hours).

Descriptive Data and Assumptions: Multiple Regression

Frequency Distribution Table

Decibel

Frequency

100-106

4

107-111

51

112-116

126

117-121

249

122-131

786

132-141

287

Histogram

Descriptive Statistics Table

Decibel

Mean

124.8359

Standard Error

0.177945

Median

125.721

Mode

127.315

Standard Deviation

6.898657

Sample Variance

47.59146

Kurtosis

-0.31419

Skewness

-0.41895

Range

37.607

Minimum

103.38

Maximum

140.987

Sum

187628.4

Count

1503

Kolmogorov-Smirnov Test

H03: There is no statistically significant relationship between the primary variable (frequency, angle in degrees, cord length, velocity, and displacement), and decibel level.

HA3: There is a statistically significant relationship between the primary variable (frequency, angle in degrees, cord length, velocity, and displacement), and the decibel level.

Measurement Scale

Internal

Measure of Central Tendency

Mean

Evaluation

The multiple regression analysis uses an alpha of 0.05; the results of the Frequency (Hz), Velocity (as measured meters per second), and displacement show the p-value of 4.10E-104 (4.10*10-104), 1.02E-18 (1.02*10-18), and 5.21E-45 (5.21*10-45) respectively. These have listed p-values < 0.05 alpha. The null hypothesis (H03) is rejected, and (HA3) is accepted, i.e., there is a statistically significant relationship between the primary variable (frequency, angle in degrees, cord length, velocity, and displacement), and decibel level.

The results of the multiple regression state that the angle in degrees and chord shows the p-values of 0.205 and 0.061, respectively. These p-values > 0.05. The null hypothesis (H03) is accepted, and the (HA3) is rejected, i.e., there is no statistically significant relationship between the primary variable (frequency, angle, cord, velocity, and displacement), and level of dB not increasing after the employees are placed on the site for future use.

The correlation coefficient of r = 0.31 states a positive correlation among the other groups. This equates to an R2 of 0.9 and states that 9 percent of the variability in decibel levels is explained by the above-listed groups.

Decibel level equations are performed by a linear formula:

Y= a + b1 X1 + b2 X2 + b3 X3 +…+ bn Xn

Decibel level = 126.82+ (-0.0011) (Frequency) +(.0.47) (Angle in Degrees) +(-5.49) (Cord Length) +(0.083) (Velocity) + (-240.51) (Displacement)

Descriptive Data and Assumptions: Independent Samples t Test

Frequency Distribution Table

Training

Frequency

49-60

12

61-70

20

71-80

21

81-90

8

91-100

1

Training

Frequency

74-80

14

81-85

21

86-90

19

91-95

6

96-100

2

Histogram

Descriptive Statistics Table

Prior Training

Revised Training

Mean

69.79032

Mean

84.77419

Standard Error

1.402788

Standard Error

0.659479

Median

70

Median

85

Mode

80

Mode

85

Standard Deviation

11.04556

Standard Deviation

5.192742

Sample Variance

122.0045

Sample Variance

26.96457

Kurtosis

-0.77668

Kurtosis

-0.35254

Skewness

-0.0868

Skewness

0.144085

Range

41

Range

22

Minimum

50

Minimum

75

Maximum

91

Maximum

97

Sum

4327

Sum

5256

Count

62

Count

62

Largest(1)

91

Largest(1)

97

Smallest(1)

50

Smallest(1)

75

Confidence Level(95.0%)

2.805048

Confidence Level(95.0%)

1.31871

Kolmogorov-Smirnov Test

H04: There is no statistically significant difference in means scores between the prior and revised training programs.

HA4: There is a statistically significant difference in means scores between the prior and revised training programs.

Measurement Scale

Internal

Measure of Central Tendency

Mean

Evaluation

The results indicate that Group A (variable) has a lower mean. With the help of the alpha of 0.05, the p-values of t Stat is 1.94E-15 (1.93993* 10-15) < 0.05. It shows that alternative hypotheses (H04) will be rejected, while the null hypothesis (HA4) will be accepted as it assumed a statistically significant difference in mean scores between the prior and revised training programs.

The mean scores of the Group B (variable) revised training had significantly improved. The mean score of Group A [(variable) prior training] was 69.7903, and Group B (revised training) was 84.7742. Therefore, the mean difference is not zero.

Descriptive Data and Assumptions: Dependent Samples t Test

Frequency Distribution Table

Exposure

Frequency

5-15

5

16-25

8

26-35

12

36-45

16

46-56

8

Exposure

Frequency

5-15

5

16-25

8

26-35

11

36-45

17

46-56

8

Histogram

Descriptive Statistics Table

Pre-Exposure μg/dL

Post-Exposure μg/dL

Mean

32.8571429

Mean

33.28571

Standard Error

1.75230655

Standard Error

1.781423

Median

35

Median

36

Mode

36

Mode

38

Standard Deviation

12.2661458

Standard Deviation

12.46996

Sample Variance

150.458333

Sample Variance

155.5

Kurtosis

-0.57603713

Kurtosis

-0.65421

Skewness

-0.42510965

Skewness

-0.48363

Range

50

Range

50

Minimum

6

Minimum

6

Maximum

56

Maximum

56

Sum

1610

Sum

1631

Count

49

Count

49

Largest(1)

56

Largest(1)

56

Smallest(1)

6

Smallest(1)

6

Confidence Level(95.0%)

3.52324845

Confidence Level(95.0%)

3.581792

Kolmogorov-Smirnov Test

H05: There is no statistically significant relationship differences between the blood lead level of the employees and pre and post-exposure to an unhealthy workplace condition.

HA5: There is a statistically significant relationship differences between the blood lead level of the employees and pre and post-exposure to an unhealthy workplace condition.

Measurement Scale

Interval

Measure of Central Tendency

Mean

Evaluation

By using an alpha of 0.05, the p-value of the t Stat is 0.0596>0.05 of alpha. The alternative hypothesis (H05) will be highly accepted and no statistically significant difference, while the null hypothesis (HA5) is rejected. In this case, it means that the pre-exposure and post-exposure were the same. As long as the instances regarding lead blood levels are contained and results proven via post-exposure results, it is clear that the mean has increased slightly (pre-exposure = 32.8571, while post-exposure =33.2857).

Descriptive Data and Assumptions: ANOVA

Frequency Distribution Table

Air

Frequency

1-3

1

4-6

4

7-9

6

10-12

7

12-15

2

Soil

Frequency

5-7

3

8-10

13

10-13

4

Water

Frequency

1-3

1

4-6

10

7-9

5

10-12

4

Training

Frequency

1-3

1

4-6

16

7-9

3

Histogram

Descriptive Statistics Table

A = Air

B = Soil

Mean

8.9

Mean

9.1

Standard Error

0.684028

Standard Error

0.390007

Median

9

Median

9

Mode

11

Mode

8

Standard Deviation

3.059068

Standard Deviation

1.744163

Sample Variance

9.357895

Sample Variance

3.042105

Kurtosis

-0.6283

Kurtosis

0.11923

Skewness

-0.36085

Skewness

0.492002

Range

11

Range

7

Minimum

3

Minimum

6

Maximum

14

Maximum

13

Sum

178

Sum

182

Count

20

Count

20

Largest(1)

14

Largest(1)

13

Smallest(1)

3

Smallest(1)

6

Confidence Level(95.0%)

1.431688

Confidence Level(95.0%)

0.816294

C = Water

D = Training

Mean

7

Mean

5.4

Standard Error

0.575829

Standard Error

0.265568

Median

6

Median

5

Mode

6

Mode

5

Standard Deviation

2.575185

Standard Deviation

1.187656

Sample Variance

6.631579

Sample Variance

1.410526

Kurtosis

-0.23752

Kurtosis

0.253747

Skewness

0.760206

Skewness

0.159183

Range

9

Range

5

Minimum

3

Minimum

3

Maximum

12

Maximum

8

Sum

140

Sum

108

Count

20

Count

20

Largest(1)

12

Largest(1)

8

Smallest(1)

3

Smallest(1)

3

Confidence Level(95.0%)

1.205224

Confidence Level(95.0%)

0.55584

Kolmogorov-Smirnov Test

H06: There are no statistically significant differences relationship between return on investment and air, soil, water, and safety training.

HA6: There is a statistically significant difference in return on investment between air, soil, water, and safety training.

Measurement Scale

Ratio

Measure of Central Tendency

Mean

Evaluation

According to the results demonstrated above, while using an alpha of 0.05, the p-value of the ANOVA analysis is 1.76E-06 < 0.05. Evidently, F = 11.9232, while F crit = 2.724944. Therefore, F > F crit. This outcome debunks the null hypothesis. (H06) is rejected, and (HA6) is accepted. There are significant differences, and this confirms that they are not equal regarding the return of their investments among the four groups.

References

BIBLIOGRAPHY Assaad, H. I. (2014). Rapid publication-ready MS-Word tables for one-way ANOVA. SpringerPlus.

Creswell, J. W. (2018). Research design: Qualitative, quantitative, and mixed methods approaches. Thousand Oaks, CA: Sage.

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