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DescriptiveStatisticsAnalysis3.docx

Running head: DESCRIPTIVE STATISTICS 1

DESCRIPTIVE STATISTICS 11

Descriptive Statistics

Student’s Name

University Name

Data Analysis: Descriptive Statistics and Assumption Testing

Descriptive statistics tool will quantitatively summarize or describe data in a sensible way. Sun Coast Remediation data description will involve use of univariate analysis that allow examination of a single variable at a time. Three major characteristics of observing a single variable are central tendency, distribution, and dispersion (Ali & Bhaskar, 2016). In terms of measures of central tendency, the median, mode or mean are used to describe data. In terms of distribution, the frequency of individual or ranges of value for variables is summarized. Data assumptions commonly used in statistical research include assumptions of normality where the distribution of the test assumes a normal distribution with a standard deviation of 1 and mean of zero. Kurtosis and Skewness can be used to test for normal distribution with Kurtosis values and Skewness value should be zero or near zero (Norman & Streiner, 2008). Independence of the data is also tested and the typical assumption is that data are independent.

Correlation: Descriptive Statistics and Assumption Testing

Frequency distribution table. Insert table here. Cut and paste from Excel.

Histogram. Insert histogram here. Cut and paste from Excel.

Descriptive statistics table.

microns

 

mean annual sick days per employee

 

Mean

5.618447

Mean

7.126214

Standard Error

0.260963

Standard Error

0.186484

Median

6

Median

7

Mode

8

Mode

7

Standard Deviation

2.648483

Standard Deviation

1.892605

Sample Variance

7.01446

Sample Variance

3.581953

Kurtosis

-0.84148

Kurtosis

0.124923

Skewness

-0.40085

Skewness

0.14225

Range

10

Range

10

Minimum

0

Minimum

2

Maximum

10

Maximum

12

Sum

578.7

Sum

734

Count

103

Count

103

Measurement scale.

The measurement scale used here is ratio scale since it has quantity and equality of units. It is worth noting that the scale has an absolute zero meaning no number exists below the zero (Pagano, 2012). The measure of microns and mean annual sick days per employee of different job sites have quantity, equal units and no number exists below zero. In short, negative mean or microns are impossible.

Measure of central tendency.

For the microns, the mean is 5.62, mode is 8 and median 6. This means that on average employees are exposed to 5.62 microns in their given job sites. They imply that the center of the data set lies between these measured of central tendency. For the mean annual sick days per employee, the median and mode have the same value 7 while the mean is 7.13. This implies that the center of the data set lies at 7 days sick days per employee each annually.

Evaluation.

There are measures of central tendency essential for descriptive statistics. The Skewness and kurtosis coefficient value ranges between -2 and +2 for correlation an indication that the data is normally distributed (Karataş, n.d). The Skewness and kurtosis value for microns is near zero. However, the values are negative indicating that they are skewed left. Similarly, the Skewness and kurtosis of the annual sick days per employee is near zero though skewed to the right. This implies that it is a normal distribution thus meeting the assumptions for parametric statistical testing.

Simple Regression: Descriptive Statistics and Assumption Testing

Frequency distribution table. Insert table here. Cut and paste from Excel.

Histogram. Insert histogram here. Cut and paste from Excel.

Descriptive statistics table.

contract #

 

safety training expenditure

 

lost time hours

 

Mean

358.278

Mean

595.9844

Mean

188.0045

Standard Error

39.4095

Standard Error

31.47701

Standard Error

4.803089

Median

145

Median

507.772

Median

190

Mode

205

Mode

234

Mode

190

Standard Deviation

588.5093

Standard Deviation

470.052

Standard Deviation

71.72542

Sample Variance

346343.2

Sample Variance

220948.8

Sample Variance

5144.536

Kurtosis

5.106205

Kurtosis

0.44408

Kurtosis

-0.50122

Skewness

2.456541

Skewness

0.951332

Skewness

-0.08198

Range

2799

Range

2251.404

Range

350

Minimum

2

Minimum

20.456

Minimum

10

Maximum

2801

Maximum

2271.86

Maximum

360

Sum

79896

Sum

132904.5

Sum

41925

Count

223

Count

223

Count

223

Measurement scale.

The contract number can be said to follow nominal scale. The contract are assigned numbers for identification purposes. The measurement scale used for expenditure and time is the ratio scale with properties of equal intervals, magnitude as well as absolute zero (Hanna & Dempster, 2012). It is impossible to spend less than zero amount on safety training or to record negative value of time.

Measure of central tendency.

On average, there are 358 contracts with a mode of 205 and median of 145. On average, the Sun Coast Company will incur 596 dollars on safety training with a mode of 234 and median of 507.8. On average, the lost time in hours due to safety training is 188 hours with a median and mode of 190.

Evaluation.

The presence of central tendency measures is essential in describing descriptive statistics. The Sun Coast Remediation should weigh on the average cost of training as well as the lost hours due to the training. The skewness and kurtosis coefficient of safety training expenditure and lost hours is near zero indicating normal distribution a key characteristic of parametric statistical testing (Norman & Streiner, 2008).

Multiple Regression: Descriptive Statistics and Assumption Testing

Frequency distribution table. Insert table here. Cut and paste from Excel.

Histogram. Insert histogram here. Cut and paste from Excel.

Descriptive statistics table.

contract #

 

Frequency (Hz)

 

Angle in Degrees

 

Chord Length

 

Velocity (Meters per Second)

 

Displacement

 

Decibel

 

Mean

341.0625

Mean

2886.381

Mean

6.782302

Mean

0.11614

Mean

50.86075

Mean

0.01114

Mean

124.8359

Standard Error

14.68412

Standard Error

81.31781

Standard Error

0.152653

Standard Error

0.001256

Standard Error

0.401686

Standard Error

0.000339

Standard Error

0.177945

Median

143

Median

1600

Median

5.4

Median

0.1176

Median

39.6

Median

0.004957

Median

125.721

Mode

157

Mode

2000

Mode

0

Mode

0.0917

Mode

39.6

Mode

0.005295

Mode

127.315

Standard Deviation

569.2818

Standard Deviation

3152.573

Standard Deviation

5.918128

Standard Deviation

0.048708

Standard Deviation

15.57278

Standard Deviation

0.01315

Standard Deviation

6.898657

Sample Variance

324081.7

Sample Variance

9938717

Sample Variance

35.02424

Sample Variance

0.002372

Sample Variance

242.5116

Sample Variance

0.000173

Sample Variance

47.59146

Kurtosis

5.448481

Kurtosis

5.708685

Kurtosis

-0.41295

Kurtosis

-1.1782

Kurtosis

-1.56395

Kurtosis

2.218903

Kurtosis

-0.31419

Skewness

2.539711

Skewness

2.137084

Skewness

0.689164

Skewness

-0.02754

Skewness

0.235852

Skewness

1.702165

Skewness

-0.41895

Range

2799

Range

19800

Range

22.2

Range

0.1697

Range

39.6

Range

0.058011

Range

37.607

Minimum

2

Minimum

200

Minimum

0

Minimum

0.03

Minimum

31.7

Minimum

0.000401

Minimum

103.38

Maximum

2801

Maximum

20000

Maximum

22.2

Maximum

0.1997

Maximum

71.3

Maximum

0.058411

Maximum

140.987

Sum

512617

Sum

4338230

Sum

10193.8

Sum

174.5585

Sum

76443.7

Sum

16.74324

Sum

187628.4

Count

1503

Count

1503

Count

1503

Count

1503

Count

1503

Count

1503

Count

1503

Measurement scale.

Frequency can be said to have interval scale with properties of equal intervals, magnitude and identity. The chord length follows a ratio scale with the magnitude, equal intervals and absolute zero properties (Hanna & Dempster, 2012). There cannot be a negative length value though there can be no length. In terms of angles in degrees, it follows a ratio scale with a true zero. Additionally, the values can be divided or multiplied.

Measure of central tendency.

The chord length has at least mean and median. In terms of chord length, the skewness and kurtosis coefficient are near zero and they are both negative values. The negative kurtosis means light tailed distribution while negative skewness indicates the data is skewed left.

Evaluation.

The presence of central tendency measures is essential in describing descriptive statistics. The Sun Coast Remediation should weigh on the average chord length of 0.12 of the different contracts. The skewness and kurtosis coefficient of the chord length indicate normal distribution a key characteristic of parametric statistical testing (Norman & Streiner, 2008).

Independent Samples t Test: Descriptive Statistics and Assumption Testing

Frequency distribution table. Insert table here. Cut and paste from Excel.

Histogram. Insert histogram here. Cut and paste from Excel.

Descriptive statistics table.

Group A Prior Training Scores

 

Group B Revised Training Scores

 

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

Measurement scale.

The training scores can be said to follow ratio scale as they have properties of absolute zero, magnitude as well as equal intervals. Not unless there was no training taking place, the training score cannot be less than zero or record a negative score.

Measure of central tendency.

The training scores both prior training for Group A and revised training for Group B have mean, mode and median. Revised training for Group B has the same mode and median.

Evaluation.

The presence of central tendency measures is essential in describing descriptive statistics. The Sun Coast Remediation should weigh on the average scores of the prior training for Group A and the revised training for Group B in order to determine whether it is necessary to conduct the revised training or just the training. The skewness and kurtosis coefficient of the training scores indicate normal distribution a key characteristic of parametric statistical testing (Norman & Streiner, 2008). However, Group A training is skewed left while Group B training is skewed right.

Dependent Samples (Paired-Samples) t Test: Descriptive Statistics and Assumption Testing

Frequency distribution table. Insert table here. Cut and paste from Excel.

Histogram. Insert histogram here. Cut and paste from Excel.

Descriptive statistics table.

Pre-Exposure μg/dL

 

Post-Exposure μg/dL

 

Mean

32.85714

Mean

33.28571

Standard Error

1.752307

Standard Error

1.781423

Median

35

Median

36

Mode

36

Mode

38

Standard Deviation

12.26615

Standard Deviation

12.46996

Sample Variance

150.4583

Sample Variance

155.5

Kurtosis

-0.57604

Kurtosis

-0.65421

Skewness

-0.42511

Skewness

-0.48363

Range

50

Range

50

Minimum

6

Minimum

6

Maximum

56

Maximum

56

Sum

1610

Sum

1631

Count

49

Count

49

Measurement scale.

The pre-exposure and post-exposure can be said to follow ratio scale as they have properties of absolute zero, magnitude as well as equal intervals. They both record the same microgram per liter exposure of employees before exposure and after exposure.

Measure of central tendency.

The pre-exposure and post-exposure have the same mean, mode and median because there is no change in level of exposure among employees before and after exposure.

Evaluation.

The presence of central tendency measures is essential in describing descriptive statistics. The Sun Coast Remediation should weigh on the average scores of the exposure level before and after employees are exposed in their work environments. The skewness and kurtosis coefficient of the exposure levels indicate normal distribution a key characteristic of parametric statistical testing (Norman & Streiner, 2008). Additionally, the data is skewed left with a light tailed distribution.

ANOVA: Descriptive Statistics and Assumption Testing

Frequency distribution table. Insert table here. Cut and paste from Excel.

Histogram. Insert histogram here. Cut and paste from Excel.

Descriptive statistics table.

A = Air

 

B = Soil

 

C = Water

 

D = Training

 

Mean

8.9

Mean

9.1

Mean

7

Mean

5.4

Standard Error

0.684028

Standard Error

0.390007

Standard Error

0.575829

Standard Error

0.265568

Median

9

Median

9

Median

6

Median

5

Mode

11

Mode

8

Mode

6

Mode

5

Standard Deviation

3.059068

Standard Deviation

1.744163

Standard Deviation

2.575185

Standard Deviation

1.187656

Sample Variance

9.357895

Sample Variance

3.042105

Sample Variance

6.631579

Sample Variance

1.410526

Kurtosis

-0.6283

Kurtosis

0.11923

Kurtosis

-0.23752

Kurtosis

0.253747

Skewness

-0.36085

Skewness

0.492002

Skewness

0.760206

Skewness

0.159183

Range

11

Range

7

Range

9

Range

5

Minimum

3

Minimum

6

Minimum

3

Minimum

3

Maximum

14

Maximum

13

Maximum

12

Maximum

8

Sum

178

Sum

182

Sum

140

Sum

108

Count

20

Count

20

Count

20

Count

20

Measurement scale.

The project return on investment in air, training, water and soil can be said to follow ratio scale as they have properties of absolute zero, magnitude as well as equal intervals. They record positive values of percentage on each variable.

Measure of central tendency.

The variables have mean, mode and median. The mean, for instance, illustrates the average percentage of project return on investment of each variable.

Evaluation.

The presence of central tendency measures is essential in describing descriptive statistics. The Sun Coast Remediation should weigh on the average percentage of project return on each variable in order to determine the variables that will reap the most returns to invest in them. The skewness and kurtosis coefficient of the project return on investment indicate normal distribution a key characteristic of parametric statistical testing (Norman & Streiner, 2008).

References Ali, Z., & Bhaskar, S. S. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anaesthesia, 60(10): 790. Hanna, H., & Dempster, B. (2012). Psychology Statistics For Dummies. John Wiley & Sons. Karataş, M. (n.d). Strategic Researches II: From Local to Global: Working Life And Social Policy. Ijopec Publication. Norman, G. R., & Streiner, D. L. (2008). Biostatistics: The Bare Essentials. PMPH USA. Pagano, R. R. (2012). Understanding Statistics in the Behavioral Sciences. Cengage Learning.