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Green Training Impacts on Healthcare Jobs and Environment Assignment Sample

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Analyzing the Effects of Green Training Sample Content on Healthcare Job Roles Assignment Sample

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Surveys are done to assimilate changes in the organization where the authorities are explaining more about the product upgrades. The main aim of the report is to provide examples of the application of data analysis and to present real material to show the efficiency of the results to the users of this report. Companies' employees are basically examined in this report about what they feel or whether they are satisfied or not with their work. Minjee Lee the Chief Analyst of the company has been given a responsibility by the CEO (Margot Robbie) to obtain an overview of all facets of the company’s employees. In this report, the given data sheets are examined and analysed to get accurate answers to the stated questions.

2.2 Memorandum

Date: 25th August 2022

To: Minjee Lee, Chief Analyst

From: Margot Robbie, CEO

Subject: Analysis of Employee Survey Data

Dear Minjee,

1. Summarisation of key variables of interest

  1. a) income that is distributed to the employees as a reward for their job roles is estimated at around 59.1105 as a means value. As stated by Dili-Ruiz et al. (2018), there are varieties of degrees that are estimated to the income levels where the people are estimating more nominal view to integrating more viable income to initiate more insight to provide job facilities. There are a total of 400 sample sizes from where the company has distributed their whole financial retrains to their employees. Casper the calculation it can be stated that the standard error is estimated at 1.41 (Nelson et al. 2018). The seems if the employees are getting enough salary to spend their needs, then job satisfaction will be increased to a great extent.
  2. b) job satisfaction can be referred to as the employees getting more viable returns to get the overall explanations that can be redeemed. Job satisfaction enables the accurate changes that are deprived in managing the overall siuasituationsdge et al. 2020). If the salaries are high then job satisfaction can be reflected in a good way. Employees work in a systematic way to get exact returns and the company thinks the same font.

2. Exploring relationships between two variables

  1. a) Two variables are being used to determine sample sizing activities that have determined that job satisfaction and income have originated through positive relationships. Furthermore, productivity in job satisfaction and income has explored positive relationships, which has established a positive mean value of 59.1105. Additionally, the standard deviation is 28.21146232 which explored positive relations between two variables (Kasalak and Dagyar 2020).
  2. b) Based on the positive value of standard deviation 795.8866063 has provided a positive correlation. In this relative exposure to present productivity in job satisfaction (Pinzone et al. 2019). Additionally, productivity and job satisfaction has been organized by descriptive statistics that explored a maximum value of 689, which has explored job satisfaction that has been provided to employees.
  3. c) Based on statistical analysis explored female employees' maximum income is less than male candidates proof less job satisfaction has been identified in female candidates (Liu et al. 2019). Hence, Kurtosis -1.58107 is the primary explored job satisfaction that has been identified in organizational productivity. Additionally, the confidence level of income has presented 2.773084, which has explored productivity in job satisfaction.

3. Estimating employee measures

  1. a) future budgets are made to show the 40 weeks' work duration in the office to state the job satisfaction to redeem the company policy. The working hours that are identified from calculations are 0.987439.
  2. b) Company culture and productivity impact on employee’s performance that has been presented that there are more viable changes. estimated proportions are belongs to the employees who are required to decrease the working hours which were obtained above.

4. Employee claims

  1. a) as per the business report it is claimed that more than a salary of 62,000 is being given to inverse the morality of the company. employees can be stated as an integral part of the company where they need to advise more of their potential to get more viable returns. Therefore, in case of an increase in salary, the whole mean value will be changed (Lu et al. 2019). This shows that the company will get more loss by comparing each genre in order to facilitate more viable norms. This increasing loss can be retrieved to a great extent.
  2. b) the calculations that are done to showcase the job satisfaction part need to be redeemed by glancing more thoughts to get more returns. It is claimed that less than 40% of employees enjoy their work but from the calculation, it can be stated that 75% of the employees get great satisfaction from their job attributes (Meng and Berger 2019). It is also stated that the company needs to retrieve its policies to get more competencies.

5. Choosing of appropriate sample size

  1. a) A sample size of 400 participants has delivered personal information and job satisfaction-related information that prescribe productivity of the organization and member union that helps to present each question data analysis for presenting statistical analysis. Based on CI mean, the population standard division is 0.029190198, which has explored collective information of data has authenticity and less volatile that presenting an appropriate analysis of the whole data set (Paais and Pattiruhu 2020).
  2. b) Moreover, the Z value of 1.644853627 is presenting job satisfaction depending on other variables, not only on income. Sampling errors have explored the value of -0.480042202, which helps to present limited eros are find out in this data set. Moreover, the interval upper and lower limit has explored 1.959963985 and 0.075557375 which present variance of the two variables is limited.

Conclusion

Based on the above context it can be stated that the job performance and satisfaction level of the employees are determined by using descriptive statistics. The above-mentioned calculations have shown drastic changes that are acquired to get the exact variables that needed to be assimilated to gain more competence. The confidence level that has been stated in this format is retrieved from the population size, income level and job satisfaction. This is also stated that there are many other influences that can be retrieved from the hypothetical analysis where they are differentiated in managing the changes in the company aspects. An analyst is inverted by the stated values that are ascertained in the values. Job characteristics have been renamed by assimilation where the job requirements are more and the strategies to output of more retrieval policies.

Data Analysis (Part B)

Q1(a)

Income

Mean

59.1105

Standard Error

1.410573116

Median

52.4

Mode

45

Standard Deviation

28.21146232

Sample Variance

795.8866063

Kurtosis

1.718329189

Skewness

1.213267748

Range

163.6

Minimum

20.2

Maximum

183.8

Sum

23644.2

Count

400

Confidence Level(95.0%)

2.773084192

z-Test: Two Sample for Means

Gender

Job Satisfaction

Mean

1.495

1.725

Known Variance

1

3

Observations

400

400

Hypothesized Mean Difference

2

z

-22.3

P(Z<=z) one-tail

0

z Critical one-tail

1.644853627

P(Z<=z) two-tail

0

z Critical two-tail

1.959963985

Q1(b)

Job Satisfaction

Mean

1.726817

Standard Error

0.038487

Median

2

Mode

2

Standard Deviation

0.768774

Sample Variance

0.591013

Kurtosis

1.164089

Skewness

1.077723

Range

3

Minimum

1

Maximum

4

Sum

689

Count

399

Confidence Level (95.0%)

0.075663

Q2(a)

Income

Stay Org

Mean

59.1105

Mean

2.7425

Standard Error

1.410573

Standard Error

0.058622

Median

52.4

Median

2

Mode

45

Mode

4

Standard Deviation

28.21146

Standard Deviation

1.172446

Sample Variance

795.8866

Sample Variance

1.37463

Kurtosis

1.718329

Kurtosis

-1.58107

Skewness

1.213268

Skewness

-0.09764

Range

163.6

Range

3

Minimum

20.2

Minimum

1

Maximum

183.8

Maximum

4

Sum

23644.2

Sum

1097

Count

400

Count

400

Confidence Level(95.0%)

2.773084

Confidence Level (95.0%)

0.115247

Q2(b)

Gender

Member Union

Mean

1.495

Mean

1.8275

Standard Error

0.02919

Standard Error

0.018914

Median

1

Median

2

Mode

1

Mode

2

Standard Deviation

0.583804

Standard Deviation

0.378288

Sample Variance

0.340827

Sample Variance

0.143102

Kurtosis

-0.48004

Kurtosis

1.033396

Skewness

0.703085

Skewness

-1.74019

Range

2

Range

1

Minimum

1

Minimum

1

Maximum

3

Maximum

2

Sum

598

Sum

731

Count

400

Count

400

Confidence Level (95.0%)

0.057386

Confidence Level (95.0%)

0.037184

Q2(c)

Age

Man Employee Rel

Mean

39.41

Mean

2.3475

Standard Error

0.53055

Standard Error

0.052786

Median

38

Median

2

Mode

33

Mode

3

Standard Deviation

10.611

Standard Deviation

1.055713

Sample Variance

112.5934

Sample Variance

1.11453

Kurtosis

-0.36256

Kurtosis

-0.13838

Skewness

0.476206

Skewness

0.45088

Range

51

Range

4

Minimum

18

Minimum

1

Maximum

69

Maximum

5

Sum

15764

Sum

939

Count

400

Count

400

Confidence Level (95.0%)

1.043023

Confidence Level (95.0%)

0.103773

Q3(a)

Work hours

Mean

45.4325

Mean

#DIV/0!

Standard Error

0.502277

Standard Error

65535

Median

40

Median

#NUM!

Mode

40

Mode

#N/A

Standard Deviation

10.04553

Standard Deviation

#DIV/0!

Sample Variance

100.9127

Sample Variance

#DIV/0!

Kurtosis

2.820596

Kurtosis

#DIV/0!

Skewness

1.543923

Skewness

#DIV/0!

Range

61

Range

0

Minimum

28

Minimum

0

Maximum

89

Maximum

0

Sum

18173

Sum

0

Count

400

Count

0

Confidence Level (95.0%)

0.987439

Confidence Level (95.0%)

#NUM!

Q3(b)

ProudOrg

Mean

1.5525

Standard Error

0.043851

Median

1

Mode

1

Standard Deviation

0.877021

Sample Variance

0.769167

Kurtosis

2.185803

Skewness

1.720832

Range

3

Minimum

1

Maximum

4

Sum

621

Count

400

Confidence Level(95.0%)

0.086208

Q4(a)

1Hrs

Income

Mean

45.4325

Mean

59.1105

Standard Error

0.502277

Standard Error

1.410573

Median

40

Median

52.4

Mode

40

Mode

45

Standard Deviation

10.04553

Standard Deviation

28.21146

Sample Variance

100.9127

Sample Variance

795.8866

Kurtosis

2.820596

Kurtosis

1.718329

Skewness

1.543923

Skewness

1.213268

Range

61

Range

163.6

Minimum

28

Minimum

20.2

Maximum

89

Maximum

183.8

Sum

18173

Sum

23644.2

Count

400

Count

400

Confidence Level (95.0%)

0.987439

Confidence Level (95.0%)

2.773084

Q4(b)

Job Characteristics

Mean

3.325

Standard Error

0.054827

Median

4

Mode

4

Standard Deviation

1.096531

Sample Variance

1.202381

Kurtosis

0.111642

Skewness

-0.981

Range

4

Minimum

1

Maximum

5

Sum

1330

Count

400

Confidence Level (95.0%)

0.107785

Q5

Income

Job Satisfaction

Mean

59.1105

Mean

1.725

Standard Error

1.410573

Standard Error

0.038433

Median

52.4

Median

2

Mode

45

Mode

2

Standard Deviation

28.21146

Standard Deviation

0.768669

Sample Variance

795.8866

Sample Variance

0.590852

Kurtosis

1.718329

Kurtosis

1.168085

Skewness

1.213268

Skewness

1.080445

Range

163.6

Range

3

Minimum

20.2

Minimum

1

Maximum

183.8

Maximum

4

Sum

23644.2

Sum

690

Count

400

Count

400

Confidence Level(95.0%)

2.773084

Confidence Level (95.0%)

0.075557

CIMean

Confidence Interval for mean (m)

Data

Population Standard Deviation (s)

0.02919

Sample Mean ( )

200

Sample Size (n)

400

Confidence Level

95%

SE

Intermediate Calculations

Standard Error of the Mean ( )

0.02919

Z Value

1.644854

Sampling Error/Margin of Error (= SE *Z Value)

-0.48004

Confidence Interval

Interval Lower Limit (= Sample Mean - ME)

1.959964

Interval Upper Limit (= Sample Mean + ME)

0.075557

CIProportion

Confidence Interval for proportion (p)

Data

Sample Size (n)

400

Count of Successes

152

Confidence Level

95%

Intermediate Calculations

Sample Proportion (p)

0.53055

Z Value

2.820596

Standard Error of the Proportion ( )

1.11453

Sampling Error/Margin of Error (= SE * Z Value)

2.185803

Confidence Interval

Interval Lower Limit (= Sample Proportion - ME)

1.543923

Interval Upper Limit (= Sample Proportion + ME)

1.720832

SampleSize

Sample size for a Proportion

Data

Estimate of True Proportion ( p or p )

0.502277

Sampling Error/Margin of Error

0.703085

Confidence Level

1.077723

Intermediate Calculations

Z value

65535

Calculated Sample Size

1.718329

Result

Minimum Sample Size Needed

0.476206

Sample size for a Mean

Data

Population OR Sample Standard Deviation ( s or s)

0.877021

Sampling Error/Margin of Error

10.04553

Confidence Level

0.086208

Intermediate Calculations

Z value

2.820596

Calculated Sample Size

1.720832

Result

Minimum Sample Size Needed

0.043851

HT Mean

Hypothesis Test for µ (Mean)

Hypotheses

Null Hypothesis

µ

28.21146

Alternative Hypothesis

µ

0.111642

Test Type

Level of significance

α

-0.48004

Critical Region

Critical Value (s)

183.8

Population Standard Deviation

-0.981

Sample Data

Sample Mean

0.107785

Sample Size

1.213268

Standard Error of the Mean

23644.2

Z Sample Statistic

1.080445

p-value

23644.2

Decision

Sample data has been presented has improvise salary stracture has need in organizational benefits .

Hypothesis Test for µ (Mean)

Hypotheses

Null Hypothesis

µ

59.1105

Alternative Hypothesis

µ

1.720832

Test Type

Level of significance

α

Critical Region

Degrees of Freedom

1.410573

Critical Value (s)

1.213268

Sample Data

Sample Standard Deviation

20.2

Sample Mean

-0.13838

Sample Size

0.45088

Standard Error of the Mean

400

t Sample Statistic

1.720832

p-value

65535

Decision

Null hypothesis has presented that need to be developed by higher produced

HT Proportion

Hypothesis Test for π (Proportion)

Hypotheses

Null Hypothesis

π

3.325

Alternative Hypothesis

π

0.054827

Test Type

0.768669

Level of significance

α

23644.2

Critical Region

Critical Value (s)

1.213268

Sample Data

Sample Size

18173

Count of 'Successes'

100.9127

Sample proportion, p

163.6

Standard Error

0.075557

Z Sample Statistic

20.2

p-value

-1.58107

Decision

Null hypothesis has presented has in this projected dataset

References

  • Dilig-Ruiz, A., MacDonald, I., Varin, M.D., Vandyk, A., Graham, I.D. and Squires, J.E., 2018. Job satisfaction among critical care nurses: A systematic review. International journal of nursing studies, 88, pp.123-134.
  • Judge, T.A., Zhang, S.C. and Glerum, D.R., 2020. Job satisfaction. Essentials of job attitudes and other workplace psychological constructs, pp.207-241.
  • Kasalak, G. and Dagyar, M., 2020. The Relationship between Teacher Self-Efficacy and Teacher Job Satisfaction: A Meta-Analysis of the Teaching and Learning International Survey (TALIS). Educational Sciences: Theory and Practice, 20(3), pp.16-33.
  • Liu, J., Zhu, B., Wu, J. and Mao, Y., 2019. Job satisfaction, work stress, and turnover intentions among rural health workers: a cross-sectional study in 11 western provinces of China. BMC family practice, 20(1), pp.1-11.
  • Lu, H., Zhao, Y. and While, A., 2019. Job satisfaction among hospital nurses: A literature review. International journal of nursing studies, 94, pp.21-31.
  • Meng, J. and Berger, B.K., 2019. The impact of organizational culture and leadership performance on PR professionals’ job satisfaction: Testing the joint mediating effects of engagement and trust. Public Relations Review, 45(1), pp.64-75.
  • Nelson, A., Cooper, C.L. and Jackson, P.R., 2018. Uncertainty amidst change: The impact of privatization on employee job satisfaction and well-being. In Managerial, Occupational and Organizational Stress Research (pp. 345-359). Routledge.
  • Paais, M. and Pattiruhu, J.R., 2020. Effect of motivation, leadership, and organizational culture on satisfaction and employee performance. The Journal of Asian Finance, Economics and Business, 7(8), pp.577-588.
  • Pinzone, M., Guerci, M., Lettieri, E. and Huisingh, D., 2019. Effects of ‘green’training on pro-environmental behaviors and job satisfaction: Evidence from the Italian healthcare sector. Journal of Cleaner Production, 226, pp.221-232.
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