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Introduction
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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
 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 DiliRuiz 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.
 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
 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).
 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.
 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
 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.
 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
 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.
 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
 a) A sample size of 400 participants has delivered personal information and job satisfactionrelated 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).
 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 abovementioned 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 
zTest: 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) onetail 
0 

z Critical onetail 
1.644853627 

P(Z<=z) twotail 
0 

z Critical twotail 
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 


200 

Sample Size (n) 
400 

Confidence Level 
95% 



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 


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 

pvalue 
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 

pvalue 
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 

pvalue 
1.58107 

Decision 

Null hypothesis has presented has in this projected dataset 
References
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 Judge, T.A., Zhang, S.C. and Glerum, D.R., 2020. Job satisfaction. Essentials of job attitudes and other workplace psychological constructs, pp.207241.
 Kasalak, G. and Dagyar, M., 2020. The Relationship between Teacher SelfEfficacy and Teacher Job Satisfaction: A MetaAnalysis of the Teaching and Learning International Survey (TALIS). Educational Sciences: Theory and Practice, 20(3), pp.1633.
 Liu, J., Zhu, B., Wu, J. and Mao, Y., 2019. Job satisfaction, work stress, and turnover intentions among rural health workers: a crosssectional study in 11 western provinces of China. BMC family practice, 20(1), pp.111.
 Lu, H., Zhao, Y. and While, A., 2019. Job satisfaction among hospital nurses: A literature review. International journal of nursing studies, 94, pp.2131.
 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.6475.
 Nelson, A., Cooper, C.L. and Jackson, P.R., 2018. Uncertainty amidst change: The impact of privatization on employee job satisfaction and wellbeing. In Managerial, Occupational and Organizational Stress Research (pp. 345359). 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.577588.
 Pinzone, M., Guerci, M., Lettieri, E. and Huisingh, D., 2019. Effects of ‘green’training on proenvironmental behaviors and job satisfaction: Evidence from the Italian healthcare sector. Journal of Cleaner Production, 226, pp.221232.