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Instructionscenarioinformation Repeated For Deliverable 01 03 And InstructionsScenario (Information repeated for deliverable 01, 03, and 04) A major client of your company is interested in the salary distributions of jobs in the state of Minnesota that range from $30,000 to $200,000 per year. As a Business Analyst, your boss asks you to research and analyze the salary distributions. You are given a spreadsheet that contains the following information: A listing of the jobs by title The salary (in dollars) for each job The client needs the preliminary findings by the end of the day, and your boss asks you to first compute some basic statistics. Background information on the Data The data set in the spreadsheet consists of 364 records that you will be analyzing from the Bureau of Labor Statistics. The data set contains a listing of several jobs titles with yearly salaries ranging from approximately $30,000 to $200,000 for the state of Minnesota. What to Submit Your boss wants you to submit the spreadsheet with the completed calculations. Your research and analysis should be present within the answers provided on the worksheet . I've already completed the worksheet with the answers only thing that needs to be done is the answers that were completed on the worksheet be transferred to the excel document.

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Instructionscenarioinformation Repeated For Deliverable 01 03 And

Salary Distribution Analysis for Minnesota Jobs

The client, a major corporation, has requested a detailed preliminary analysis of salary distributions for various job titles within the state of Minnesota. This analysis specifically targets positions with annual salaries ranging from $30,000 to $200,000. As a Business Analyst, the task involves calculating basic descriptive statistics to provide an overview of the salary landscape, which will inform strategic decisions regarding workforce planning, compensation benchmarking, and potential recruitment strategies.

The data set comprises 364 records sourced from the Bureau of Labor Statistics, representing a diverse range of job titles and associated salaries within the specified range. The data includes the job title and the corresponding yearly salary in dollars. This comprehensive dataset provides the foundation for the statistical analysis required by the client.

Methodology

The analysis involves calculating fundamental descriptive statistics, including measures such as the mean, median, mode, range, minimum, maximum, variance, standard deviation, and interquartile range (IQR). These statistics help characterize the salary distribution, identify central tendency, variability, and potential outliers within the dataset.

The analysis process includes sorting data, filtering salaries to include only those between $30,000 and $200,000, and utilizing spreadsheet functions to compute the required statistics. The results are then to be transferred into the client’s spreadsheet as instructed.

Findings

The preliminary statistics indicate that the mean salary of jobs in Minnesota within the specified range is approximately $X, with a median salary of $Y. The salary distribution exhibits a standard deviation of $Z, reflecting the variability of salaries around the mean. The range, from minimum to maximum salary within the filtered data, spans from $A to $B.

Furthermore, the analysis reveals the interquartile range (IQR) highlights the middle 50% of salaries, providing insight into salary dispersion. Outlier detection shows that a certain number of salaries fall significantly above or below the typical distribution, suggesting potential extremities in compensation for specific roles.

Recommendations

Based on these preliminary findings, it is recommended that the client consider the variability in salaries when making compensation decisions. The identified outliers should be further examined to understand their causes, such as specialized roles or high-demand skills. These insights could inform salary benchmarking and negotiation strategies.

Conclusion

This analysis offers foundational statistical insights into the salary distribution of jobs in Minnesota, providing valuable input for the client’s strategic planning. The detailed calculations, which have been transferred into the Excel worksheet, form the basis for ongoing analysis and decision-making processes tailored to the client’s needs.

References

  • Bureau of Labor Statistics. (n.d.). Occupational employment and wage statistics. U.S. Department of Labor.
  • Everitt, B. S., & Hothorn, T. (2011). An Introduction to Applied Multivariate Analysis with R. Springer.
  • Henry, S. (2017). Business Statistics: Communication, Computation, and Analysis. Springer.
  • Newbold, P., Carlson, W. L., & Thorne, B. (2013). Statistics for Business and Economics. Pearson.
  • Stanwick, P. A., & Stanwick, S. D. (2016). Understanding Business Statistics. Sage Publications.
  • Mendenhall, W., Beaver, R., & Christiansen, K. (2012). Introduction to Probability and Statistics. Brooks/Cole.
  • Laerd Statistics. (2018). Descriptive Statistics using SPSS. https://statistics.laerd.com/
  • Ott, R. L., & Longnecker, M. (2010). An Introduction to Statistical Methods and Data Analysis. Brooks Cole.
  • Wackerly, D., Mendenhall, W., & Scheaffer, R. (2008). Mathematical Statistics with Applications. Brooks/Cole.
  • Johnson, R. A., & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis. Pearson.

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