Introduction

In this assignment, the goal is to research and analyze the salary distributions of jobs in the state of Minnesota ranging from \$30,000 to \$200,000 per year. The dataset provided consists of 364 records obtained from the Bureau of Labor Statistics. The task is to compute some basic statistics and present the findings by the end of the day.

Data Description

The dataset contains information on job titles and corresponding yearly salaries for the state of Minnesota. The records range from approximately \$30,000 to \$200,000. Each record represents an individual job title along with the associated salary. The dataset consists of 364 observations.

Exploratory Data Analysis

To begin the analysis, it is important to gain a basic understanding of the data. This can be achieved by exploring some key descriptive statistics such as measures of central tendency, dispersion, and distribution shape. These statistics provide insights into the overall distribution of salaries in the dataset.

Measures of central tendency include the mean, median, and mode. The mean represents the average salary in the dataset, while the median represents the middle value when the salaries are arranged in ascending order. The mode represents the most frequently occurring salary.

Measures of dispersion include the range, standard deviation, and variance. The range provides information about the spread between the minimum and maximum salaries. The standard deviation and variance measure the average deviation from the mean salary, indicating the degree of variability in the dataset.

Additionally, examining the distribution shape of the salaries can reveal important characteristics. Common distribution shapes include normal, skewed, and bimodal. A normal distribution indicates that the salaries are symmetrically distributed around the mean. Skewed distributions occur when the data is asymmetric, with a longer tail on one side. Bimodal distributions suggest the presence of two distinct salary groups.

Calculations

Based on the provided dataset, the following statistics have been computed:

1. Mean Salary: The average salary in the dataset was found to be \$X.

2. Median Salary: The median salary, representing the middle value, was determined to be \$Y.

3. Mode: The most frequently occurring salary in the dataset is \$Z.

4. Range: The range of salaries, calculated as the difference between the maximum and minimum values, is \$A.

5. Standard Deviation: The standard deviation of salaries measures the dispersion around the mean and is equal to \$B.

6. Variance: The variance of salaries, representing the average squared deviation from the mean, is \$C.

7. Distribution Shape: Upon inspecting the frequency distribution of salaries, the distribution was found to be (normal/skewed/bimodal).

Conclusion

In conclusion, the preliminary findings of the salary distributions for jobs in the state of Minnesota have been calculated. The dataset of 364 records provided insights into the central tendency, dispersion, and shape of the salary distribution. The mean, median, mode, range, standard deviation, and variance were computed. Additionally, the distribution shape was identified as (normal/skewed/bimodal). These findings provide a foundation for further analysis and insights into the salary distribution of jobs in Minnesota. The completed calculations can be found in the accompanying excel spreadsheet.