Data Information: Wage Income Statistics: Men VS Women Wage gap, by description, is the difference in salary among two groups of people. The description is associated with the practice of paying one gender more than the other. For many years there has been speculation and research done to determine if men are earning more income than women in the same job position. These speculations prompt the United States Senate and House of Representative to assemble Equal Pay Act of 1963 which prohibits discrimination of salary on account of gender (U.S. Equal Employment Opportunity Commission, n.d.). The act has been in existence since the late 60’s and today there is still talk about the difference in pay. In this assignment information from the data set on wage and wage earners will be analyzed by using descriptive statistic to determine if men in fact earn more than women. Measures of Center Tendency, Dispersion, and Skew The statistical data for wages between men and women support the hypothesis that men make more money than women. The central tendency of mean calculates that the average male earns $36, 492.92 annually while women only average $24,451.51. One could argue that the difference is caused by one male in the population making an extreme amount more than the rest of the population. The central tendency of median does agree with the information presented with the mean. The median income for the women of the population is $21,716. Although this number is close to the average, it still falls short of the men’s median income of $32,138. One central tendency we do not see with the population is the same amount of income being made for more than one subject so there is no mode with the data. Understanding the dispersion and skew of the data can show how different the sample data is from their individual means. The sample data from the men show that their dispersion is less than the women’s sample income. When we look at the coefficient of variation percentages one can see that the men’s income levels are closer than that of the women’s. Both the men and women’s income levels are skewed to the right. This shows that the majority median income is less than the mean and there are a few high levels of income. Looking at all aspects of the dispersion and central tendency and one could ultimately see that when one compares the sample data of income that the men do produce more than the women. I need help with "based on your skew value and histogram, discuss the best measures of central tendency and dispersion of your data. Justify your selection." Please help

Question

Data Information: Wage Income Statistics: Men VS Women Wage gap, by description, is the difference in salary among two groups of people. The description is associated with the practice of paying one gender more than the other. For many years there has been speculation and research done to determine if men are earning more income than women in the same job position. These speculations prompt the United States Senate and House of Representative to assemble Equal Pay Act of 1963 which prohibits discrimination of salary on account of gender (U.S. Equal Employment Opportunity Commission, n.d.). The act has been in existence since the late 60’s and today there is still talk about the difference in pay. In this assignment information from the data set on wage and wage earners will be analyzed by using descriptive statistic to determine if men in fact earn more than women. Measures of Center Tendency, Dispersion, and Skew The statistical data for wages between men and women support the hypothesis that men make more money than women. The central tendency of mean calculates that the average male earns $36, 492.92 annually while women only average $24,451.51. One could argue that the difference is caused by one male in the population making an extreme amount more than the rest of the population. The central tendency of median does agree with the information presented with the mean. The median income for the women of the population is $21,716. Although this number is close to the average, it still falls short of the men’s median income of $32,138. One central tendency we do not see with the population is the same amount of income being made for more than one subject so there is no mode with the data. Understanding the dispersion and skew of the data can show how different the sample data is from their individual means. The sample data from the men show that their dispersion is less than the women’s sample income. When we look at the coefficient of variation percentages one can see that the men’s income levels are closer than that of the women’s. Both the men and women’s income levels are skewed to the right. This shows that the majority median income is less than the mean and there are a few high levels of income. Looking at all aspects of the dispersion and central tendency and one could ultimately see that when one compares the sample data of income that the men do produce more than the women. I need help with "based on your skew value and histogram, discuss the best measures of central tendency and dispersion of your data. Justify your selection." Please help

Answer 1

To discuss the best measures of central tendency and dispersion of the data based on the skew value and histogram, we need to understand the concepts of skewness, measures of central tendency, and dispersion.

Skewness is a statistic that measures the asymmetry or lack of symmetry in a data set's distribution. A positive skewness value indicates a longer and fatter right tail, while a negative skewness value indicates a longer and fatter left tail. Skewness helps us understand the shape of the distribution.

Measures of central tendency, such as the mean, median, and mode, provide a single representative value for the entire data set. The mean is calculated by summing up all the values and dividing by the total count. The median is the middle value when the data is sorted in ascending or descending order. The mode is the value that occurs most frequently in the data set.

Dispersion measures, such as range, standard deviation, and coefficient of variation, help us understand how spread out or concentrated the data values are.

Now, let's discuss the best measures of central tendency and dispersion based on the skew value and histogram.

The given information states that the data for both men and women's income is skewed to the right. This means that there are a few high-income outliers pulling the mean to the right, making it larger than the median. In this case, the mean may not be the best measure of central tendency because it is sensitive to outliers.

Instead, the median would be a more appropriate measure of central tendency because it is less affected by extreme values. The median represents the middle income value, which is less influenced by the few high-income outliers in the distribution.

For dispersion, one measure that could be appropriate is the interquartile range (IQR). The IQR is a measure of spread that considers the middle 50% of the data, ignoring potential outliers. It is calculated as the difference between the third quartile (Q3) and the first quartile (Q1). Using the IQR can provide a better understanding of the spread without being influenced by extreme values.

In summary, based on the skew value and the fact that the data is skewed to the right, the best measures of central tendency would be the median and the best measure of dispersion would be the interquartile range (IQR). These measures are less affected by extreme values and provide a more accurate representation of the data.