variables

LaTonya Carroll 

RE: Discussion - Week 3 

COLLAPSE

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Measure of Central Tendency

Continuous Variable: Respondent Income in Constant Dollars

            When looking at the distribution of data within a sample, central tendency is often used. Measure of central tendencies include mean, median and mode. Looking at the continuous variable respondents’ income in constant dollars, the mean which is the average of the data sample is $30,647.90. The mean of this distribution provides an average of the respondent’s income in constant dollars. The median of a data sample is the data point that occurs in the middle of the distribution, which is $24,017. The mode is the measure of central tendency that has the highest frequency of occurrence and it is the only measure that can be used in nominal variables, whereas mean, and median, and mode can be used with interval and ordinal variables. The best measure of central tendency that could be used is the median. This is due to the mean being affected by a few extreme outliers (Laureate, 2014). 

The median in this income distribution shows the midpoint of the distribution. This is helpful in that the mean is affected by outliers, which is not really helpful in that is provides an inflated picture of average respondent income. Also, the mode is not helpful, because it just tells the reviewers the most frequent income that occurs amongst the respondents. The standard deviation of the respondent’s income is $29,628.15. Because of the outliers, It is somewhat high. When you look at distribution, instead of only 68% of the respondent’s income falling within the standard deviation, it shows it is closer to 80-90% (Laureate, 2014).  The variability of data tells the reviewer how the spread out the data is. Looking at the skewness of the data, one would conclude that there is not a lot of variability as the skewness is 2.578, which is close to being zero. The range is very wide, being $158,287, but the mean is $30,647.90. A few extreme outliers make the distribution appear as if it had a larger positive skew, however, the distribution actually shows almost a normal distribution with no skew. The data shows increased average income due to a few incomes reported $100,000 or more of the average.  the most frequently occurring income is higher than the average income of all respondents. 

Categorical Variable: Should Marijuana be made legal?

The frequency distribution of this categorical variable is not skewed. Respondents are almost equal in their opinion of whether or not marijuana should be legalized, with 54% of the respondents agreeing that marijuana should be  legalized whereas 46% saying is should not be legalized. An appropriate measure of variation for this distribution in this case could be the mean. Because the variable is code with a 1 and 2, it helps to see what the higher number of respondents lie. However, in saying that the mode is 1, which lends to the distribution of more respondents choosing to legalize versus not. The mode is the category or data point that has the highest frequency in the dataset. There is not a way to calculate a median and mean as there are not any numbers to calculate. There is not much variability in the distribution with the skew being 0.161, which almost zero (Laureate, 2014; Frankfort-Nachmias, 2020). This data shows that the respondents are indecisive as a whole within the sample with a little over half being in favor of legalizing marijuana versus not. 

Social Change

Respondent Income in constant Dollars

The income in constant dollars of respondents can provide information as to the socioeconomic status of the sample. For example, could help determine if assistance is needed, how much respondents would be eligible to receive in unemployment benefits, or the socioeconomic status of the respondents. City and local taxes are driven by income, income is falsely elevated it could mean that some services that would have been covered by the government would fall on the taxpayers. However, this could be helpful when calculating the average income in the area. Because of the extreme outliers, the average income is elevated, which could prove beneficial for individuals selling their homes (Beatty et al, 2020) 

Legalization of Marijuana

Determining the opinions of respondents on whether or not marijuana should be made legal is important. Legalizing marijuana is important for medical and social reasons. However, there are mounting concerns that the legalization of marijuana will contribute abuse and/ or crime related to marijuana use. There has been increasing issues with marijuana being grown in the states where it is legal, then being sent to other countries by drug cartels. Also, in the capital cities of those states who had legalized marijuana prior to this study, many had an increase in murder rates after marijuana legalization. The overall murder rates have remained constant. In regard to traffic safety and driving under the influence, there was no increase in arrest, but actually a decrease. Because although it may be legal to smoke marijuana in some states, it is still illegal to drive under the influence of marijuana. However, there was a slight increase in substance abuse treatment abilities. (Zvonarev et al., 2019). 

REFERENCES

 Beatty, K., Heffernan, M., Hale, N., & Meit, M. (2020). Funding and Service Delivery in Rural and Urban Local US Health Departments in 2010 and 2016. American Journal of Public Health, 110(9), 1293–1299. https://doi-org.ezp.waldenulibrary.org/10.2105/AJPH.2020.305757

Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.

Laureate Education (Producer). (2016d). Descriptive statistics [Video file]. Baltimore, MD: Author.