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Please answer those questions with one paragraph for each Post, nr 1,2 and 3(attached)

  1. Was the presentation of results clear? If so, provide some specific comments on why. If not, provide constructive suggestions.
  2. Are you able to understand how the results might relate back to positive social change? Do you think there are other aspects of positive social change related to the results?

Central Tendency and Variability

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            Descriptive statistics allows you to describe a sample by creating a frequency distribution of the variables being examined. The frequency distribution is visually displayed with the variable of the x-axis and the tally of each value on the y-axis (Cipher, 2017). Measures of central tendencies are the mean, median, and mode. The mean is the average of all the values of the variable; the median is the middle value; the mode is the most common reoccurring value (Frankfort-Nachmias et al., 2020).

                                         Continuous Variable: Age of the Respondents

             The data displayed in the histogram in figure 1.2 is the continuous variable; the age of the respondents from the General social survey dataset using IBM SPSS statistics software, version 27 (Walden University, 2014). The dataset for the respondent’s age is 508 (n=508), displayed in Figure 1.1, is clearly outlined. The respondents’ mean age is 48, and the median age is 48, with the mode being 38, which is the most commonly occurring age (Walden, 2014). The standard deviation is 17, with the mean age being 48; the age ranges will be 31 to 75 years of age. The central tendencies of the data are equal, with skewness of -327, no possibilities of error.

                                                      Social Change

              The data displayed in the histogram in figure 1.2 is the age of the respondents, reveals the respondents are middle-aged adults. The data is not skewed, so it would be safe to use to make an assumption of the sample population. The research question that this data could help to answer is:

How does the population’s age influence the federal healthcare programs for the urban communities in the northeast region of the United States?

Figure 1-1: Age of the Respondents                                                                                                                                The data displayed in the histogram in figure 1.2 is the continuous variable; the age of the respondents from the General social survey dataset using IBM SPSS statistics software, version 27 (Walden University, 2014). The respondent’s age dataset is 510 (n=510), with no missing data displayed in Figure 2.1. The frequency distribution shows that of the 510 respondents, 417 were white, which is 81.8% of the sample population, 44 respondents were black, which is 8.6%, and 49 of the respondents from another race at 9.6% of the population sample (Walden, 2014).  

                                                                    Social Change

               The data displayed in figure 2.2 is a bar graph of the category variable; the race of the respondents reveals more respondents that are white in the sample population. The data may have validity and reliability concerns since the data may not be transferable since 81.8% of the respondents were white. The variation in the data of the race of the respondents impedes making assumptions for the population. The research question that the data could help to answer is:

What is the relationship between race and healthcare equity in the rural Midwest of the United States?

Figure1: Frequency Distribution – Race of the Respondents               

                                                References

Cipher, D. J. (2017). Introduction to statistical analysis. In J. R. Gray, S. K. Grove, & S. Sutherland (Eds.), Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (8th ed., 523–527). Saunders Elsevier.

Frankfort-Nachmias, C., Leon-Guerrero, A. Y., & Davis, G. (2020). Measures of central tendency. In Social statistics for a diverse society (9th ed., pp. 75–111). SAGE Publications, Inc.

Frankfort-Nachmias, C., Leon-Guerrero, A. Y., & Davis, G. (2020). The what and the why of statistics. In Social statistics for a diverse society (9th ed., 8–14, 43-74). SAGE Publications, Inc.

Wagner, III, W. E. (2020). Using ibm® spss® statistics for research methods and social science statistics (7th ed.). SAGE Publications, Inc. (US).

LaTonya Carroll 

RE: Discussion – Week 3 

COLLAPSE

Top of Form

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.

The chosen continuous variable is respondent’s family income in constant dollars.

Mean, Median, Mode, Standard Deviation

First, we will look at simple definitions of mean, median, mode, and standard deviation. The mean is the average of a distribution. The median is the middle of a distribution. The mode represents the category that contains the largest frequency or percentage in the distribution. Standard deviation shows how much variation there is from the mean (Frankfort-Nachmias, 2020). For the chosen continuous variable of respondent’s family income in constant dollars, the mean income in dollars is $27340.21, the median is 21285.00, the mode is 26015, and the standard deviation is 27782.325.

The Better Measure for Central Tendency

Central tendency measures the typical value and reflects the center of the data distribution. When choosing the best measure of central tendency, the level of measurement needs to be considered. With interval-ratio data, we have to look at the shape of the distribution. The mean is the best measure of central tendency when dealing with quantitative data. The median or the mode is appropriate for this data as it is skewed to the right. When data is skewed, the mean may not give accurate information. The median and mode are not affected by extreme scores (Frankfort-Nachmias, 2020). For this variable, I think it would be appropriate to use as the central tendency as it shows the largest score in the distribution.

How variable are the data?

Measures of variability describe how far apart data points fall from the center. It is the amount of dispersion in a dataset. As stated previously, standard deviation shows how much variation there is from the mean. Standard deviation measures the dispersion of the data. The lowest value for standard deviation is 0. When the value is 0, all answers are identical. The further the standard variation is from 0, the more variation there is (Frankfort-Nachmias, 2020; Laureate Education, 2016d). The standard deviation for this variable is 27782.325.

Describe this Data

The data for this variable is quantitative in numerical form. It is continuous, and it is discrete.

Research Question that might Inform Social Change

What effect does family income have on obtaining a higher education degree in young adul

Categorical Variable

            The categorical variable chosen is respondent’s political party affiliation.

A frequency distribution.

            A frequency distribution refers to how often something happens within a sample of values (Frankfort-Nachmias, 2020).  In this case, we are looking at how often respondents reported affiliation with a particular political party. The chart and bar graph below shows the frequency distribution.

Appropriate Measure of Variation.

Because this data is nominal, the mode is used a measure of variation as this is appropriate to the level of measurement.

How variable are the data?

Measures of variability describe how far apart data points fall from the center. It is the amount of dispersion in a dataset. An appropriate way to measuring how variable the data is in a nominal dataset would be to use the equation for the index of qualitative variation (IQV)

IQV = K ( 100 2 − ∑ P c t 2 )

100 2 ( K − 1 )

(Frankfort-Nachmias, 2020).  

How would you describe this data?

The data for respondent’s political party affiliation is categorical and nominal.

Research Question that might Inform Social Change

What is the connection between political affiliation, partisanship, and political views among respondents?

 References

 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.

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