Opinion for 8.1 and 8.2

| November 23, 2015

1 posts

Re:Module 8 DQ 2


Considering your personal research interest, which of the methods described in this course do you believe will be most useful to your research? Why? This response does not need to be supported with external research.


My personal research interest lies in the area of poverty’s impact on the mind, specifically access to affordable and nutritious foods within low socio-economic food deserts and the relationship that it has with academic standardized test success of African-American junior high school students.


As an educator who is working in an area where:


approximately 17.8% of the population of Virginia lives in a food desert  (the school district being in one of those areas) (USDA-ERS, 2013)

the school district  is 98% African-American

51.4% of children are living below the poverty level (City Data, 2015)

is ranked last in overall health factors out of 133 localities (Mertens, 2015)

has only one of its nine schools accredited based on standardized test scores

I am seeking to establish if there is a correlation between the two.


Based on what we have learned in this course, I believe my research would most benefit from the employment of the Bivariate Correlation method, as I am not currently seeking to establish cause, just relationships as they occur naturally. By employing a correlation, and plotting the variables (perhaps in a scatterplot), I would be able to visually examine if one variable is related, or not, to the change in another. Additionally, the resulting correlation coefficient, would be able to tell me how strong and in which direction, the relationship is (Gravetter&Wallnau, 2010).





City Data (2015).Petersburg, Virginia poverty rate data. Retrieved from: http://www.city-data.com.


Gravetter, F. J. &Wallnau, L. B. (2010). Statistics for the behavioral sciences (9th ed.). Belmont, CA: Wadsworth Cengage Learning.


Mertens, S. (2015, March 29). Petersburg ranks poor in new health report. The Progress Index. Retrieved from: http://www.progress-index.com.


U.S. Department of Agriculture, Economic Research Service (2013). Food deserts in virginia. Retrieved from: http://www.virginiafoodsystemcouncil.org.



Re:Module 8 DQ 2

My main interest is history and how psychology plays into various aspects of history. Therefore, the research as it plays into statistics would fall into the use of how students would fall into the general understanding of those various aspects of history. I believe that the Chi Square design in its various forms is the best method that I will return over and over again. There are several key reasons I believe that the Chi Square will be helpful to my future research.

The Chi Square will give me the ability to objectively glean observed and expected frequencies. The point here is to understand that it is not possible to tell that such observations are dissimilar to prove statistical significance. Thus, “mere” observation can be observed with scientific backing.

The Chi Square strongly supports categorical variables and their differences and when it comes to exploring historical categories this is very importance for there are many various categories that come into play.

History is dealing with many social issues in our world and the Chi Square test is a strong test to use to map out the social responses. Thus, to examine the hypotheses that are often found within history the Chi Square is a great test to use.

Thus, to use the Chi Square will be a great test to use in my historical research and it can also be used in how psychology plays into the exploration of history and how it shapes society. The goal that I have is to understand that history is not mere facts or data about dead people but that it has on going impact upon our society and the future. This demands that we look at categories and the Chi Square test is a perfect design to use to help map out the responses of our modern society.

Re:Module 8 DQ 1

The Chi Square, or nonparametric test, is used to sample data to test out a hypothesis about the shape or proportions of a population distribution (Gravetter&Wallnau, 2010).  For example, if researchers wanted to know whether people voting in a certain district favored a school voucher system was by chance or if there was a pattern for preference, this would involve a comparison between what is observed and what would be expected.

The variables would be: for; maybe; against.

The null hypothesis would state: H0: P1 = P2 = P3 . The percentages in category 1 (for), category 2 (maybe), and category 3 (against) are equal.

The alternative hypothesis would state: H1: P1≠ P2≠  P3with a Type I error.

This would be appropriate because any test between frequencies or proportions of mutually exclusive categories like these three would require the use of chi-square (Triola, 2015).  In this instance, individuals would not be assigned to categories, but instead would be placed into categories based on their decision.  Once a comparison of the obtained value and the critical value is made, then a decision can be made. If the obtained value is more extreme than the critical value, then the null hypothesis cannot be accepted, and the researchers can claim that the distribution of responses across the three groups is not equal.  (Gravetter&Wallnau, 2010).  Since the numerical value of the test is a measure of the discrepancy between the observed and expected frequencies, it makes no assumptions about the parameters of the population and does not require data from an interval or ratio scale.


Gravetter, F. J., &Wallnau, L. B. (2010). Statistics for the behavioral sciences (9th ed.). Belmont, CA: Wadsworth Cengage Learning.

Triola, M. (2015). Essentials of statistics (5th ed.). Boston, MA: Pearson.


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