RSCH-8210N-1 Quantitative Reasoning Assignment
Education in the U.S., although still considered influential for overall future success, is floundering in recent times. Issues such as overcrowding, lack of funding, and quality of facilitators are sometimes indicated as the scapegoats for this dilemma (Lynch, 2017), however research data shows that these factors are only minimal contributions to this problem. The purpose of this paper is to take a closer look at data provided that will assist in the following: Identifying variables that may contribute to this issue, explaining units of analysis and levels of measurement that support these variables, and how these variables influence social change RSCH-8210N-1 Quantitative Reasoning Assignment.
Description of Variables
The high school longitudinal study of 2009 provides various possible factors that may contribute to the issues of concern pertaining to education in the United States. Of these, two that mentioned that can be considered as the most influential do not focus on the students themselves, but their parents.
The first variable of interest is highest level of education for the parents. In order to identify this, the data set creates a category system of level in education that include the following: 1- less than high school, 2- high school diploma/GED, 3- certification/diploma from school providing occupational training, 4- Associate’s degree, 5- Bachelor’s degree, 6-Master’s degree, 7- PhD/MD/Law/other high level professional degree (2009)RSCH-8210N-1 Quantitative Reasoning Assignment. Other categories such as -9 (missing information), -8 (non-response), -7 (Item legitimate skip/NA), and 0- No bio/adoptive/step parents in home are identified as well.
The second variable of interest is the employment status of the parents. In order to identify this, the data set creates a category system pertaining to past as well as current employment history to include the following (2009): 1- has never worked for pay, 2- not currently working for pay, 3- currently working part time (less than 35 hours a week), and 4- currently working full time (more than 35 hours a week). Other categories such as -9 (missing information), -8 (non-response), -7 (Item legitimate skip/NA), and -6 (component not applicable) are identified as well.
Unit of Analysis
According to the class reading, the unit of analysis is explained as the object of research, with examples including individuals, groups, organizations, or social artifacts (Frankfort-Nachmias, & Leon-Guerrero, 2018)RSCH-8210N-1 Quantitative Reasoning Assignment. In both variable cases, the unit of analysis would be the parents, in that their past academic history as well as current/history of employment is being utilized as research factor material.
Levels of Measurement
Given the categories in data set for the parent’s highest level of education, the level of measurement would be considered ordinal. The ordinal level of measurement is explained as numbers being assigned to rank order categories, using the example of low, middle, and high (2018). Because the categories of education level ascend from 1 being less than high school education to 7 being PhD/M.D./Law/ other high level professional degree, ordinal level of measurement seems appropriate.
For identifying the level of measurement for parents’ employment status, it is not as clear as it is for the education variable. Although there appears to be a ranking order for employment categories (ordinal), there is a more pronounced dataset that leans to a nominal approach. The nominal level of measurement indicates numbers or other symbols assigned to a set of categories for naming purposes (2018)RSCH-8210N-1 Quantitative Reasoning Assignment. In this capacity, identifying parents by way of employed, full time employed, part time employed, and unemployed can be seen less as a ranking scale, but set groups to fit into.
Variables and Social Change
Implications of social change. Social change can take on different meanings, from changes that influence society to how society influences change. In observing the variables selected, both apply. Low income households as well as lack of education obtained by parents create a disadvantage for children (Ratcliffe, 2015). This goes back to Lynch’s argument on reasons for education failing our youth, stating the first factor being lack of parent involvement (Lynch, 2017)RSCH-8210N-1 Quantitative Reasoning Assignment. The consequence of parents obtaining insufficient education is two-fold, parents have to work more hours to maintain financial stability and they may lack the education needed to assist with homework. Focus on low income/ low education is presented here due to more research available, and is in no way excluding the smaller percentage of children in a moderate to higher income/ education household.
How variables are used for social change. Sadly, these variables represent a large population across the Unites States. How can we utilize these variables to promote social change that can provide a more positive future for our youth? This information can be beneficial in creating programs, such as mentoring or after school programs for children as well as parenting trainings or night school programs, to provide opportunity for change.
Parents do not want to be inaccessible to their children or create a life that can possibly effect the success on their future. Taking notice of this variables that play an influential factor in the future of our children and using them to create preventative measures through assisting these parents, society is initiating change for the betterment as a wholeRSCH-8210N-1 Quantitative Reasoning Assignment.
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: Sage Publications.;
High School Longitudinal Study 2009 Dataset. HSLongStudy_student.sav [DateSet1]- IBM SPSS Statistics Data Editor;
Lynch, M. (2017, April 3). 18 Reasons the U.S. Education System is Failing. Retrieved from https://www.theedadvocate.org/10-reasons-the-u-s-education-system-is-failing/;
Ratcliffe, C. (2015, September). Child Poverty and Adult Success. Retrieved from https://www.urban.org/sites/default/files/publication/65766/2000369-Child-Poverty-and- Adult-Success.pdf; RSCH-8210N-1 Quantitative Reasoning Assignment
Variables, Measurement, and SPSS
The purpose of nursing research is to identify gaps in practice through and evidence-
based review of the literature and to design research that will provide new knowledge to support
nursing science. Developing a research proposal requires the researcher to perform several
complex steps to generate new evidence. Each step must conform to accepted research
guidelines. To be successful, the researcher must understand these steps and have the knowledge
to ensure that each step is followed correctly (Frankfort-Nachmias & Leon-Guerrero, 2018). This
paper will identify and describe two variables from the Afrobarometer dataset. The variables
chosen for this assignment are, Q3b, “Your present living conditions” (Variable 1), and Q8c,
“How often gone without medical care” (Variable 2) (Walden University, 2018). In addition,
how each variable might be used to answer a social change question and the implications for
social change will also be described.
The Afrobarometer data set (Walden University, 2018) was queried using IBM SPSS
statistical software, Version 24. Variable 1 measures respondent’s present living conditions. The
individual is the unit of analysis (Frankfort-Nachmias & Leon-Guerrero, 2018). The level of
measurement is rank ordered and is therefore ordinal (Heavey, 2018). It is constructed on a 5
point pre-coded Likert scale ranked from 1-very bad to 5=very good. It also includes coded
responses -1=missing, 9= don’t know and 998=refused.
Variable 2 measures how often respondent has gone without medical care. The individual
is the unit of analysis (Frankfort-Nachmias & Leon-Guerrero, 2018). The level of measurement
is rank ordered and is therefore ordinal (Heavey, 2018). It is constructed on a 5 point pre-coded RSCH-8210N-1 Quantitative Reasoning Assignment
Likert scale ranked from 0=never to 4=always. It also includes coded responses -1=missing, 9=
don’t know and 998=refused.
The variables were selected because they have a direct relationship to social change as
stated in the Walden Social Change mission which includes making a difference by addressing
challenges where we live, where we work and in the global community (Walden University,
2017, p.7). Both of these variables, your present living conditions and how often gone without
medical care are directly related to helping the researcher understand the current state or
conditions impacting this population. This data would be important to support initiatives to
improve living conditions and access to medical care.
To participate fully in social science research, one must understand how to correctly
apply the principals of statistics. Statistical analysis done correctly will lean toward accurate
results. Not every researcher will become a statistician, but every researcher must understand statistics RSCH-8210N-1 Quantitative Reasoning Assignment 4
Frankfort-Nachimias, C. & Leon-Guerrero, A. (2018). Social statistics for a diverse society. (8th
ed.). SAGE Publications
Heavey, E. (2018). Statistics for nursing: A practical approach. (3rd ed.). Jones and Bartlett
Walden University. (2017). Social change at Walden. In 2017-2018
Walden University catalog. http://catalog.waldenu.edu/mime/media/149/4598/Sept_Cat_
2017.pdf RSCH-8210N-1 Quantitative Reasoning Assignment