8210WK4 ASSGN

In Week 3, you used the same variables as in Week 2 to perform a descriptive analysis of the data. For this Assignment, you will calculate a confidence interval in SPSS for one of the variables from your Week 2 and Week 3 Assign
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ATTACHED FILE(S)
Assignment: Introduction to Quantitative Analysis: Confidence Intervals
In your Week 2 Assignment, you displayed data based on a categorical variable and continuous variable from a specific dataset. In Week 3, you used the same variables as in Week 2 to perform a descriptive analysis of the data. For this Assignment, you will calculate a confidence interval in SPSS for one of the variables from your Week 2 and Week 3 Assignments.
To prepare for this Assignment:
· Review the Learning Resources related to probability, sampling distributions, and confidence intervals.
· For additional support, review the Skill Builder: Confidence Intervals and the Skill Builder: Sampling Distributions, which you can find by navigating back to your Blackboard Course Home Page. From there, locate the Skill Builder link in the left navigation pane.
· Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you chose) from Week 2.
· Choose an appropriate variable from Weeks 2 and 3 and calculate a confidence interval in SPSS.
· Once you perform your confidence interval, review Chapter 5 and 11 of the Wagner text to understand how to copy and paste your output into your Word document.
For this Assignment:
Write a 2- to 3-paragraph analysis of your results and include a copy and paste of the appropriate visual display of the data into your document. If you are using the Afrobarometer Dataset, report the mean of Q1 (Age). If you are using the HS Long Survey Dataset, report the mean of X1SES.
Based on the results of your data in this confidence interval Assignment, provide a brief explanation of what the implications for social change might be.
By Day 7
Submit your Introduction to Quantitative Analysis: Confidence Intervals Assignment.
Submission and Grading Information
To submit your completed Assignment for review and grading, do the following:
· Please save your Assignment using the naming convention “WK4Assgn+last name+first initial.(extension)” as the name.
· Click the Week 4 Assignment Rubric to review the Grading Criteria for the Assignment.
· Click the Week 4 Assignment link. You will also be able to “View Rubric” for grading criteria from this area.
· Next, from the Attach File area, click on the Browse My Computer button. Find the document you saved as “WK4Assgn+last name+first initial.(extension)” and click Open.
· If applicable: From the Plagiarism Tools area, click the checkbox for I agree to submit my paper(s) to the Global Reference Database.
· Click on the Submit button to complete your submission.
REFERENCES
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.
· Chapter 5, “The Normal Distribution” (pp. 151-177)
· Chapter 6, “Sampling and Sampling Distributions” (pp. 179-209)
· Chapter 7, “Estimation” (pp. 211-240)
Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
· Chapter 3, “Selecting and Sampling Cases”
· Chapter 5, “Charts and Graphs”
· Chapter 11, “Editing Output”
·
http://rpsychologist.com/index.html
http://academicguides.waldenu.edu/rsch8210
http://onlinestatbook.com/2/estimation/ci_sim.html
Skill Builders:
· Confidence Intervals
· Sampling Distributions
To access these Skill Builders, navigate back to your Blackboard Course Home page, and locate “Skill Builders” in the left navigation pane. From there, click on the relevant Skill Builder link for this week.

Rubric Detail
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Name:RSCH_8210_Week4_Assignment_Rubric

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Excellent

Good

Fair

Poor

Analysis and Results

Points:
Points Range:
36 (60%) – 40 (66.67%)

Paper includes a clear description of the chosen variables, their unit of analysis, and their levels of measurement. A clear visual display of the data (if appropriate) is also provided, and a detailed description is given about how these quantitative reasoning and analysis skills will translate into the ability to enact positive social change.
Overall, the paper demonstrates an excellent understanding of the chosen variables and their utility.
Feedback:

Points:
Points Range:
32 (53.33%) – 35 (58.33%)

Paper includes a description of the chosen variables, their unit of analysis, and their levels of measurement. A visual display of the data (if appropriate) is also provided, and a description is given about how these quantitative reasoning and analysis skills will translate into the ability to enact positive social change.
Overall, the paper demonstrates a good understanding of the chosen variables and their utility.
Feedback:

Points:
Points Range:
28 (46.67%) – 31 (51.67%)

Paper includes a description of the chosen variables, but the description is missing one or more of the following details: their unit of analysis, their levels of measurement, and/or a visual display of the data (if appropriate).
A description is given about how these quantitative reasoning and analysis skills will translate into the ability to enact positive social change, but the description is vague.
Overall, the paper demonstrates a fair understanding of the chosen variables and their utility.
Feedback:

Points:
Points Range:
0 (0%) – 27 (45%)

Paper includes a description of the chosen variables, but the description is missing several of the following details: their unit of analysis, their levels of measurement, and/or a visual display of the data (if appropriate).
A description is not given about how these quantitative reasoning and analysis skills will translate into the ability to enact positive social change.
Overall, the paper demonstrates a poor understanding of the chosen variables and their utility.
Feedback:

Writing

Points:
Points Range:
18 (30%) – 20 (33.33%)

Paper is well organized, uses scholarly tone, follows APA Style, uses original writing and proper paraphrasing, contains very few or no writing and/or spelling errors, and is fully consistent with graduate-level writing style. Paper contains multiple, appropriate and exemplary sources expected/required for the assignment.
Feedback:

Points:
Points Range:
16 (26.67%) – 17 (28.33%)

Paper is mostly consistent with graduate-level writing style. Paper may have some small or infrequent organization, scholarly tone, or APA Style issues, and/or may contain a few writing and spelling errors, and/or somewhat less than the expected number of or type of sources.
Feedback:

Points:
Points Range:
14 (23.33%) – 15 (25%)

Paper is somewhat below graduate-level writing style, with multiple smaller or a few major problems. Paper may be lacking in organization, scholarly tone, APA Style, and/or contain many writing and/or spelling errors, or shows moderate reliance on quoting versus original writing and paraphrasing. Paper may contain inferior resources (number or quality).
Feedback:

Points:
Points Range:
0 (0%) – 13 (21.67%)

Paper is well below graduate-level writing style expectations for organization, scholarly tone, APA Style, and writing, or relies excessively on quoting. Paper may contain few or no quality resources.
Feedback:

Show Descriptions

Show Feedback

Analysis and Results–
Levels of Achievement:
Excellent
36 (60%) – 40 (66.67%)
Paper includes a clear description of the chosen variables, their unit of analysis, and their levels of measurement. A clear visual display of the data (if appropriate) is also provided, and a detailed description is given about how these quantitative reasoning and analysis skills will translate into the ability to enact positive social change.
Overall, the paper demonstrates an excellent understanding of the chosen variables and their utility.
Good
32 (53.33%) – 35 (58.33%)
Paper includes a description of the chosen variables, their unit of analysis, and their levels of measurement. A visual display of the data (if appropriate) is also provided, and a description is given about how these quantitative reasoning and analysis skills will translate into the ability to enact positive social change.
Overall, the paper demonstrates a good understanding of the chosen variables and their utility.
Fair
28 (46.67%) – 31 (51.67%)
Paper includes a description of the chosen variables, but the description is missing one or more of the following details: their unit of analysis, their levels of measurement, and/or a visual display of the data (if appropriate).
A description is given about how these quantitative reasoning and analysis skills will translate into the ability to enact positive social change, but the description is vague.
Overall, the paper demonstrates a fair understanding of the chosen variables and their utility.
Poor
0 (0%) – 27 (45%)
Paper includes a description of the chosen variables, but the description is missing several of the following details: their unit of analysis, their levels of measurement, and/or a visual display of the data (if appropriate).
A description is not given about how these quantitative reasoning and analysis skills will translate into the ability to enact positive social change.
Overall, the paper demonstrates a poor understanding of the chosen variables and their utility.
Feedback:

Writing–
Levels of Achievement:
Excellent
18 (30%) – 20 (33.33%)
Paper is well organized, uses scholarly tone, follows APA Style, uses original writing and proper paraphrasing, contains very few or no writing and/or spelling errors, and is fully consistent with graduate-level writing style. Paper contains multiple, appropriate and exemplary sources expected/required for the assignment.
Good
16 (26.67%) – 17 (28.33%)
Paper is mostly consistent with graduate-level writing style. Paper may have some small or infrequent organization, scholarly tone, or APA Style issues, and/or may contain a few writing and spelling errors, and/or somewhat less than the expected number of or type of sources.
Fair
14 (23.33%) – 15 (25%)
Paper is somewhat below graduate-level writing style, with multiple smaller or a few major problems. Paper may be lacking in organization, scholarly tone, APA Style, and/or contain many writing and/or spelling errors, or shows moderate reliance on quoting versus original writing and paraphrasing. Paper may contain inferior resources (number or quality).
Poor
0 (0%) – 13 (21.67%)
Paper is well below graduate-level writing style expectations for organization, scholarly tone, APA Style, and writing, or relies excessively on quoting. Paper may contain few or no quality resources.
Feedback:

Total Points: 60

Name:RSCH_8210_Week4_Assignment_Rubric

1
Variables, Measurement, and SPSS
Student Name
University
Course
Professor’s Name
Date
Variables, Measurement, and SPSS
The Afro barometer dataset publishes valuable information regarding the issues that affect the continent, such as sociopolitical and economic development. It comprises a wide range of variables, which if counted, reach approximately 63 in number. Many factors can be taken into account when operationalizing the variables. They include “individual versus others’ living conditions” and how frequent one goes without a meal. Responses were gathered from participants to inform the assessment of the relationship between the variables identified.In particular, a total of 50000 responses were collected on the variables and analyzed. This variable had ordinal values since it is based on order ranking (Williams, 2020). The list below indicates the findings that were generated after comparing “individual versus others’ living conditions”.

Much Worse than Others:

8%

Worse than Others:

45.9%

Same as Others:

36.5%

Better than Others:

29.6%

Much Better than Others:

11.3%

Total:

93.7%

Total of Missing/Don’t Know:

6.3%
Many types of responses were gathered after raising the question of “how often do you go without eating?” 50000 responses were collected to further investigate this research question. This variable also had an ordinal metric since it was based on ordering and ranking as shown below. Below are the results that were generated after quantifying this variable based on the responses that were collected.

Never

49%

Just Once or Twice:

15.4%

Several Times:

30.5%

Many Times:

14%

Always:

4%

Total:

92.4%

Total Missing/Don’t Know:

7.6%
Based on the above findings, this study further explored the views, feelings, and perceptions of the participants relating to their living conditions and hunger.
To achieve this objective, the performance of these factors were employed for living hunger and living conditions. The study found that two of the most commonly mentioned replies related to revealing that they had never gone hungry and never felt hungry. After assessing the two lowest percentages for hunger and living conditions, this study can conclude that they are better than the rest of the population. In order to gain valuable insights into individuals’ living conditions and quality of life and how regularly they have to go hungry, one can utilize such data for any type of correlation, causality, and statistical significance (Van Roekel & De Theije, 2020). Many strategies and techniques can be employed to enhance their living conditions by spearheading social change. Policymakers and researchers at community levels can, for instance, adopt programs geared towards reducing homelessness, economic empowerment, and job creation (Van Roekel & De Theije, 2020). These initiatives go a long way in reducing the hunger crisis and strengthening food security.
References
Van Roekel, E., & De Theije, M. (2020). Hunger in the land of plenty: The complex
humanitarian crisis in Venezuela.Anthropology Today,36(2), 8-12.
Williams, R. A. (2020).Ordinal independent variables. SAGE Publications Limited.

Visually Displaying Data Results
Name
Institution
Course
Professor’s name
Date
1
Categorical and Continuous Variables
It is possible to use a variety of factors to convey one’s point of view through visual representations (Frankfort-Nachmias & Leon-Guerrero, 2018). This assignment required the selection of one category and one explanatory variable from a data collection. The variables were then presented in a graphic format. Categorical variables have only a few possible values and a restricted number of categories, such as yes or no questionnaire survey or gender (Kosara, 2013). For categorical variables, quantitative techniques and pie charts should be used.
Continuous variables are those whose values are always changing and are more complicated than discrete values (Kosara, 2013). Weight and height are both deterministic variables that do not change over time. In order to better visualize interval and ratio data, histograms, line charts, and frequency and percentage graphs should all be used (Kosara, 2013).
Dataset and Visual Display
High School Longitudinal Research data were selected for the study period, socioeconomic demographics, teacher effectiveness, and educational and job histories. It was decided that the school instructors’ criteria for student learning would be the categorical variable. It was decided to use the impression of collective responsibility held by teachers as a continuous variable (HSLongstudy student. sav, 2009). Understanding how instructors create criteria and how they motivate pupils to meet them is one of the aims of this study. It is important to understand these elements to identify potential avenues for social change. The categorical variable was represented by a pie chart, while a histogram represented the continuous variable.

Social Change
The visual display and data set supplied by the pie chart show that the teachers’ norms and expectations are “high” for students. The fact that the labeling concerning the teacher’s accountability did not include any representation of responsibility from the teachers is disturbing. Some say that the designations given appear to imply a lack of obligation on the part of instructors in helping these pupils meet the requirements established by them. To put it another way, if instructors have established high expectations for their pupils, what would they be doing to help their students to reach those expectations?
Programs like tutoring, mentorship, and rewards might help instructors aid their students in fulfilling these goals, as well as motivate students and enables students to have a responsibility in facilitating their student standards are met. Teachers may guarantee they do everything they can to assist students in achieving by removing the mentality of “do as I say, not as I do,” Complex thoughts and information may be conveyed in a single visual presentation, which may seem impossible. A picture is, in fact, worth an old saying when it comes to research.
References
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 (data set file). Retrieved from: HSLongstudy_student.sav [DataSet 1]- IBM SPSS Statistics Data Editor;
Kosara, R. (2013, April 17). Data: Continuous vs. Categorical. Retrieved from https://eagereyes.org/basics/data-continuous-vs-categorical;

Introduction to Quantitative Analysis: Descriptive Analysis
Name
Institution Name
Course Name
Professor’s Name
Date

1
Introduction to Quantitative Analysis: Descriptive Analysis
This analysis was conducted on both US and non-US citizens. The categorization considered the population elements as the Categorical Nominal Variable.
Descriptive analysis

Frequency

Valid Percent

Cumulative Percent

Valid

YES

1186

93.4

93.4
NO 84 6.6 100.0
Total 1270 100.0
Total 2538
The frequency is used to illustrate the overall number of persons who attempted to reply to the survey – 93.4 percent of the participants were American citizens – (6.6 percent) were responsive.
Continuous Variable
SPSS output: Descriptive Statistics Output is as follows (Frankfort & Guerrero, 2018):

Since it is a categorical variable, the “mode” suggests that the information presented above is superior. This indicates that the majority of adolescents concur with the findings of the survey on the significance of scientific education (De Philippis 2015). The use of graphs and pie charts is one method of presenting information in order to make it easier to grasp (Freund, J. E., & Miller, I. 2004). The frequency distribution on the table reveals this information. In the table, it is shown that (4,073) of all adolescents strongly believe that the topic of Sciences presented in their institutions is extremely beneficial. Based on the preceding findings, 49.4 percent = 9,897 youths are in agreement. Both of the surveyed groups provided more information than was requested by chance (50 percent), indicating that (69.7 percent). This further suggests that the majority of American teenagers consider science to be essential to their daily lives and futures.
This knowledge is helpful to our societies since it demonstrates that scientific curriculums are productive and influential in our educational institutions. The goal is to generate a generation of American engineers, software coders and technologists, mathematicians/scientists, and health care professionals. As an employee at a leading academic medical center, I can see where this data may be useful to our program manager in promoting our services. Now that I have done the study and seen the results, I am in a position to tell my superiors that we need to step up our activities to satisfy Chicago’s youth and show them how vital science is to their future success. This was a difficult job that consumed most of my day, but the information I gleaned from it might have significant ramifications for our society. It is time for the United States government and higher education institutions to realize the need for expanded STEM programs and successful career bridge programs (De Philippis, 2015). As a result, the return on that investment may be beneficial to communities across the United States and maybe the rest of the globe.
References
De Philippis, M. (2015). STEM Graduates and High School Curriculum: Does Early Exposure to Science Matter?
Frankfort-Nachmias, C. (2018). Social statistics for a diverse society. Thousand Oaks: Sage
Freund, J. E., & Miller, I. (2004). John E. Freund’s mathematical statistics with applications. Upper Saddle River, NJ: Prentice hall.
GSS General Social Survey | NORC. (n.d.). Retrieved December 3, 2017.

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