For the Session Long Project, you will be analyzing data collected on 87 respondents for the 2016 General Social Survey.
Smith, T. W., Davern, M., Freese, J., & Hout, M. (n.d.) General social surveys, 1972-2016 [machine-readable data file]. Principal Investigator, Smith, Tom W.; Co-Principal Investigators, Peter V. Marsden and Michael Hout; Sponsored by National Science Foundation. –NORC ed.– Chicago: NORC, 2018: NORC at the University of Chicago [producer and distributor]. Data accessed from the GSS Data Explorer website at gssdataexplorer.norc.org.
The objective of this study is to examine predictors for email (number of weekly hours spent using email). This project will involve analyzing descriptive statistics, correlation and bivariate analysis, checking assumptions, and performing linear and multiple regression.
For the SLP, you will be using the GSS.sav dataset, which includes six variables: ID, age (years), email (using email measured in weekly hours), children (number of children), sex (0=female, 1=male), and income (0= LT $1000 – 24999, 1= $25000 or more).
*Please refer to SPSS Commands for tips on analyzing data.
The Methodology section of a study proposal often includes a table summarizing the variables in the study. Provide a table which displays the name of the variable, whether the variable is a DV or IV, and the type of the variable (e.g., categorical, ordinal, continuous).
Stage 1: Data Screening and Descriptive Statistics
Your research assistant has completed data screening for this dataset (the first step before data analysis), which include checking for accuracy, missing data, and outliers.
Conduct analysis of the descriptive statistics and provide a brief report (as you would in the Results section of a peer-reviewed journal). Your report should include descriptive statistics on all pertinent variables in the dataset (i.e., frequencies/percentages for nominal data; mean/median and standard deviations for continuous data).
Include relevant tables in your write-up of the descriptive statistics.
Stage 2. Bivariate Statistics and Correlations
Conduct bivariate analysis of the data and provide a brief report to include in the Results section. Your report should include the following:
Correlation coefficients and p-values of email with age, children, sex, and income.
Whether there is a statistically significant correlation between email with respect to the following: 1) age and 2) children.
Include relevant tables and a description/interpretation of results.
Please submit Module 1 SLP at the end of Module 1.
SLP Assignment Expectations
Your assignment will be graded according to the Quantitative Grading Rubric. (To see the rubric, go to Assessments>Rubrics. Click the arrow next to the rubric name and choose Preview.)
Length: SLP assignments should be at least 2 pages (500 words) in length excluding tables.
References: Any references used should be from academic sources and cited using APA format.
Organization: Subheadings should be used to organize your paper according to question.
Format: This assignment should be written in a scientific format (as in the “Results” section of a peer-reviewed study). APA format is required for all assignments at the PhD level. Refer to the following guidelines in presenting tables and results in APA format: 1. APA Table Guidelines, 2. Reporting Results See Syllabus page for more information on APA format.
Grammar and Spelling: While no points are deducted for minor errors, assignments are expected to adhere to standard guidelines of grammar, spelling, punctuation, and sentence syntax. Points may be deducted if grammar and spelling impact clarity.
The following items will be assessed in particular:
Relevance—All content is connected to the question.
Precision—Specific questions are addressed. Calculations, statements, facts, and statistics are specific and accurate.
Depth of discussion—Points are presented and integrated.
Evidence—Statements are well supported with facts, statistics or references.
Logic—Presented discussion makes sense; conclusions are logically supported by premises, statements, or factual information.
Clarity—Writing is concise and understandable, and subjects are sufficiently described.
Objectivity—The use of first person and subjective bias are avoided.
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