IBM SPSS Factor Analysis Assignment

IBM SPSS Factor Analysis Assignment
Complete the following: In your IBM SPSS Statistics Step by Step text, read Chapter 20, “Factor Analysis.” Some of the material is quite mathematical, so do not worry if you cannot follow the math. On the other hand, the terms and logic of principal components and factor analysis are important. Having read Chapter 20 in Applied Statistics, you should be able to make sense of this material. Internet Download the data for this assignment from the eResources file. The name of the file for this week is helping2.sav. A description of the study (real data) is given in the chapter. Two separate analyses will be completed with the same set of data to demonstrate the differences between a no-frills analysis and one where additional useful options are selected. The assignment this week is to run a factor analysis on the helping2.sav data. PLEASE FOLLOW THESE INSTRUCTIONS EXACTLY: 1. PLEASE ONLY USE THE FIRST 14 VARIABLES. OMIT VARIABLE 15 AS IT IS NOT A VALID ONE FOR THIS ANALYSIS. 2. IMPORTANT – YOU ONLY HAVE TO DO AND TURN IN THE FULL ANALYSIS, THE ONE WHICH INCLUDES STEP 5a IN IT. YOU DO NOT HAVE TO DO THE FIRST ONE, WHICH THEY REFER TO AS THE SIMPLEST AND BASIC ANALYSIS. SKIP THE STEPS IN THE TABLE AT THE BOTTOM OF PAGE 274, AND INSTEAD DO THE FULL ANALYSIS WITH STEPS GIVEN ON PAGE 275 (note your page numbers may be a bit different in your edition of the text). This full analysis will produce all of the required tables that go in Sections 1 to 4 in your assignment (remember, put the correct tables and figures (properly labeled) in the correct sections, and discuss them there in some detail). 3. At the risk of sounding redundant, you must use and follow the DAA template. You must also include a one paragraph introduction to your paper, and you must include a one paragraph summarization of your paper. Most papers will be around 12 to 18 pages. 4. Follow the G&M steps EXACTLY as they are given, BUT OMIT VARIABLE 15 (see #1 above). Please do not add, subtract, alter or modify anything. There is nothing that is meant to be tricky here. Just do what the instructions for the full analysis asks for, use the proper data set, and you should get the same output. 5. Please be sure that output goes in the correct sections. Assumptions such as the KMO Bartlett test go in the assumption area. Results (scree plot; rotated components matrix) go in the interpretation area. 6. THIS IS IMPORTANT – THERE ARE NO ALPHA LEVELS OR “STANDARD” NULL HYPOTHESES IN FACTOR ANALYSIS. Instead, we have the implied hypothesis that “There will be no satisfactory factor structure to simplify the correlation matrix.” and the implied alternative that “There will be a satisfactory factor structure to simplify the correlation matrix.” More on this soon. USE THESE NULLS AND ALTERNATIVES IN SECTION 3 OF THE DAA TEMPLATE. 
IBM SPSS Factor Analysis Assignment
[u04a1] Unit 4 Assignment 1 IBM SPSS Factor Analysis Follow the directions in Section 20.5 of Chapter 20 in your IBM SPSS Statistics Step by Step text. Reproduce all of the IBM SPSS output from the analysis and copy and paste into a Word document called week4assign.doc. Also see the Data Analysis Formatting Guidelines, linked in the Resources, for more information. The format and organization of this model should be used for all subsequent data analysis assignments. See the Instructor’s Expectations in the course syllabus for additional details. Note that all tables and figures are clearly and appropriately identified. Clarity of writing and following instructions are gradable components of all assignments. Section I – Data File Description The source of the database. Any history or “story” that provides context for the data. All variable(s) that are used in the analysis, including the measurement scale associated with each variable and any missing cases. The number of cases (sample size). The presumed population. Any other general information that describes the data file and variables. Section II – Assumptions, Data Screening, and Verification of Assumptions Clearly identify and verify any assumptions and requirements underlying the use of each inferential statistical procedure. Systematically verify each assumption and requirement for the variables that will be used in the analysis. If an assumption or requirement cannot be verified with the given information, indicate what information would be needed to provide verification. If the assumption or requirement is not consistent with the variables in the data file, indicate what remediation might be undertaken to ameliorate the problem. Screen the data for out-of-bound values and outliers. Section III – Inferential Procedure, Hypotheses, Alpha Level State the alpha level (use .05 unless otherwise indicated). State the research question(s). State the statistical hypotheses, both null and alternative. Indicate what the calculated statistic will be that addresses each of the hypotheses. Section IV – Interpretation Indicate the results and interpret the meaning of the results for each inferential analysis and do this specifically for the variables that are being analyzed. State your conclusions, as they relate directly to the research questions and hypotheses, based on the interpretation of the results. Indicate any limitations or constraints regarding these conclusions.
IBM SPSS Factor Analysis Assignment
Data Analysis Formatting Guidelines The format and organization of this model should be used for all subsequent data analysis assignments. See the Instructor’s Expectations in the course syllabus for additional details. Note that all tables and figures are clearly and appropriately identified. Clarity of writing and following instructions are gradable components of all assignments. Section I – Data File Description The source of the database. Any history or “story” that provides context for the data. All variable(s) that are used in the analysis, including the measurement scale associated with each variable and any missing cases. The number of cases (sample size). The presumed population. Any other general information that describes the data file and variables. Section II – Assumptions, Data Screening, and Verification of Assumptions Clearly identify and verify any assumptions and requirements underlying the use of each inferential statistical procedure. Systematically verify each assumption and requirement for the variables that will be used in the analysis. If an assumption or requirement cannot be verified with the given information, indicate what information would be needed to provide verification. If the assumption or requirement is not consistent with the variables in the data file, indicate what remediation might be undertaken to ameliorate the problem. Screen the data for out-of-bound values and outliers. Section III – Inferential Procedure, Hypotheses, Alpha Level State the alpha level (use .05 unless otherwise indicated). State the research question(s). State the statistical hypotheses, both null and alternative. Indicate what the calculated statistic will be that addresses each of the hypotheses. Section IV – Interpretation Indicate the results and interpret the meaning of the results for each inferential analysis and do this specifically for the variables that are being analyzed. State your conclusions, as they relate directly to the research questions and hypotheses, based on the interpretation of the results. Indicate any limitations or constraints regarding these conclusions.