Discriminant analysis is a statistical technique which can be used classify individuals/cases into groups on the basis of one or more quantitative measures (predictor variables).
For this Assignment, you will run a discriminant analysis using the Week 8 Data File for Discriminant Analysis.sav. You will use “type” as the dependent variable.
To prepare for this Assignment, review Lesson 16A and Lessons 31–35 in your Green and Salkind (2017) text and Week 8 Assignment Template document. Consider how a discriminant analysis will allow you to answer your research questions effectively.
Submit a synthesis of statistical findings derived from discriminant analysis that follows the Week 8 Assignment Template. Your synthesis must include the following:
An APA Results section for the discriminant analysis [see an example in Lesson 35 of the Green and Salkind (2017) text].
Only the critical elements of your SPSS output:
A properly formatted research question
A properly formatted H10 (null) and H1a (alternate) hypothesis
A descriptive statistics narrative and properly formatted descriptive statistics table
A properly formatted combined group plot
An Appendix including the SPSS output generated for descriptive and inferential statistics
An explanation of the differences and similarities of multiple regression analysis and discriminant analyses
Note: You will cut and paste the appropriate SPSS output into the Appendix. The SPSS output is not in APA format, so you will need to type the information from the SPSS output to the appropriate sections of the APA table. You must use the Week 8 Assignment Template to complete this Assignment.
LEARNING RESOURCES
Required Readings
Important Note: Some of the readings found in this course are more than 5 years old. Although we strive to use current references whenever possible, several of the articles/resources found in this course are seminal, or foundational, works.
Green, S. B., & Salkind, N. J. (2017). Using SPSS for Windows and Macintosh: Analyzing and understanding data (8th ed.). Upper Saddle River, NJ: Pearson.
Unit 8, “Correlation, Regression, and Discriminant Analysis Procedures” (pp. 186–224)
Lesson 31, “Pearson Product-Moment Correlation Coefficient” (pp. 186–192)
Lesson 32, “Partial Correlations” (pp. 193–198)
Lesson 33, “Bivariate Linear Regression” (pp. 199–205)
Lesson 34, “Multiple Linear Regression” (pp. 206–215)
Lesson 35, “Discriminant Analysis” (pp. 216–225)
Bougie, R. & Sekaran, U. (2019). Research methods for business: A skill-building approach (8th ed.). Hoboken, NJ: John Wiley & Sons.
Chapter 4, “Defining the Research Problem”
Ethical Issues in the Preliminary Stages of Investigation (p. 61)
Chapter 5, “The Critical Literature Review”
Ethical issues (pp.71-73)
Chapter 10, “Administering Questionnaires”
Ethics in Data Collection (pp. 158-159)
Chapter 11, “Experimental designs”
Ethical Issues in Experimental Design Research (pp. 182-183)
Frechtling, D. C., & Boo, S. (2012). On the ethics of management research: An exploratory investigationLinks to an external site.. Journal of Business Ethics, 106(2), 149–160. doi:10.1007/s10551-011-0986-7
Greenwood, M. (2016). Approving or improving research ethics in management journals.Links to an external site. Journal of Business Ethics, 137(3), 507–520. doi:10.1007/s10551-015-2564-x
Katzenstein, J., & Chrispin, B. R. (2011). Social entrepreneurship and a new model for international development in the 21st century.Links to an external site. Journal of Developmental Entrepreneurship, 16(1), 87–102. doi:10.1142/S1084946711001720
Santhosh, M., & Baral, R. (2015). A conceptual framework for exploring the impacts of corporate social responsibility on employee attitudes and behaviourLinks to an external site.. Journal of Human Values, 21(2), 127–136. doi:10.1177/0971685815594270
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