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HU Credits:
3
Degree/Cycle:
2nd degree (Master)
Responsible Department:
Criminology
Semester:
1st Semester
Teaching Languages:
Hebrew
Campus:
Mt. Scopus
Course/Module Coordinator:
Prof. Ron Factor
Coordinator Office Hours:
Please coordinate appointments
Teaching Staff:
Prof. Ron Factor,
Ms. OrTal Shyla Baron
Course/Module description:
An advanced statistics course for criminology students
Course/Module aims:
The purpose of this course is to familiarize students with advanced concepts in statistics. The students will learn methods and statistical tests that will enable them to assess studies carried out by others as well as to carry out basic independent research. In particular, the course will introduce the linear and logistic regression models.
Learning outcomes - On successful completion of this module, students should be able to:
To test research hypotheses with linear and logistics regression models; Interpret and present the results of linear and logistics regressions; Evaluate studies that use linear and logistics regression models; Process data using the SPSS and Excel software.
Attendance requirements(%):
100% - Students are required to attend all lectures and lab sessions
Teaching arrangement and method of instruction:
Lectures and lab sessions
Course/Module Content:
1. Measures of association
2. Pearson correlation
3. Simple linear regression
4. Observations and predicted value
5. Assumptions of linear regression
6. Variance explained
7. Significance of regression coefficients
8. Multivariate linear regression
9. Control
10. Multicollinearity
11. Dummy variables
12. Interactions
13. Logistic regression
Required Reading:
וייסבורד, דיוויד ופקטור, רוני (2019). סטטיסטיקה יישומית למדעי החברה ולמשפטים. צפרירים: נבו הוצאה לאור בע"מ.
Additional Reading Material:
אייזנבך, ר. (1992). סטטיסטיקה ללא סטטיסטיקאים. ירושלים: הוצאת אקדמון.
זמיר, ש.; בייט-מרום, ר. (2005). מבוא לסטטיסטיקה לתלמידי מדעי החברה – א', יחידות 1-5. הוצאת האוניברסיטה הפתוחה.
שריד, מ.; שריד, י. (2011). המדריך העברי למשתמש בתכנת ה-SPSS ל-Windows. קרית חיים: מכון שריד – שירותי מחקר והדרכה.
Agresti, A., & Finlay, B. (2009). Statistical Methods for the Social Sciences. New Jersey, NY: Prentice Hall.
Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. London, UK: SAGE Publications.
Fox J. (2008). Applied Regression Analysis and Generalized Linear Models. Los Angeles: Sage.
Kleinbaum, D., & Lawrence, I. (1988). Applied Regression Analysis and Other Multivariable Methods. Boston, MA: PWS-KENT Publishing Company.
Welkowitz, J. (2012). Introductory Statistics for the Behavioral Sciences. Wiley: Hoboken, N.J.
Factor, R. (2014). The Effect of Traffic Tickets on Road Traffic Crashes. Accident Analysis & Prevention, 64, 86-91.
Factor, R. (2019). A Quasi-Experiment Testing a Public Participation Process for Designing and Implementing an Enforcement Program Among Minorities. Journal Of Experimental Criminology, 15, 77-86.
Jonathan-Zamir, T., Weisburd, D., Dayan, M., and Zisso, M. (2019) The Proclivity to Rely on Professional Experience and Evidence-Based Policing: Findings from a Survey of High-Ranking Officers in the Israel Police. Criminal Justice and Behavior (forthcoming).
Morris, R.G., Johnson, M.C. & Higgins, G.E. (2009). The Role of Gender in Predicting the Willingness to Engage in Digital Piracy among College Students. Criminal Justice Studies, 22(4), 393-404.
Reisig, M. D., Bratton, J., & Gertz, M. G. (2007). The Construct Validity and Refinement of Process-Based Policing Measures. Criminal Justice and Behavior, 34(8), 1005-1028.
Weitzer, R., Tuch, S. A., & Skogan, W. G. (2008). Police-Community Relations in a Majority-Black City. Journal of Research in Crime and Delinquency, 45(4), 398-428.
Grading Scheme :
Written / Oral / Practical Exam / Home Exam 85 %
Submission assignments during the semester: Exercises / Essays / Audits / Reports / Forum / Simulation / others 15 %
Additional information:
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