William Paterson University Department of Sociology. Course Syllabus: SOC/CCJ 3020: Data Analysis

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1 William Paterson University Department of Sociology Course Syllabus: SOC/CCJ 3020: Data Analysis 1. Title of course and number: SOC/CCJ 3020: Data Analysis. 2. Department and secretary's telephone number and address. Department of Sociology Office: Raubinger 465 Telephone Number: (973) Semester offered: Spring Faculty member's name, office hours, telephone number and address Faculty Member: Louis R. Gaydosh, Ph.D. Office: Raubinger 4 th Floor Office Hours: Only by appointment Address: GAYDOSHL@WPUNJ.EDU. 5. Required texts, suggested readings, and other materials for study. Web site for course: 6. Course objectives. The purpose of this course is to convey an understanding of the role of (primarily) statistical analysis in the disciplines of sociology and criminal justice. This includes discussion of why sociologists/criminologists use statistics in their research, as well as presentation of techniques of quantitative data analysis. Specific objectives include: A. To acquaint students with levels of measurement in the social sciences. B. To familiarize students with the variety of data available online that are relevant to sociology and criminal justice. C. To develop in students a confidence in their ability(ies) to understand and apply statistical procedures in their own research in sociology and criminal justice. D. To make students better "consumers" of research by enhancing their abilities to evaluate critically the studies they read in books, professional journals, newspaper articles, etc. E. To introduce students to the statistical functions included in IBM SPSS Statistics- a powerful data analysis software package available to students across the William Paterson University campus. 7. Student learning outcomes. After completing this course, students should be able to understand the purpose and role of statistical concepts and techniques in the sociological/criminal justice research process. This general outcome will be facilitated through the following more specific learning outcomes. A. Students will be examined specifically on their ability to distinguish between social science variables measured at nominal, ordinal, and interval levels. B. Students will locate data relevant to the disciplines of sociology and criminal justice and prepare them for analysis.

2 C. Students will know how to enter data into relevant computer software programs and use IBM SPSS Statistics to generate and produce the following descriptive statistics: measures of central tendency- mode, median, mean; measures of variability- range, inter-quartile range, variance, standard deviation; percentages; proportions; 5-number summary. D. Students will examine the relationships between 2 (or more) variables using appropriate measures of association and correlation- specifically Chi-square and Pearson correlation coefficient; they will also apply linear regression techniques to predict values of [dependent] variables. E. Students will demonstrate understanding of inferential statistics through application of the relevant inferential procedures, such as the t-test, ANOVA, and other techniques. F. Students will show their ability(ies) to apply the commands and procedures of IBM SPSS Statistics relevant to statistical analysis- in 2 respects: i. Applying IBM SPSS Statistics to the solution of problems assigned specifically in this course; and ii. Developing knowledge of how and when to use IBM SPSS Statistics in the analysis, testing, and interpretation of quantitative data in wider research contexts. Test 1 8. Topical outline of the course content. I. Introductory Concepts. 1. Introductory Comments on Statistics. 2. Introduction to IBM SPSS Statistics 3. Descriptive and Inferential Statistics. 4. Locating Relevant Data Online. 5. Entering Data for Analysis in IBM SPSS Statistics. II. Variables and Levels of Measurement: Population and Sample. 1. Variables: Levels of Measurement. 2. Variables: Recoding and Computing. 3. Population and Sample Defined 4. Sample Selection III. Organization and Presentation of Data Test Descriptive Statistics: Measures of Central Tendency 2. Descriptive Statistics: Measures of Variability 3. Descriptive Statistics: Measure of Position 4. Descriptive Statistics: Five-number Summary and Coefficient of Variation

3 III. Introduction to Graphing Functions in IBM SPSS Statistcs. 1. Graphing Function: Boxplot 2. Graphing Function: Scatterplot. 3. Graphing Function: Histogram 4. Graphing Function: Bar Graph 5. Graphing Function: Pic Chart IV. Analyzing More than One Variable: Cross-tabulation and Measures of Association for Nominal and Ordinal Variables. Test 3 1. Cross-tabulation using Crosstabs in IBM SPSS Statistics 2. Measures of Association for Nominal and Ordinal Variables: Lambda, Gamma, Kendall s Tau. V. Correlation and Regression Analysis 1. Correlation Coefficient and Coefficient of Determination 2. Linear Regression: Slope and Y-intercept of a Line V. Hypothesis Testing: Crosstabulation and t-test. Test 4 1. Formulating Null and Research Hypotheses. 2. The Meaning of (Statistical) Significance. 3. Testing Hypotheses about Independent Variables- Chi-square 4. Testing Hypotheses about Differences Between Two Means- t-test 5. Testing Hypotheses about Differences Between More than Two Means: Analysis of Variance. 6. Testing Hypotheses about Correlation Coefficients Test 5: A comprehensive review of all previous topics. 9. Teaching methods (e.g., lecture, discussions, presentations, etc.). As an elementary course, classroom lectures and interactive laboratory demonstrations are the primary teaching methods. In addition, students will be required to learn the use of computing technology, particularly IBM SPSS Statistics, as an aid to calculation and problem-solving. Also, students will be expected to utilize the resources of the Internet and World Wide Web to explore selected topics in greater detail. 10. Course expectations: a. Reading Assignments Students will be expected to read at least one chapter per week (see above Topical outline of the course content ), and to visit appropriate World Wide Web sites as assigned. b. Tentative timeline for submission of written assignments or other work. Students will be required to submit computer assignments illustrating their work in IBM SPSS Statistics and PowerPoint slides of their findings.

4 Students will use search engines and other programs to access and manage data and datasets. Data will typically be derived from publicly available Web sites, although some data will be collected by students from questionnaires or other instruments. Students will be notified of dates on which assignments are due at the time of the assignment(s). Generally, students will have one week to complete assignments. c. Attendance. Attendance will be recorded at each class session and students are expected to attend all classes. If a student is unable to attend a class (for any reason), he/she should notify the instructor in advance. If this is not possible, the student must make arrangements to make up whatever work he/she has missed. It is the student s responsibility to complete all work in the course. A student will not be given a grade if he/she does not complete all work in the course. d. Participation in out-of-class activities (e.g. in labs, workshops, performances, etc.). Students will be expected to complete assignments using IBM SPSS Statistics and/or PowerPoint in various computer facilities on campus or other venues. In addition, students will be expected to visit assigned World Wide Web sites as assigned. e. Examinations (tentative dates, make-up policy, etc.). There will be five (5) examinations given during the semester. Tentative dates follow. Exam 1: Week of February 3-7; Exam 2: Week of March 10-14; Exam 3: Week of April 14-18; Exam 4: Wednesday, May 7, 2014 (combined with comprehensive Review Exam); Exam 5: Wednesday, May 7, 2014 (comprehensive Review Exam). Both Exam 4 and the comprehensive Review Exam will be given in the same examination period. Examination Policies. All exams will be announced (at least one week) in advance. Exams will include a variety of question types- primarily objective, but also some others. There will be NO make-up exams for unexcused absences; students granted permission to take a make-up exam must do so prior to the NEXT class meeting following the original exam administration. Exams will be graded according to the following standards. Numerical Score / Letter Grade / A / A / B / B / B / C / C / C / D / D 58 or below / F Students must take all exams in order to receive a grade for the course. All exams will be weighted equally in computing the student's final grade.

5 Final grades for the course will also be based on these standards. f. Class participation. g. Students are welcome to ask questions and participate in classroom discussions of topics relevant to the subject matter of the course. Participation is a function of attendance; on this matter, see Attendance policies above. 11. Grading and other methods for assessing student academic performance. For the structure and function of examinations in this course, see Examination Policies above. Students will also be expected to visit World Wide Web sites and submit reports and documents from said Web sites as assigned. 11. Additional information such as availability of academic support services, tutoring, etc. Tutoring is available at the Academic Support Center in Raubinger Hall. A list of tutors and subjects, as well as their weekly schedules will be published and distributed to students. 13: Last day to withdraw from a course: Wednesday, March 23, 2016.

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