Statistics in SPSS - JSM406

• Title: Statistics in SPSS
• Guaranteed by: Department of Sociology (23-KS)
• Faculty: Faculty of Social Sciences
• Actual: from 2015 to 2016
• Semester: both
• E-Credits: 8
• Hours per week, examination: 1/1, Ex [HT]
• Capacity: winter:unknown / 25 (25); summer:unknown / unknown (25)
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: taught
• Language: English
• Teaching methods: full-time
• Teaching methods: full-time
• Note: course can be enrolled in outside the study plan; enabled for web enrollment; priority enrollment if the course is part of the study plan; you can enroll for the course in winter and in summer semester
• Guarantor: PhDr. Ing. Petr Soukup, Ph.D.; Mgr. Ivan Petrúšek, Ph.D.
• Teacher(s): Mgr. Ivan Petrúšek, Ph.D.; PhDr. Ing. Petr Soukup, Ph.D.
• Class: Courses for incoming students
• Is pre-requisite for: JSM503, JSM508
• Is interchangeable with: JSM513

Annotation

Last update: Mgr. Ivan Petrúšek, Ph.D. (31.01.2023)

The course is primarily for students of study programme Sociology, Public and Social Policy (in Czech). The course is also recommended to students of Erasmus+ and other foreign exchange programs. All other students will be allowed to enter only if the capacity is not full.

Students will learn and practice basic statistical methods by analyzing sociological survey data in a program called SPSS (Statistical Product and Service Solutions). As this is an introductory course, no previous knowledge of statistics is required.

Literature

Last update: Mgr. Ivan Petrúšek, Ph.D. (27.01.2021)

Mandatory:

Field, A. (2009). Discovering Statistics Using SPSS. Third edition. London: Sage.

(detailed reading assignment from the course textbook will be specified after each class; please view the files section of this course for the pdf of the textbook)

 

Recommended:

Norušis,M., J. (2005).SPSS 13.0: statistical procedures companion. New Jersey: Prentice Hall.

deVaus, D. (2002). Surveys in social research. London:Routledge - Taylor & Francis Group.

Czech students: Mareš, Rabušic, Soukup. Analýza sociálněvědních dat (nejen) v SPSS. 2015. muniPRESS, Brno. (ch. 2 - ch. 10)

Teaching methods

Last update: Mgr. Ivan Petrúšek, Ph.D. (31.01.2023)

The classes are a combination of lectures and seminars. The first part of each class (approx. 40 minutes) is a lecture during which the tutor introduces key concepts in statistical theory and methods of data analysis (see syllabus below). The second part (approx. 40 minutes) is a seminar where students apply the methods introduced during the lecture in the SPSS environment. Institute of Sociological Studies will provide the enrolled students with the SPSS licence (so that they will have the software installed on their personal computers).

The course will be taught in two parallel lectures:

1) Tuesday, 8 a.m., Pekařská building, room 308, 

also possible to enter online via ZOOM:

https://cesnet.zoom.us/j/4677639176?pwd=dVAyWkJISGRrOGp2ZUJRc0I2Y3p2UT09

Meeting ID: 467 763 9176, Passcode: 355749

Materials (recordings, HW evaluation) are available through Google dics: 

https://drive.google.com/drive/folders/1YmsXRQLJm24E4p5IgHEzcYEqQcyViTuJ?usp=sharing

2) Tuesday, 11 a.m, Pekařská building, room 308

also possible to enter online via ZOOM:

https://cuni-cz.zoom.us/j/7173160164 (Passcode: x2VC8r)

 

Requirements to the exam

Last update: Mgr. Ivan Petrúšek, Ph.D. (31.01.2023)

Grading will be based on homework assignments (7 mandatory assignments, each worth 5 points) and a final exam (worth 65 points). Students may earn up to 100 total points.

Deadline for homework assignments: Monday (11:59 am) via email. In other words, students will have eight days to prepare and submit their homework assignments.

Grading:

• 91 - 100 points = grade A
• 81 - 90 points = grade B
• 71 - 80 points = grade C
• 61 - 70 points = grade D
• 51 - 60 points = grade E
• 0 - 50 points = not passed (grade F)

NOTE: Total points earned will be rounded to the whole number (e. g. the overall result of 50.5 points is rounded to 51 points and corresponds to the grade E).

Syllabus

Last update: Mgr. Ivan Petrúšek, Ph.D. (31.01.2023)

Course Schedule

Week 1: Course overview. Introduction to SPSS environment.
Week 2: Descriptive vs inferential statistics. Levels of measurement.
Week 3: Introduction to probability and probability distributions.
Week 4: Sampling variation. Central limit theorem. Confidence intervals (for the mean).
Week 5: Statistical hypotheses testing framework. One-sample t-test.
Week 6: Independent-samples t-test. Paired-samples t-test.
Week 7: Exploring assumptions of parametric tests. Assumption of normality.
Week 8: Analysis of variance (within- and between-group variability, F-test, post-hoc tests).
Week 9: Analysis of categorical data I (confidence interval for a proportion, introduction to crosstabs).
Week 10: Analysis of categorical data II (chi-square test of independence, contingency coefficients, residuals).
Week 11: Correlation analysis (Covariance, Pearson and Spearman correlation coefficients, Scatterplot).