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Poslední úprava: Mgr. Ivan Petrúšek, Ph.D. (30.01.2024)
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Poslední úprava: Mgr. Ivan Petrúšek, Ph.D. (30.01.2024)
The main objective of this course is to introduce the key statistical theory and teach practical skills in quantitative data analysis. Students will learn the IBM SPSS software environment by editing and analyzing an established questionnaire survey dataset. Hence, the students will learn the basics of secondary data analysis (i.e. basic data management tasks such as creating new variables or subsetting the dataset based on specified conditions, computing descriptive statistics, preparing elementary data visualizations, and making inferences from sample data). This course will prepare students to employ the essential quantitative methods in their research projects and attend follow-up intermediate statistics courses. |
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Poslední úprava: Mgr. Ivan Petrúšek, Ph.D. (30.01.2024)
Required reading: Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. Fourth edition. London: Sage. (detailed reading assignment from the course textbook will be specified after each class) Recommended reading: Agresti, A. (2018). Statistical Methods for the Social Sciences (5th Edition). Pearson. Wheelan, Ch. (2013). Naked Statistics: Stripping the Dread from the Data. W. W. Norton. |
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Poslední úprava: Mgr. Ivan Petrúšek, Ph.D. (30.01.2024)
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Poslední úprava: Mgr. Ivan Petrúšek, Ph.D. (30.01.2024)
Grading will be based on homework assignments (6 mandatory assignments, each worth 5 points) and a final in-class exam (worth 70 points). Students may earn up to 100 total points. Grading:
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, which corresponds to the grade E). |
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Poslední úprava: Mgr. Ivan Petrúšek, Ph.D. (30.01.2024)
Course Schedule Week 1: Course overview. Introduction to the software environment. |