(in Polish) Analiza statystyczna w chemii 0600-S1-O-ASC
1. Basics of working with IBM SPSS software
2. Preparation of data for statistical analysis
3. Graphical representation of data
4. Measures of central tendency, variability, and asymmetry
5. Point and interval estimation
6. Testing statistical hypotheses
7. Simple and multiple linear regression
8. Analysis of variance
Total student workload
Learning outcomes - knowledge
Learning outcomes - skills
Learning outcomes - social competencies
Expository teaching methods
Exploratory teaching methods
- practical
Type of course
Prerequisites
Course coordinators
Assessment criteria
Assessment methods:
Independently performed projects in the computer lab using IBM SPSS software - W3, U1, U2
Assessment criteria:
0-50% - fail (2)
50-60% - satisfactory (3)
61-65% - satisfactory plus (3+)
66-75% - good (4)
76-80% - good plus (4+)
81-100% - very good (5)
Practical placement
Not applicable
Bibliography
1. J. O. Aldrich, J. B. Cunningham, Using IBM SPSS Statistics: An interactive hands-on approach, SAGE, 2016.
2. A. C. Elliott, W. A. Woodward, Statistical analysis: Quick reference guidebook with SPSS examples, SAGE, 2007.
3. J. McClave, T. Sincich, Statistics, Pearson Education Limited, 2018.
4. J. Miller, J. Miller, Statistics and chemometrics for analytical chemistry, Pearson Education Limited, 2010.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: