040637 FK WMS: Business Statistics 2 (2013W)
Continuous assessment of course work
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Summary
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Fr 06.09.2013 09:00 to Fr 20.09.2013 14:00
- Registration is open from We 25.09.2013 09:00 to Th 26.09.2013 17:00
- Deregistration possible until Mo 14.10.2013 23:59
Registration information is available for each group.
Groups
Group 1
Termine Tutorium: 8., 22. und 29.11., 10.00-13.00 PC 03
max. 60 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
09.10.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
16.10.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
23.10.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
30.10.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
06.11.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
08.11.
10:00 - 13:00
PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday
13.11.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
20.11.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
22.11.
10:00 - 13:00
PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday
27.11.
18:00 - 20:00
Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
28.11.
16:00 - 18:00
Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
28.11.
18:00 - 20:00
Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
29.11.
10:00 - 13:00
PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday
04.12.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
06.12.
13:00 - 16:00
PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Wednesday
11.12.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
18.12.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
08.01.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
10.01.
15:00 - 16:30
Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
15.01.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
22.01.
18:00 - 20:00
Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
29.01.
08:00 - 10:00
Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
31.01.
08:00 - 10:00
Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Aims, contents and method of the course
Group 2
Tutorium: Mo, 11.11., Mo, 18.11., Mo, 25.11. MO 11.11.2013,14.00-17.00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
max. 60 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Friday
11.10.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
18.10.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
25.10.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
08.11.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
11.11.
14:00 - 17:00
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
15.11.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
18.11.
14:00 - 17:00
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
22.11.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
25.11.
14:00 - 16:00
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Monday
25.11.
19:00 - 20:00
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Friday
29.11.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
06.12.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
13.12.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
16.12.
10:00 - 16:00
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
07.01.
10:00 - 16:00
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
08.01.
15:00 - 17:00
Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
Friday
10.01.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
17.01.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
24.01.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
31.01.
14:00 - 16:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Aims, contents and method of the course
from Brannath/Futschik/Krall:
Chapter 7 Simple regression
Chapter 8 Multiple regression
Chapter 9 Analysis of variance
Chapter 7 Simple regression
Chapter 8 Multiple regression
Chapter 9 Analysis of variance
Group 3
max. 60 participants
Language: German
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Friday
11.10.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
18.10.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
25.10.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
30.10.
18:00 - 20:00
Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
08.11.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
15.11.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
20.11.
17:00 - 18:00
Hörsaal 11 Oskar-Morgenstern-Platz 1 2.Stock
Friday
22.11.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
29.11.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
06.12.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
13.12.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday
18.12.
15:00 - 18:00
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
18.12.
18:00 - 20:00
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
08.01.
09:00 - 11:00
Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday
08.01.
14:00 - 18:00
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Friday
10.01.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
17.01.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
24.01.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Friday
31.01.
16:00 - 18:00
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Aims, contents and method of the course
from Brannath/Futschik/Krall:
Chapter 7 Simple regression
Chapter 8 Multiple regression
Chapter 9 Analysis of variance
Chapter 7 Simple regression
Chapter 8 Multiple regression
Chapter 9 Analysis of variance
Group 4
max. 60 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Monday
07.10.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
14.10.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
21.10.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
28.10.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
04.11.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
11.11.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
18.11.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
25.11.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
02.12.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
09.12.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
16.12.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
13.01.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
20.01.
08:00 - 10:00
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Monday
27.01.
08:00 - 10:00
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Aims, contents and method of the course
This is a 2-hour course:
- Simple linear regression:
Scatterplot, correlation, tests for the coefficients of correlation and regression
- Multiple linear regression:
Coefficient of determination, F-test, t-tests of regression coefficients, dummy-variables, prediction, residual analysis
- Analysis of variance:
Boxplots, one-way analysis of variance, interactionplots, two-way analysis of variance
- Analysis of categorical data:
Chi-squared-test of goodness-of-fit, contingency tables, barplots (grouped, stacked), test of homogenity, test of independence, odds ratio, logistic regressionAn obligatory part of the course is a Tutorial in Statistics.
The contents are:
- Data handling in SPSS
- Analysing data in SPSS
- Conduction of a small empirical survey to a given research question (formulation of hypotheses, development of a questionnaire, data collection, evaluation of the data, summary of the results in a report)
- Simple linear regression:
Scatterplot, correlation, tests for the coefficients of correlation and regression
- Multiple linear regression:
Coefficient of determination, F-test, t-tests of regression coefficients, dummy-variables, prediction, residual analysis
- Analysis of variance:
Boxplots, one-way analysis of variance, interactionplots, two-way analysis of variance
- Analysis of categorical data:
Chi-squared-test of goodness-of-fit, contingency tables, barplots (grouped, stacked), test of homogenity, test of independence, odds ratio, logistic regressionAn obligatory part of the course is a Tutorial in Statistics.
The contents are:
- Data handling in SPSS
- Analysing data in SPSS
- Conduction of a small empirical survey to a given research question (formulation of hypotheses, development of a questionnaire, data collection, evaluation of the data, summary of the results in a report)
Information
Assessment and permitted materials
For the course evaluation, the received points from following three parts will be taken into account:
- Tests (midterm- and end of term): 15 and 25 Points
- Tutorial project: 15 Points
- Cooperation: 10 Points
- Tests (midterm- and end of term): 15 and 25 Points
- Tutorial project: 15 Points
- Cooperation: 10 Points
Minimum requirements and assessment criteria
The course partially covers theory of the three topics mentioned in content, followed by examples and calculations.
The tutorial will be dedicated to empirical project (planning, data collection,
analysis with statistical software, report).
The tutorial will be dedicated to empirical project (planning, data collection,
analysis with statistical software, report).
Examination topics
Reading list
Brannath/Futschik/Krall: Statistik im Studium der Wirtschaftswissenschaften: Eine Einführung anhand von Beispielen.
Association in the course directory
Last modified: Mo 07.09.2020 15:29
Chapter 7 Simple regression
Chapter 8 Multiple regression
Chapter 9 Analysis of variance