Intendierte Lernergebnisse
More and more data is becoming available in all areas of Business and Economics; one of its use-cases is to build and back hypotheses such as purchase decisions by customers. Transforming data into scientific theories requires tools which are known as statistical methods."Methodology 2: Statistics" aims at providing a fundamental knowledge about these tools by analyzing univariate and multivariate data sets. Examples are- descriptive statistics- estimation, prediction, and testing of proportions and means- analysis of variance- contingency tables- linear regressionThe lecture is accompanied by a KS with the same name, in which exercises and case studies will be solved by the students using the statistical software R.
Lehrmethodik
Lectures with active and passive parts, accompanied by eLearning-material. Individual practice through exercises, case studies, and quizzes.
Inhalt/e
- data, variables, frequencies- descriptive statistics- estimating, predicting, and testing of proportions- estimating, predicting, and testing of means- comparison of means- analysis of variance (ANOVA)- contingency tables and chi-square-test- linear regression
Erwartete Vorkenntnisse
basic mathematical and statistical knowledge at high-school level, in particular:- basic arithmetic- elementary probability calculus and probability distributions (binomial and normal distribution)- successful completion of "Methodology 1: Mathematics" highly recommended
Curriculare Anmeldevoraussetzungen
Please combine with "KS Methodology 2: Statistics"