040501 KU Data Analysis for Marketing Decisions (MA) (2016W)

In (international) marketing research, one needs profound knowhow on data analysis and statistics – more than one would expect! This course aims at familiarizing students with (a) the stages of the data analysis process, (b) key statistical methods, and (c) the software package IBM SPSS. A combination of lectures and hands-on exercises will prepare students for conducting their own projects in other marketing courses, their master thesis and/or their post-academic career.

The major topics covered in the course are:
Theoretical introduction to basic marketing research terms: data, variables, models, marketing research process, sample, population, sampling methods, measurement scales, etc.
Introduction and familiarization with the statistical software SPSS
Clearing and preparing data for further analysis
Descriptive statistics: central tendency, variability, skewness, kurtosis
Testing statistical assumptions: normality, homogeneity of variance, homoscedasticity, autocorrelation
Inferential statistics and hypothesis testing: parameter estimates, sampling error, confidence intervals, Type I and Type II errors, p-values, t-values
Performing comparisons: chi-square test, independent samples t-test, paired-sample t-tests, analysis of variance (one-way, factorial, repeated-measures)
Investigating relationships: bivariate correlation, ordinal correlation, partial correlation
Regression models: simple linear regression, multiple linear regression, logistic regression
Finding structures using Factor Analysis
Presenting, reporting and interpreting results
Identifying practical and theoretical implications drawn from statistical analyses

Sessions include theoretical background knowledge of the relevant analytical techniques combined with direct hands-on application of the techniques on real-life datasets using SPSS.

The course involves a combination of formal lectures and lab sessions. Formal lectures will provide background knowledge on the nature of data, hypotheses formulation and the selection of an appropriate statistical technique. The lab sessions will provide the opportunity to get familiar with SPSS and gain hands-on experience in conducting and interpreting analysis techniques. To consolidate the gained knowledge, students will execute two projects.