M&S 3 2018-2019

1. Big Data

1.1. Machine Learning

1.2. Data preparation

2. Markov Models

3. Data Visualization

3.1. Dashboarding

3.2. Interpretation of graphs/figures

3.3. Choosing the right type of graph to present numbers

4. Pricing Models

5. Data Analysis

5.1. Pivot tables in Excel

5.2. Basic descriptive statistics in SPSS

6. Mathematical Models

6.1. Logistic Regression

6.2. Cluster Analysis

6.3. Multinomial Logit

6.4. Lineair regression

6.5. Decision tree

7. Game Theory

8. Markov Models

9. Critical Thinking

9.1. Example misinterpretations statistics

9.2. Find the "mistake" in one of the lectures, win a price