Topics Statistics are in English only.

They cover a number of important topics with clear explanations and examples. The topics can be used as a crash course in Statistics.

They are based on Powerpoint slides that were used during a master program at Erasmus University Rotterdam for the course Statistics. The book used for this course is *Statistics for Management and Economics* by Gerald Keller (Cengage Learning).

Some examples or assignments require the use of Excel.

**Introduction****Basics**- Data types in Statistics
- Numerical descriptive statistics
- Measures of central location (mean, median, mode)
- Measures of variability (variance, standard deviation, range)
- Measures of relative standing (percentiles, quartiles, IQR, boxplot, histogram)
- Measures of linear relationship (covariance, coefficient of correlation, regression)

**Discrete and continuous distributions**- Probability distributions
- Discrete probability distributions
- Distribution of households
- Population mean
*E(X)* - Population variance
*V(X)* - Covariance of two discrete variables
- Laws of
*E(X)*and*V(X)* - Laws about a linear sum
- Coefficient of correlation
- Binomial distribution
- Continuous random variables
- Probability density functions
- The normal density function
- Standard normal distribution
- Other continuous distributions

- Sampling
- Sampling distributions
- Some mathematics
- Central Limit Theorem
- Verify Central Limit Theorem
- Using the standard normal distribution
- The difference of two means
- Normal approximation of Binomial
- Distribution of a sample proportion

**Estimation**- Two types of estimators

- Unbiased estimators
- Consistency
- Estimating the mean (known population variance)
- Interpreting the interval estimator
- Interval bound
- Characteristics
- Selecting the sample size
- Estimating the mean (unknown population variance)

**Hypothesis testing (one population)**- The procedure

- Strategies to perform tests
- The
*Z*test

- Hypothesis testing, unknown population variance
- The
*t*test - Inference about the population variance
- Confidence interval of the variance

- Inference about proportions

**Hypothesis testing (two or more populations)**- Comparing two population means
- Independent populations
- Matched pairs
- Equal, (un)known population means
- Inference about variances
- Testing the population variances
- Comparing two population means

- Difference between two proportions
- Analysis Of Variance: ANOVA

**Chi-squared tests and coefficient of correlation**- The Goodness-of-fit test
- Market shares companies A and B
- Contingency (cross) tables
- Coefficient of correlation

**Linear regression**- Deterministic and probabilistic models
- How does linear regression work?
- Now the general formula for this case

**Regression analysis**- Simple linear regression models
- Requirements
- Testing the slope
- Testing the coefficient of correlation
- Coefficient of determination

- Homo- and heteroscedasticity

**Multiple regression**- Testing the individual coefficients
- Multicollinearity
- Nonlinear models
- Two predictor variables (linear and quadratic)

- Nominal variables

**Time series-seasons-forecasting**- Time series components

- Trend and seasonal effects
- Seasonal analysis

- Autoregressive models