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
