Statistics for social sciences

- Descriptive statistics: Location measures, variance measures
- Probability and combinatorics: The concept of probability, probability models, probability calculations, conditional probability
- Discrete stochastic variables: Calculation of expectation and variance, binomial distribution, hypergeometric distribution, poisson distribution
- Continuous stochastic variables: Normal distribution/normal approximation, t-distribution
- Estimation: Point estimation and interval estimation
- Hypothesis testing
- Correlation
- Linear regression analysis
- Use of spreadsheets

Learning outcome - Knowledge:
The candidate should
- have the necessary methodical foundation in probability calculus and statistics for other subject in the study programme.
- be able to connect the use of statistical methods to problems related to the economics-administrative area. 

Learning outcome - Skills:
The candidate should
- be able to present and interpret statistical data using central and dispersion measures, frequency distributions and graphical methods.
- master basic probability, including probability models, combinatorics, sample models, conditional probabilities, the law of total probability, Bayes law and independence.
- be able to analyze probability distributions and calculate expectation and variance of a random variable, extend this to linear combinations of random variables.
- understand the simultaneous probability distributions, including the calculation of expectation, variance and covariance.
- be able to select probability models and use discrete and continuous probability distributions, including the binomial distribution, hypergeometric distribution, Poisson distribution, normal distribution/central limit theorem and t-distribution.
- be able to estimate the unknown parameters, both point estimation and interval estimation.
- master hypothesis testing in the measurement model and the binomial model and evaluate different testing methods, interpret the significance level, significance probability and power of tests.
- be able to apply and interpret the regression analysis, both the estimation and hypothesis testing of regression coefficients, and calculate and interpret the correlation coefficient.
- be able to conduct chi-square tests, both model testing and test of independence.

Learning outcome - Competence:
The candidate should
- be able to use statistics to communicate about economic relationships.
- be able to use statistics to express and analyze economic relationships.
- have a statistical understanding that can form the basis for further studies and lifelong learning.

Pedagogical methods:
Lectures 

Mandatory requirements:
Compulsory excersises must be completed to gain admission to the exam.