Course content

• Descriptive statistics: Location measures, variance measures
• Probability calculations and combinatorics: The concept of probability, probability models, conditional probability
• Discrete stochastic variables: Calculation of expectation/variance/covariance, binomial distribution, hypergeometric distribution, poisson distribution
• Continuous stochastic variables: Normal distribution, exponential distribution, approximations to the normal distribution, linear combinations
• Estimation: Point estimation, interval estimation, properties of estimators, valuation of sample size
• Hypothesis testing: Hypothesis testing in measurement models (z-test and t-tests), hypothesis testing using normal approximation, chi-square tests, p-value, test strength.
• Linear correlation and regression: Least squares method, intervall estimation, hypothesis testing, prediction.
• Use of computer tools

Learning outcome

Knowledge. The candidate should

• have the necessary methodical foundation in probability calculus and statistics for other subjects in the study programme.
• be able to connect the use of statistical methods to problems related to the economics-administrative area.

Skills. The candidate should

• have a basic understanding of the probability concept, be able to do probability calculations, and calculations using probability distributions.
• be able to estimate, and calculate confidence intervals for, unknown parameters.
• be able to choose and use the appropriate hypothesis test.
• be able to use and interpret linear regression models.

Competence. The candidate should

• be able to use statistics to express, analyze, and communicate economic relationships.
• have a statistical understanding that can form the basis for further studies and lifelong learning.

Learning methods and activities

Lectures and exercises. Assignments must be passed to gain entry to the exam. Lectures are streamed from Gjøvik, and will also be available in the learning platform in the future. Guidance takes place both through the use of real-time technology (Collaborate) and through the use of Forums in the learning platform.

Compulsory assignments

• Exercises

Specific conditions

Recommended previous knowledge

An introductory course in mathematics.

Required previous knowledge

None.

Course materials

To be announced at the start of the semester.

Credit reductions