BØA115 Statistics for Economists

Contents and structure

• The course should provide the necessary methodological foundation in probability theory and statistics for other courses, in particular for the course Research Methods in the Social Sciences. It is a key goal that the course should provide analytical insight and that emphasis is placed on examples of statistical methods used on a wide range of issues related to business and administration.

Content

• Presentation and interpretation of statistical data using measures of central tendency and measures of spread, frequency distributions and graphical methods.
• Basic probability theory, including probability distributions, combinatorics, sampling distribution, conditional probabilities, the law of total probability, Bayes' theorem and independence, etc.
• Probability distributions. Calculating expected value and variance of a random variable, and of linear combinations of random variables.
• Joint probability distribution, including calculating expected values, variance, and covariance.
• Probability distributions. Discrete and continuous probability distributions, including binomial distribution, hypergeometric distribution, normal distribution/approximately normal distributions, and t-distribution etc.
• Estimation of unknown parameters, both a point estimate and confidence interval
• Hypothesis testing in a sampling model and in a binomial model. Assessment of different test methods. Interpretation of significance level, p-value, and the power of a test.
• Analysis of covariance between two random variables, both by regression analysis and by interpretation of the correlation coefficient, and by estimation and hypothesis testing of the regression coefficient.
• Analysis of the differences between groups, including hypothesis testing.
• Chi-square tests (model testing and independence testing)
• Use of statistical software, such as Excel, to process data and perform quantitative analysis

Learning Outcome

Knowledge:

The student:

• has knowledge of the basic methods of data collection as well as the concepts of population and sample. Knows the implications of these choices for the statistical inference.
• has knowledge of probability theory, combinatorics, and applications of these. Including conditional and unconditional probabilities as well as dependent and independent events.
• knows what random variables, expected values and variance are. Can interpret descriptive statistics.
• understands the concepts of correlation and causality
• knows different probability distributions
• knows what the central limit theorem is and what its significance is.
• can interpret a hypothesis test and a confidence interval
• can interpret results from a regression analysis

Skill:

The student:

• can use basic parametric and non-parametric methods to analyze and describe data.
• can calculate probabilities using probability theory.
• can calculate joint probabilities and covariance.
• can calculate different types of confidence intervals for different types of data.
• can perform hypothesis tests on different types of data.
• can perform simple linear regression, perform hypothesis tests, and calculate prediction intervals.
• can perform simple analysis tasks in statistical software, such as in Excel

General expertise: 

The student:

• understands parametric and non-parametric statistics
• understands the importance of inference, correlation, and causality
• can read scientific articles, where the methodology is basic statistics
• understands the strengths and weaknesses of statistical analysis
• can use the knowledge from the course in other courses

Entry requirements

None

Recommended previous knowledge

Good prerequisite knowledge in mathematics is recommended.

Teaching methods

Lectures, exercise classes and obligatory assignments. 

Compulsory learning activities

4 obligatory assignments which must be graded as passed before the exam can be taken. The assignments might possibly be held on a digital platform. 

Assessment

Written exam, 4 hours. The exam might possibly be held on a digital platform.

Grades between A and F will be given, where F corresponds to fail. 

Examination support material

A sheet with mathematical formulas and statistical tables will be attached to the exam.

All calculators are allowed, with the following exceptions/limitations

- the calculator can not communicate

- the calculator can not handle symbolic mathematical expressions

- the calculator will not be connected to electricity

- the calculator can not make noise in the exam facilities

More about examination support material