Introduction to Statistics
Overall Course Objectives
To give the participants an introduction to statistical methods and applications, and to provide them with an understanding of random variation and of the use of statistical models. Important statistical principles for collection and analysis of data are introduced, and methods for model choice, estimation, testing and model verification are presented. The participants learn to handle a number of elementary problems which occur frequently in engineering practice and are thus enabled to critically assess statistical (empirical) investigations and references.
See course description in Danish
Learning Objectives
- Estimate and interpret simple summary statistics, such as mean, standard deviation, variance, median and quartiles as well as correlation
- Apply simple graphical techniques, including histograms, qq-normal plots, and box plots
- Identify and describe probability distributions, including Poisson, binomial, exponential and the normal distribution using Python
- Compare different statistical methods
- Apply and interpret important statistical concepts, such as the formulation of models, parameter estimation, construction of confidence intervals and hypothesis testing
- Apply and interpret simulation based statistical methods
- Apply and interpret simple statistical methods within one- and two sample situations and for count data
- Apply and interpret simple statistical methods within simple and multiple linear regression and analysis of variance
- Use Python and interpret its output
- Interpret power considerations and perform sample size calculations in different settings using Python
- Debate and criticize empirically based information
Course Content
Simple methods for graphical and tabular assessments of collected or measured data: empirical distributions, histogram, normal probability plot, box plot. Model formulation. Model control: control of distribution function. Application of especially Poisson-, binomial-, exponential- and normal distribution. Estimation and test of parameters and construction of confidence intervals in frequently occuring situations (e.g. means, variances, proportions). Regression analysis with one independent variable and introduction to the analysis of variance and to the analysis of contingency tables, estimation theory and simulation based methods.
Recommended prerequisites
01002/01005/01901, At the latest at the same time.
Teaching Method
Lectures, group exercises, and projects.
Faculty
Remarks
The course is a general methodological course aimed at all engineering students. The course is offered in both Danish and English in both semesters. Lectures are given in Danish in spring semesters and in English in fall semesters. Both Danish and English web-based lectures (video podcasts) are available online in both versions. All material is available in English. Some material is available in Danish as well as English. The exam is given in Danish as well as English.