DAT110 Introduction to Data Analysis and Visualisation

Credits (ECTS):10

Course responsible:Kristin Tøndel, Eirik Valseth

Campus / Online:Taught campus Ås

Teaching language:Norsk

Course frequency:Annually

Nominal workload:Lectures 78 hours, exercises 26 hours, preparation for presentations 96 hours, colloquia and self study 50 hours.

Teaching and exam period:This course starts in Spring parallel. This course has teaching/evaluation in the Spring parallel.

About this course

Introduction to elementary data analysis based on modern tools

- Datatypes and loading of data from various file formats.

- Visualization and explorative analysis for identification of structure and trends (histograms, scatterplots, box-plots etc.).

- Some simple statistics (mean, median, variance etc.).

- Correlation and covariance (of single variables and matrix data).

- Crosstables.

- Elementary normal distribution theory, normalizing transformations and testing for normality.

- Geometric distributions, binomial distributions, Poisson-distributions.

- Inference (parametrical and non-parametrical for investigation of one and two samples) and simple analysis of variance.

- Least squares modelling (linear and polynomial fit).

- Logistic regression (classification with two groups).

- Smoothing of time-dependent data.

- Cluster analysis (k-means, hierarchical clustering etc.).

Learning outcome

Skills and insight into basic data analysis techniques based on modern data collection. In addition to these, focus will be give to work relevant soft skill such as team work and presentation skills.

The student will learn to choose appropriate methods for

1) Explorative data analysis (plotting/visualisation and descriptive statistics),

2) Visualisation,

3) Inference,

4) Modelling and prediction with continous and categorical responses (regression and classification) and validation of predictive models.

5) Introduction to cluster analysis and smoothing of time series data.

  • Lectures, and group work with manual- and computer lab exercises (assistant teachers and course responsible will be present at the groups). 4 hours mandatory attendance per week. Student-active learning is used.
  • Guidance during tutoring sessions.
  • MATH111 Calculus 1

    INF120 Programming and Data Processing

  • Written examination: 3.5 hours. A-F.

  • The external and internal examiner jointly prepare the exam questions and the correction manual. The external examiner reviews the internal examiner's examination results by correcting a random sample of candidate's exams as a calibration according to the Department's guidelines for examination markings.
  • Mandatory exercises (hand-ins) and 2 double lectures mandatory attendance per week. Requirements for approval of mandatory activity will be announced at the beginning of the term.
  • Lectures: 2 hours per week. Lectures/exercises: 2 hours per week. Exercises: 2 hours per week.
  • 5 credits with STAT100

    10 credits with MATH-INF110

  • Special requirements in Science