First Cycle Level 1
School of Technology and Business Studies
This course can be included in the following main field(s) of study:
1. Microdata Analysis
Progression indicator within (each) main field of study:
Approved by the Faculty School of Technology and Business Studies, 26 October 2010.
This syllabus is valid from 26 October 2010.
Revised, 13 February 2013.
Revision is valid from 13 February 2013.
Upon completion of this course the student will:
- be able to summarize and interpret data with the use of descriptive statistics.
- apply basic knowledge about simple and multiple linear regression.
- be able to perfom statistical inference.
- be able to calculate probabilities with the use of the normal model.
- be able to calculate expected values from random variables and to calculate probabilities with the use of addition- and multiplication rule.
- know the principles of data collection by experiment and sampling.
- be able to identify and use statistical software in the frame of the course content.
- have knowledge about the terminology in the framework for this course.
The course covers the sources of official data as well as descriptive statistics and how to draw conclusions about the distribution of data by using graphs. Also data tabulation and the principles of drawing conclusions from two-way tables are dealt with. The course also covers how to summarize data using measures of center, spread and association and how to analyze data using normal distribution.
The principles of data collection by experiments and sampling are also covered in the course as well as how to analyze association between variables using scatter plot, simple linear regression and measures of correlation. The concepts of random event, probability, random variable and the basic rules of probability is also covered. The course also covers estimates of means and proportions and their sampling distributions as well as normal approximation and the central limit theorem. Estimates of differences between two proportions and two means and confidence intervals for mean, proportion and the difference between two proportions and between two means are covered, as well as how to draw conclusions based on confidence intervals. The student will independently identify and use statistical software for assignments.
Forms of Study
Webbased lectures and exercises form the basis of study.
GradesThe Swedish grades U - VG
The practical assignments can be adapted to fit the students intended major.
Students may do a maximum of five resits.
The course cannot be included in a degree together with the following courses:
Data Analysis and Statistics I - Undergraduate level. 7,5 credits.
Statistics in Computer Science and IT- Undergraduate Course. 7,5 credits
Statistics, Data Analysis and Probability for Economists - Undergraduate level 1. 15 credits.
- De V. R. D., Velleman, P. F., Bock, D. E.. (2008) Stats : data and models. 2 uppl. Boston : Pearson/Addison-Wesley. (869 s). ISBN 978-0-321-46855-0
Note: Latest edition
Reading instructions: Valda delar ca 400 sid.