Syllabus

Data Analysis and Statistics I

Code
ST1013
Points
7.5 ECTS-credits
Level
First Cycle Level 1
School
School of Information and Engineering
Subject field
Statistics (STA)
Group of Subjects
Statistics
Disciplinary Domain
Natural Science, 100%
This course can be included in the following main field(s) of study
Microdata Analysis1
Progression indicator within (each) main field of study
1G1N
Approved
Approved by the Faculty School of Information and Engineering, 14 December 2010.
This syllabus is valid from 15 December 2010.
Revised
Revised, 13 February 2013.
Revision is valid from 13 February 2013.
Download as pdf To course page

Learning Outcomes

At the end of the course students will be able to:

· summarize and interpret data with the use of descriptive statistics.
· interpret print-outs from simple linear regression.
· perform statistical inference.
· calculate probabilities with the use of the normal model.
· calculate expected values from random variables and to calculate probabilities with the use of addition- and multiplication rule.
· describe the principles of data collection by experiment and sampling.
· use statistical software in the frame of the course content.
· use the terminology in the framework for this course.

Course Content

The course covers the sources of official data as well as descriptive statistics and how to draw conclusions about the distribution of data using graphs. Besides that, data tabulation and the principles of drawing conclusions from two-way tables are treated. 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, measures of correlation, and two-way tables. The concepts of random event, probability, random variable, and the basic rules of probability are also covered. Covered in the course are also 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 use of statistical software is also included in the course contents.

Assessment

Written exam.

Forms of Study

Lectures/tutorials and computation labs form the basis of study

Grades

The Swedish grades U–VG.

Prerequisites

  • General entry requirements and Mathematics 2a or 2b or 2c, Physics 1a or 1b1+1b2

Other Information

The practical work may consider the students intended major.
A maximum of five examinations.
Examination scores are gained via tests and assignments as well as from the final exam. The student keeps the scores from test and assignments up to and including the first re-sit.
The course cannot be included in a degree together with the following courses:
Statistics Data Analysis and Probability for Economists - Undergraduate level 1. 15 credits-credits.
Statistics in Computer Science and IT - Undergraduate Level. 7,5 credits.

Qualification course in Data Analysis and Statistics for masterprogram in Business Intelligence - Undergraduate level 1. 7,5 credits.

Literature

  • De V. R. D., Velleman, P. F., Bock, D. E.. (2008) Stats : data and models. 2 ed. Boston : Pearson/Addison-Wesley. (869 p). ISBN 978-0-321-46855-0
    Note: Latest edition
    Reading instructions: Valda delar ca 400 sid.