Study Guide

Objective

After completing the course the student can:
- calculate different mean and standard deviation figures for a given statistical data
- determine the regression line and correlation, and understand their significance
- identify and draw various statistical diagrams
- recognize the basic concepts of continuous and discrete probability distributions
- normalize a normally distributed variable and calculate the associated probabilities
- calculate confidence intervals and understand the significance of error in statistical mathematics
- determine p-value using the z-test and t-test of average
- construct contingency tables and apply the chi-square test
- utilize information technology in the processing and analysis of statistical data

Content

- mean and standard deviation figures
- diagrams and their differences
- regression, correlation
- basic definitions and formulas of probability
- discrete probability distribution, binomial distribution, Poisson distribution
- continuous probability distribution, normal distribution, normalization
- statistical testing, sampling, confidence interval
- z-test and t-test of average
- contingency tables and chi-square test

Materials

All course material and links to outside materials are on ITSlearning.

Teaching methods

Lectures, exercises, homework, guided practice, project work, independent study

Exam schedules

Part-exam 1 will take place on week 44.
Part-exam 2 will take place on week 50.

There will be an opportunity to retake both part-exams in January 2025.

International connections

During the course we will learn statistical and probability skills and knowledge fundamental for an ICT-engineer's profession. Various forms of technology are widely used in all topics and students are encouraged to learn more ways to use technology in solving problems within the course's topics. A lot of learning happens in class with the guidance of the teacher but independent study and homework is important as well.

Sustainable development aspects are considered during the course. Lecture material and homework feature examples about creating an ecologically sustainable and resilient society, and the impact of statistics in promoting sustainable development is discussed.

Completion alternatives

If a student wants to pass the course by taking only an exam, this needs to be agreed upon with the teacher.

Student workload

Contact hours: 28 h (lectures) + 24 h (homework classes) = 52 h
Exams: 4 h
Independent study (homework, exam preparation, extra task etc.): 74 h

Content scheduling

The course will begin on week 36 and end on week 50.

Topics:
- mean and standard deviation figures
- diagrams and their differences
- regression, correlation
- basic definitions and formulas of probability
- discrete probability distribution, binomial distribution, Poisson distribution
- continuous probability distribution, normal distribution, normalization
- statistical testing, sampling, confidence interval
- z-test and t-test of average
- contingency tables and chi-square test

Further information

It is possible to do an optional statistical project during the course which will give you an extra 2 credits, i.e. a total of 7 credits. This project will be about a topic of your own choosing (with the help of the teacher) and you are expected to use a wide range of statistical and/or probabilistic methods in it. You are expected to gather, process, present and analyse data and produce a report about it, to be submitted by the end of the course by an agreed upon deadline. It is expected that you devote approximately 30-50 hours of work into this. The report won't affect your course grade but, if it contains the required elements and is of an appropriate depth, you will get the 2 extra credits.

More detailed instructions and requirements as well as a template file can be found on ITS. Email the teacher before you start doing the project so that no two students come up with too similar topics.

Evaluation scale

H-5

Assessment methods and criteria

The assessment consists of:
- Two part-exams (2x50 p = 100 p). Part-exam 1 is on week 44, part-exam 2 on week 50.
- Homework (84 p)
- Attendance (6 p)
- Extra task (10 p)
Total: 200 p

To pass, the total points obtained must be at least 70, and at least 30 of them must come from the part-exams.

Attendance is taken at the start of each lecture, excluding the first one. At the end of the course, based on the number of attendances, you’ll receive the following number of points:
7: 1 p
8: 2 p
9: 3 p
10: 4 p
11: 5 p
12-13: 6 p

There are 12 topics, each has some homework questions on ITS and a set of homework questions to be submitted. Each topic's homework gives 7 p in total

The extra task is work up to 10 p and can be completed by the deadline set by the teacher. This task is about learning how to use some technology not covered during classes.

Grade boundaries:
0-69: FAIL
70-93: 1
94-117: 2
118-141: 3
142-165: 4
166-200: 5

Assessment criteria, fail (0)

Fewer than 70 points
and
fewer than 30 points from the part-exams

Assessment criteria, satisfactory (1-2)

70-93 points: 1
94-117 points: 2

And at least 30 points obtained from the part-exams

Assessment criteria, good (3-4)

118-141 points: 3
142-165 points: 4

And at least 30 points obtained from the part-exams

Assessment criteria, excellent (5)

166-200 points: 5

And at least 30 points obtained from the part-exams

Qualifications

Courses Engineering Precalculus, Calculus and Topics in Applied Mathematics
OR
equivalent skills