Statistics and Probability (4cr)

Code: 5000BL67-3010

General information

Enrollment: 30.05.2024 - 15.09.2024; Registration for the implementation has ended.

Timing: 02.09.2024 - 18.12.2024; Implementation has ended.

Number of ECTS credits allocated: 4 cr

Local portion: 4 cr

Mode of delivery: Contact learning

Unit: Engineering and Business

Teaching languages: Finnish

Seats: 0 - 160

Degree programmes: Degree Programme in Information and Communication Technology

Groups: PTIVIS22T
Data Networks and Cybersecurity; PTIVIS22P
Game and Interactive Technologies; PTIVIS22S
Embedded Software and IoT; PTIVIS22H
Health Technology; PTIVIS22O
Software Engineering and Project Management; PTIVIS22I
Data Engineering and AI

Course: 5000BL67

Unfortunately, no reservations were found for the realization Statistics and Probability 5000BL67-3010. It's possible that the reservations have not yet been published or that the realization is intended to be completed independently.

Evaluation scale

H-5

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

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

Qualifications

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