Studieguide

Statistics and probability MAP22MT04-3001 04.03.2023-01.05.2023 3 credits (PRE21D-V) +-
Competence objectives of the study unit

- The student knows basic probability theory and can use different statistical distributions to solve problems
- The student can statistically analyze and present a data material in a relevant way
- The student can apply regression models to different data sets

Prerequisites

Functions an equations 1,
Geometry and equations,
Functions an equations 2
Derivator and integrals

Content of the study unit

Statistics
- descriptive statistics
- probability theory
- discrete and continuous distributions
- Excel as a tool for analyzing data

Curve fitting and regression
- matrix calculus and linear algebra
- linear regression - least squares method
- linearization
- mathematical software (Excel, Mathcad or other program) to build regression models

Assessment criteria

Failed (0)

Uppfyller ej kraven för vitsord 1. (not translated)

Assessment criteria – satisfactory (1-2)

Statistics and computational skills: Know the basics of statistics and can perform simple calculations
Curve fitting and regression: Know the basics of regression analysis
Mathematics software: Can use a software to solve basic problems

Assessment criteria – good (3-4)

Statistics and calculation skills: Is familiar with statistics and can perform relevant calculations
Curve fitting and regression: Is familiar with the concept of regression and can perform curve fitting of technical models
Mathematics software: Can use a software to solve applied problems

Assessment criteria – excellent (5)

Statistics and computational skills: Is well versed in statistics and can perform more advanced statistical calculations.
Curve fitting and regression: Can independently perform curve fitting and regression models in advanced technical problems
Mathematics software: Can use a software to solve advanced problems in mechanical engineering

Name of lecturer(s)

Roger Nylund

Learning material

- Teorikompendium och övningsuppgifter
- Relevanta läroböcker som rekommenderas vid kursstart (not translated)

Learning methods

Föreläsningar, räkneövningar och datorövningar (not translated)

Objects, timing and methods of assessment

Tentamen (max 30 p)
Vitsordsskala:
10 p 1
14 p 2
18 p 3
22 p 4
26 p 5

Slutlig bedömning diskuteras och bestäms vid kursstart i samarbete med studeranden. (not translated)

Teaching language

Swedish

Timing

04.03.2023 - 01.05.2023

Enrollment date range

01.12.2022 - 03.03.2023
Group(s)
- PRE21D-V
Responsible unit

Faculty of Technology and Seafaring

Teachers and responsibilities

Tom Lillhonga

Degree Programme(s)

Degree Programme in Mechanical and Production Engineering

Campus

Vasa, Wolffskavägen 33

RDI share

0.00 credits

Share of online studies

0.00 credits

Assessment scale

H-5

Practical training and working life co-operation

Föredrag av gäster från näringslivet. (not translated)

Exam dates and retake possibilities

Presenteras på kursens Moodle-sida (not translated)

Timing and attendance

Period 4, våren 2023 (not translated)

Content scheduling

Närstudier 36 timmar.
Studerandens arbete på egen tid: i medeltal 45 timmar (not translated)

Assessment criteria

Failed (0)

Uppfyller ej kraven för vitsord 1. (not translated)

Assessment criteria – satisfactory (1-2)

Statistik och beräkningskompetenser: Känner till grunderna i statistik och kan utföra enkla beräkningar
Beräkningsprogram: Kan använda ett beräkningsprogram för lösning av grundläggande problem (not translated)

Assessment criteria – good (3-4)

Statistik och beräkningskompetenser: Är insatt i statistik och kan utföra relevanta beräkningar
Beräkningsprogram: Kan använda ett beräkningsprogram för lösning av tillämpade problem (not translated)

Assessment criteria – excellent (5)

Statistik och beräkningskompetenser: Är väl insatt i statistik och kan utföra mer avancerade statistiska kalkyler.
Beräkningsprogram: Kan använda fler än ett beräkningsprogram för lösning av problem inom produktionsteknik (not translated)