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

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)