Datan analysointi (3 cr)
Code: TZLM7300-3004
General information
Enrollment
01.11.2022 - 05.01.2023
Timing
09.01.2023 - 19.05.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Online learning
Unit
Teknologiayksikkö
Campus
Pääkampus
Teaching languages
- Finnish
Seats
0 - 20
Degree programmes
- Logistiikka (AMK)
Teachers
- Ida Arhosalo
Teacher in charge
Ida Arhosalo
Groups
-
LOGRAKVERKKOLogistiikan ja rakentamisen verkko-opetus
Objective
Purpose
After the course you will understand how analysis of statistical data can help an engineer to make better business decisions.
Learning outcomes
You can analyze, visualize and interpret small and big data to draw conclusions and make forecasts using statistical methods.
Content
Descriptive, exploratory, and prescriptive statistics
Confidence interval estimation and hypotheses testing
Multi-variable regression models
Time series analysis, smoothing and forecasting methods
Big data analysis using a computer
Use of Excel and some machine learning software
Oppimateriaali ja suositeltava kirjallisuus
Morrison, S. J. (2009) Introduction to engineering statistics. Hoboken, NJ: Wiley
Hoerl, R & Snee, R. (2012) Statistical Thinking: Improving Business Performance. Hoboken, NJ: Wiley
Kelleher, Mac Namee & D'Arcy (2020) Fundamentals of Machine Learning for Predictive Data Analytics. Cambridge, MA: MIT Press
Other material accessible in Moodle
Teaching methods
In online learning the student works independently by familiarizing with the theory and putting the theory into practice by solving assignments using a computer.
Exam schedules
The date and execution of the exam will be announced in the beginning of the course.
Vaihtoehtoiset suoritustavat
The admission procedures are described in the degree rule and the study guide.
Student workload
Independent study about 20 hours
Learning tasks about 40 hours
Further information
The assessment is based on learning tasks and exams.
An equivalent course with contact lessons in English TZLM7300-3002 Data Analysis.
Evaluation scale
0-5
Arviointikriteerit, tyydyttävä (1-2)
Adequate 1
You have achieved the desired goals. You know a few of the concepts and methods and how to apply them in familiar situations but your reasoning is often deficient and you make mistakes in calculations.
Satisfactory 2
You have achieved the desired goals. You know many of the concepts and methods and how to apply them in familiar situations but your reasoning is sometimes deficient or you make mistakes in calculations.
Arviointikriteerit, hyvä (3-4)
Good 3
You have achieved the desired goals. You know most of the concepts and methods and how to apply them in familiar situations showing often the ability to reason completely and calculate flawlessly
Very good 4
You have achieved the desired goals. You know most of the concepts and methods and how to apply them in new situations showing in most cases the ability to reason completely and calculate flawlessly.
Assessment criteria, excellent (5)
Excellent 5
You have achieved the desired goals. You know all the concepts and methods and how to apply them in new situations showing always the ability to combine things, reason completely and calculate flawlessly.
Qualifications
You master basic statistics and related Excel functions.