Statistics (3cr)
Code: 6M00DQ20-3002
General information
- Enrolment period
- 02.12.2020 - 31.03.2021
- Registration for the implementation has ended.
- Timing
- 08.03.2021 - 07.05.2021
- Implementation has ended.
- Credits
- 3 cr
- Mode of delivery
- Contact learning
- Campus
- TAMK Main Campus
- Teaching languages
- Finnish
- Degree programmes
- Degree Programme in Forestry
Objectives (course unit)
The student
- is able to use a computer to calculate basic statistical values
- is able to illustrate statistical data with suitable graphs.
- is able to interpret material using graphs and key values
- knows the basics of regression and correlation.
- is able to calculate the confidence interval of the sample and is able to use it for example hypothesis testing
- can calculate probabilities both theoretically and by computer simulating.
Content (course unit)
The concept of probability, the most common distributions, eg. normal, binomial, t and poisson distribution. Principles of statistical testing, processing of measurement data on a computer and graphical representation of it.
Use and importance of key statistical indicators. Use of regression techniques in modeling and predicting measurements.
Assessment criteria, satisfactory (1-2) (course unit)
The student understands the difference between the population and the sample. The student is able to calculate the mean, dispersion and position numbers from the sample. The student is able to design simple experimental designs for statistical research and illustrates the results both graphically and numerically. The student understands the basics of distributions.
Assessment criteria, good (3-4) (course unit)
In addition to the before mentioned, the student is able to apply statistical thinking in handling different research settings and measurement sets. The student masters the basics of statistical reasoning when processing different sized samples. The student understands the importance of the results of regression analysis.
Assessment criteria, excellent (5) (course unit)
In addition to the before mentioned, the student has a comprehensive understanding of the course topics and their use in problem solving as well as the ability to present and justify logically selected solutions.
Location and time
Ajat (ja paikat) on kerrottu TuniMoodlessa.
Exam schedules
Tentti pidetään 10.05.2021 klo 10.15-13.00 luokassa.
Uusintatentit 19.5.2021 ja 09.06.2021
Assessment methods and criteria
Arvointi perustuu kurssin lopuksi pidettävään tenttiin. Arvosana määräytyy maksimipistemäärästä saatujen pisteden perusteella seuraavasti:
40 % -> arvosana 1
52,5 % -> arvosana 2
65 % -> arvosana 3
77,5 % -> arvosana 4
90 % -> arvosana 5
Opiskelijalla on mahdollisuus saada lisäpisteitä tekemällä ja palauttamalla kotitehtäviä viikoittain Moodlessa oleviin palatuskansioihin.
Lisäpisteitä saa seuraavasti:
25 % -> 1 lisäpiste
50 % -> 2 lisäpistettä
75 % -> 3 lisäpistettä
Huom! Lisäpisteet otetaan huomioon vain, jos opiskelija saa vähintään 40 % kokeen maksimipisteistä koekysymysten perusteella.
Assessment scale
0-5
Teaching methods
Etäopetus, nauhoitetut luennot, videot, kotitehtävät, tentti
Learning materials
Opettajan tekemää oppimateriaalia julkaistaan TuniMoodlessa. Oppikirja: Martti Holopainen - Pekka Pulkkinen: Tilastolliset menetelmät + Antti Majaniemen moniste (jälkimmäinen TuniMoodlessa).
Student workload
Etäopetusta 9 * 3 tuntia + 3 tunnin koe. Loput 81 h - 30 h = 51 tuntia opiskelijan omaa opetuksen ulkopuolista työtä.