Statistics (3 cr)

Objectives (course unit)

Student is able to
- construct graphical presentation for statistical data.
- calculate basic statistical measures with computer.
- interpret data using statistical measures and graphs.
- understand basics of combinatorics.
- calculate probabilities.
- construct a confidence interval and perform a hypothesis test.
- understand the concepts of regression and correlation.

Content (course unit)

Probability, combinatorics, statistical measures, distributions (normal, binomial, t, Poisson), confidence interval, hypothesis testing, use of statistical computer program, regression

Prerequisites (course unit)

Basic use of Excel, Functions and matrices and Integral Calculus, or similar skills

Assessment criteria, satisfactory (1-2) (course unit)

Student understands the difference between population and sample. Student is able to calculate measures of central tendency and variation. He/she knows the basic elements of research methods and is able to present data in charts and tables. Student understands the basic concepts of distributions. He/she is able to solve simple applications that are similar to the problems solved during the course. Justification of solutions and the usage of mathematical concepts may still be somewhat vague.

Assessment criteria, good (3-4) (course unit)

In addition, student is able to apply statistics thinking when handling data from different kind of research methods. Student knows basic elements of decision making with different size of samples. He/she understands meaning of results of regression analysis. Student is able to solve the given exercises independently and helps other students in the group.

Assessment criteria, excellent (5) (course unit)

In addition, student has an overall understanding of course topics. He/she can solve more demanding engineering problems and has the ability to present and justify the chosen methods of solution. Statistical notations and concepts are used precisely. Student is motivated and committed to help the group to manage the course.

Location and time

Perjantaisin klo 11.15-14.00 aikavälillä 23.10.-18.12.2020.

Exam schedules

Tentti pidetään 18.12.2020 klo 11.15-14.00 luokassa B4-27.

Evaluation 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

Student workload

Etäopetusta 8 * 3 tuntia + 3 tunnin koe. Loput 81 h -27 h = 54 tuntia opiskelijan omaa opetuksen ulkopuolista työtä.

Content scheduling

Sisällön jaksotus TuniMoodlessa