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Tilastotieteen perusteet (3 cr)

Code: HTLZ1001-3001

General information


Enrollment

04.01.2021 - 10.01.2021

Timing

11.01.2021 - 21.05.2021

Number of ECTS credits allocated

3 op

Virtual portion

3 op

Mode of delivery

Online learning

Unit

Liiketoimintayksikkö

Teaching languages

  • Finnish

Seats

0 - 40

Degree programmes

  • Liiketalous (AMK)

Teachers

  • Heli Kauppinen

Groups

  • HTL19IY
    Liiketalous

Objective

The student understands the meaning of quantitative methods in work life.

The student understands the basic terminology in data collection, different data sets and variables.

The student knows the statistical aspects of preparing a questionnaire.

The student can calculate the descriptive statistics, and knows the basics of data tables and visualization.

The student knows possibilities of MS Excel in statistical analysis, and possibly another statistical program.

Content

1.Different types of data: data gathering and good questionnaire
2.Statistics and decision making
3.Tables
4.Basics of graphical presentation
5.Descriptive statistics and correlation
6.Simple statistical analyses: dependency and time series

Location and time

Etäohjaukset viikoittain Zoomissa.

Oppimateriaali ja suositeltava kirjallisuus

Kimmo Vehkalahti (2014): Kyselytutkimuksen mittarit ja menetelmät. Finn Lectura.

Leila Karjalainen (2015): Tilastotieteen perusteet. Pii-kirjat.

Kaikki kurssimateriaali ja harjoitustehtävät ovat ladattavissa Moodlesta. (https://moodle.jamk.fi)

Teaching methods

Kurssilla opiskellaan itsenäisesti viikon materiaali ja sen pohjalta tehdään tehtävät. Tehtäviin saa tarvittaessa apua Moodlessa ja viikoittain järjestettävässä etäohjauksessa.

Exam schedules

Tentit 12.4. ja 19.4. alkavilla viikoilla.

Student workload

Opintojakso suoritetaan harjoitustehtävien ja verkossa tehtävän loppukokeen avulla.

Content scheduling

Opintojakso on jaksotettu viikkoihin, joilla on oma teemansa.

Opintojakso koostuu seuraavista teemoista.
1. Erilaiset aineistot ja tutkimukset; datan kerääminen (viikko 2)
2. Aineiston tiivistäminen taulukoksi (viikot 3 ja 4)
3. Graafisen esittämisen perusteet (viikot 5 ja 6)
4. Tunnuslukuja (viikko 7)
5. Riippuvuus ja korrelaatio, hajontakuvio (viikko 8)
6. Riippuvuuden mallintaminen (viikko 9)
7. Aikasarjat (viikko 10)

Evaluation scale

0-5

Arviointikriteerit, tyydyttävä (1-2)

5 (excellent) : The student knows excellently the terminology in data collection, different data sets and variables. The student knows the basics of how to prepare a good questionnaire. The student can independently calculate and interpret descriptive statistics, and is able to make quality tables and visualize data. The student can utilize statistical methods in research and decision-making.
4 (very good) : The student knows very well the terminology in data collection, different data sets and variables. The student knows very well the basics of how to prepare a good questionnaire. The student can independently calculate and interpret descriptive statistics, and is able to make quality tables and visualize data. The student can utilize statistical methods in research and decision-making.
3 (good): The student knows well the terminology in data collection, different data sets and variables. The student knows well the basics of how to prepare a good questionnaire. The student can calculate and interpret descriptive statistics, and is able to make quality tables and visualize data. The student knows basics of how to utilize statistical methods in research and decision-making.
2 (satisfactory): The student knows some of the terminology in data collection, different data sets and variables. The student knows at satisfactory level the basics of how to prepare a good questionnaire. The student can calculate and interpret descriptive statistics, and is able to make quality tables and visualize data when guided. The student knows basics of how how to statistical methods in research and decision-making.
1 (poor): The student knows some of the terminology in data collection, different data sets and variables. The student knows at poor level the basics of how to prepare a good questionnaire. The student can calculate and interpret descriptive statistics, and is able to make quality tables and visualize data when guided. The student knows the importance of statistical methods in research and decision-making.
0 (fail): The student does not know the terminology in data collection, different data sets and variables. The student does not know the basics of how to prepare a good questionnaire. The student can not calculate and interpret descriptive statistics, and is not able to make quality tables and visualize data. The student does not know the importance of statistical methods in research and decision-making.

Arviointikriteerit, hyvä (3-4)

3 (good): The student knows well the terminology in data collection, different data sets and variables. The student knows well the basics of how to prepare a good questionnaire. The student can calculate and interpret descriptive statistics, and is able to make quality tables and visualize data. The student knows basics of how to utilize statistical methods in research and decision-making.

4 (very good) : The student knows very well the terminology in data collection, different data sets and variables. The student knows very well the basics of how to prepare a good questionnaire. The student can independently calculate and interpret descriptive statistics, and is able to make quality tables and visualize data. The student can utilize statistical methods in research and decision-making.

Assessment criteria, excellent (5)

5 (excellent) : The student knows excellently the terminology in data collection, different data sets and variables. The student knows the basics of how to prepare a good questionnaire. The student can independently calculate and interpret descriptive statistics, and is able to make quality tables and visualize data. The student can utilize statistical methods in research and decision-making.

Qualifications

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