Syllabus

LEARNING OUTCOMES

Students learn
- statistical modeling
- to understand how to analyze time series data and make forecasts in economics and business
- to design statistical research.

Credits: 6

Schedule: 01.03.2022 - 14.04.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Tomi Seppälä, Hannu Kahra

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

• valid for whole curriculum period:

  Topics in linear models and time series analysis: special estimation methods of regression models, ARMA and ARIMA models, forecasting, stationarity, integrated series, cointegration, ARCH and GARCH models, multivariate models, panel data

Assessment Methods and Criteria

• valid for whole curriculum period:

  NOTE! Students must pass a preliminary assignment in order to be able to attend the course. More information will be given on the MyCourses page of the course closer to the begin of the registration.

  exam
  assignments

Workload

• valid for whole curriculum period:

  Contact teaching
  Independent work 
  Exam 
  
  

DETAILS

Substitutes for Courses

• valid for whole curriculum period:

  Substitutes for Courses

Prerequisites

• valid for whole curriculum period:

  Prerequisites

FURTHER INFORMATION

Further Information

• valid for whole curriculum period:

  Teaching Language : English

  Teaching Period : 2022-2023 No teaching
  2023-2024 No teaching

Description