MLI36A020 - Introduction to Statistics, Lecture, 30.10.2023-17.11.2023

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Learning outcomes for this course, upon successful completion, include the ability to:  1) know and select a tool or measure appropriate to the task and to the measurement nature of the variables, 2) use basic descriptive statistics of central tendency and cross-tabulation to summarize data, 3) learn how to visually present data, such as graphing, table construction, and decision trees, 4) understand populations and sample sizes and their effect on statistical results, 5) use statistical estimation, correlation, and classical statistical tests for simple and multiple regression analyses, 6) understand the use of inferential statistics as a method of decision-making when faced with uncertainty, 7) apply hypothesis testing with confidence intervals for categorical and continuous variables, and 8) use data analysis software, such as the Excel data analysis tool pack, to analyze data and present visualizations of it.

Credits: 6

Schedule: 30.10.2023 - 17.11.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Roman Stepanov

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:

    In this course, the student is introduced to the subject of business statistics to explore quantitative analyses in business, the basic procedures in problem solving, and the sources and types of data used by business firms. Basic statistical analysis will be used by the student to summarize and describe numeric data and to perform inferential statistical analysis to test hypotheses. Emphasis will be placed on learning how to select the appropriate tool to solve problems associated with statistical uncertainty.

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Module 4
    2022-2023 Module 5
    2023-2024 Module 5
    2023-2024 Module 5

    Enrollment :

    The course is targeted only for the Mikkeli Campus students.

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