Open University

Tampere

Introduction to Probability and Statistical Inference, Lectures

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Basic studies

Faculty of Information Technology and Communication Sciences

Technology and Natural Sciences

Apply for Open University studies by using the following links:<ul><li><a href="https://tau-avoin.ilmoittaudu.fi/lobby/?realization=J-otm-24d60af1-4dee-4ab9-b364-eea3668f3120_2023-tampere-MATHAPP210" target="_blank">MATH.APP.210 Introduction to Probability and Statistical Inference, lectures, Tampere</a></li></ul>You can find a link to the Open University Admissions service and application instructions on the <a href="https://www.tuni.fi/en/study-with-us/open-higher-education-studies/open-university/applying-open-university">Applying to Open University studies</a> page.Some of the studies require prior studies. For example, studying intermediate studies may require some completed basic studies. These are described on the Information about studies tab of the study unit under prior requirements.When you have been admitted to the studies, you must enrol separately via the Sisu information system for the implementation of the unit of study and, for example if set, for a practise group of your choice. You will receive instructions on how to do this by e-mail after you have confirmed your acceptance of the study place by paying the required fee.

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Hervanta Campus

Contact teaching

Look information at <a href="https://www.tuni.fi/en/study-with-us/open-higher-education-studies/open-university/applying-open-university">Applying to Open University studies</a>.

Rules and axioms of probability theory, the probability distribution of a discrete and continuous random variable, density and cumulative distribution function, expected value, variance, and standard deviation, uniform distributions, Bernoulli, binomial, and Poisson distributions, normal distribution, t-, F- and chi^2 distributions, joint probability distribution, covariance, correlation, random sample, sample statistic, and distribution of the statistic, point and confidence interval estimation, principles of hypotheses testing, estimation and testing under Bernoulli and normal distributions.

<h2>Common</h2><h3>Lecture: </h3>05.03.2024 12:00 - 14:00 06.03.2024 12:00 - 14:00 12.03.2024 12:00 - 14:00 13.03.2024 12:00 - 14:00 19.03.2024 12:00 - 14:00 20.03.2024 12:00 - 14:00 26.03.2024 12:00 - 14:00 03.04.2024 12:00 - 14:00 09.04.2024 12:00 - 14:00 10.04.2024 12:00 - 14:00 16.04.2024 12:00 - 14:00 17.04.2024 12:00 - 14:00 23.04.2024 12:00 - 14:00 24.04.2024 12:00 - 14:00 <h2>Voluntary</h2><h3>Group 1: Exercise group 1</h3>05.03.2024 14:00 - 16:00 12.03.2024 14:00 - 16:00 19.03.2024 14:00 - 16:00 26.03.2024 14:00 - 16:00 09.04.2024 14:00 - 16:00 16.04.2024 14:00 - 16:00 23.04.2024 14:00 - 16:00 <h3>Group 2: Exercise group 2</h3>07.03.2024 12:00 - 14:00 14.03.2024 12:00 - 14:00 21.03.2024 12:00 - 14:00 04.04.2024 12:00 - 14:00 11.04.2024 12:00 - 14:00 18.04.2024 12:00 - 14:00 25.04.2024 12:00 - 14:00 <h3>Group 3: Exercise group 3</h3>07.03.2024 14:00 - 16:00 14.03.2024 14:00 - 16:00 21.03.2024 14:00 - 16:00 04.04.2024 14:00 - 16:00 11.04.2024 14:00 - 16:00 18.04.2024 14:00 - 16:00 25.04.2024 14:00 - 16:00

In this course, the student learns the basic rules of calculating the probabilities and the basics of combinatorics. He or she understands the concept of a random variable and knows the properties of expectation and variance. The student is familiar with the most often used discrete and continuous probability distributions and is able to perform probability calculations under these distributions. The student understands the concept of joint probability distribution and knows the properties of covariance and correlation. The student obtains an understanding how random sampling is used in statistical inference, and why the concept of sample statistic and the distribution of the statistic are important in inference. The student learns the basic principles of estimation and hypothesis testing theory and is able to calculate confidence interval estimates and to perform statistical hypotheses testing especially in situations of one and two groups. The student understands the limitations of the testing theory and is able to calculate different effect size measures.

Finnish

<h2>Prerequisites</h2>Compulsory prerequisites: High school mathematics or equivalent.Recommended prerequisites (any of the below or equivalent): Fundamentals of Engineering Mathematics, Differential and Integral Calculus, OR Basic concepts of Mathematics, Introduction to Analysis or Analysis for Teachers, OR Bachelor of Engineering - University of Applied Sciences, Fundamentals of Differential and Integral Calculus, OR Introduction to Statistics.

<ul><li>AYCSMSCVO Open University Route, Computing Sciences, MSc. Tech.</li><li>AYEEMSCVO Open University Route, Electrical Engineering, MSc. Tech.</li><li>AYITMSCVO Open University Route, Information Technology, MSc. Tech.</li><li>AYKODIVO Open University Route, Mechanical Engineering, MSc</li><li>AYLYHYTVO Fast Open University Route</li><li>DATA.STAT-P03</li><li>MATH.MA-M03</li><li>MATH.MA-P03</li></ul>

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Introduction to Probability and Statistical Inference, Lectures

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Introduction to Probability and Statistical Inference, 5 cr

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Introduction to Probability and Statistical Inference, Lectures