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Statistics and Probability (5 cr)

Code: 5000BL67-3008

General information


Enrollment

01.12.2023 - 15.01.2024

Timing

08.01.2024 - 30.04.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Engineering and Business

Campus

Kupittaa Campus

Teaching languages

  • English

Seats

20 - 40

Degree programmes

  • Degree Programme in Information and Communications Technology

Teachers

  • Mikko Peltonen de Santiago

Groups

  • PINFOS21
  • 10.01.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 12.01.2024 10:00 - 12:00, Statistics and Probability 5000BL67-3008
  • 16.01.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 17.01.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 23.01.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 24.01.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 30.01.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 31.01.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 06.02.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 07.02.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 13.02.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 14.02.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 27.02.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 28.02.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 05.03.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 06.03.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 12.03.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 13.03.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 19.03.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 20.03.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 26.03.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 27.03.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 02.04.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 03.04.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 09.04.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 10.04.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008
  • 16.04.2024 14:00 - 16:00, Statistics and Probability 5000BL67-3008
  • 17.04.2024 12:00 - 14:00, Statistics and Probability 5000BL67-3008

Objective

After completing the course the student can:
- calculate different mean and standard deviation figures for a given statistical data
- determine the regression line and correlation, and understand their significance
- identify and draw various statistical diagrams
- recognize the basic concepts of continuous and discrete probability distributions
- normalize a normally distributed variable and calculate the associated probabilities
- calculate confidence intervals and understand the significance of error in statistical mathematics
- determine p-value using the z-test and t-test of average
- construct contingency tables and apply the chi-square test

Content

- mean and standard deviation figures
- diagrams and their differences
- regression, correlation
- basic definitions and formulas of probability
- discrete probability distribution, binomial distribution, Poisson distribution
- continuous probability distribution, normal distribution, normalization
- statistical testing, sampling, confidence interval
- z-test and t-test of average
- contingency tables and chi-square test

Materials

All practical information on timetables, project work, grading etc., as well as links to web materials are provided in ITSLEARNING.

Teaching methods

Teacher-directed classroom activities, group work and independent work; project work, reports, task-based (homework)

International connections

The contents of the course give understanding to use the mean and standard deviation,.. , and the figures to analyze the data.
The students will team up for a project work and writing reports on some current and relevant aspect of statistics, which gives everyone an opportunity to understand the topic; all students will develop their statistical proficiency.
Task-based assessment supports learning and is continuous throughout the course. Studying in an international group develops students’ ability to intercultural communication and multicultural collaboration.

Completion alternatives

Probability and Statistics (3rd edition),Murray R. Spiegel, John J. Schiller, R. Alu Srinivasan, SCHAUM’S outlines.

Student workload

Classroom activities: Classroom activities participation: 50 h
Homework: Working on homework sets 1-6: 30 h
Project work: Research, presentation material, presentation: 20h
Final exam: Preparing for the final exam : 25 h

Content scheduling

- mean and standard deviation figures
- diagrams and their differences
- regression, correlation
- basic definitions and formulas of probability
- discrete probability distribution, binomial distribution, Poisson distribution
- continuous probability distribution, normal distribution, normalization
- statistical testing, sampling, confidence interval
- z-test and t-test of average
- contingency tables and chi-square test

Evaluation scale

H-5

Assessment methods and criteria

Homework sets 1-6: 30 %: Total of thirty homework exercises based on reading material and classroom notes: diagnostic/formative self / teacher evaluation
in connection with each homework set return session.
Project work, reports, presentations: 40 % : Each outcome of the project work is assessed independently (assessment criteria is specified in TSLEARNING): peer feedback summative teacher feedback at the end of the course.
Two written exam (1,5 hrs) on specified material: Summative teacher evaluation at the end of the course

Assessment criteria, fail (0)

Fail in the final exam and not doing the assignments.

Assessment criteria, satisfactory (1-2)

Collect (50--60) points in the exam and doing 50% of the assignments.

Assessment criteria, good (3-4)

Collect (70--80) points in the exam and doing at least 75% of the assignments

Assessment criteria, excellent (5)

Collect (90--100) points in the exam and doing at least 90% of the assignments

Qualifications

Courses Engineering Precalculus, Calculus and Topics in Applied Mathematics
OR
equivalent skills