Statistics and Probability (5 cr)
Code: 5000BL67-3005
General information
Enrollment
01.06.2023 - 17.09.2023
Timing
05.09.2023 - 15.12.2023
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Engineering and Business
Campus
Kupittaa Campus
Teaching languages
- English
Degree programmes
- Degree Programme in Information and Communication Technology
- Degree Programme in Information and Communications Technology
Teachers
- Hazem Al-Bermanei
Groups
-
ICT_MOD_UPV_23ICT_MOD_UPV_23
-
PTIVIS20OSoftware engineering and Project Management
-
PINFOS20
-
PTIVIS20TData Networks and Cybersecurity
-
PTIVIS20HTerveysteknologia
-
PTIVIS20SEmbedded Software and IoT
-
PTIVIS20PGame and Interactive Technologies
- 23.11.2023 14:00 - 16:00, (engl.) Statistics and Probability 5000BL67-3005
- 27.11.2023 14:00 - 16:00, (engl.) Statistics and Probability 5000BL67-3005
- 30.11.2023 14:00 - 16:00, (engl.) Statistics and Probability 5000BL67-3005
- 04.12.2023 14:00 - 16:00, (engl.) Statistics and Probability 5000BL67-3005
- 07.12.2023 14:00 - 16:00, (engl.) Statistics and Probability 5000BL67-3005
- 11.12.2023 14:00 - 16:00, (engl.) Statistics and Probability 5000BL67-3005
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 Optima): peer feedback summative teacher feedback at the end of the course.
Final exam: 30 %: A 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