(in Polish) Statistics and Probabilistics for Engineers IE-SI7O>SaPfE

This course has not yet been described...

Course coordinators

Final assessment

The form and criteria for obtaining a credit, including the rules for retake credits, as well as the conditions for admission to the exam:

Lectures: Obtaining 50% points on classwork. The final grade depends upon the sum of points obtained namely: Percentage of points obtained Grade at least 50% - less than 60% 3.0 at least 60% - less than 70% 3.5 at least 70% - less than 80% 4.0 at least 80% - less than 90% 4.5 at least 90% 5.0

Auditorium exercises: There will be 2-4 tests during the course. The final grade is determined based on the sum of points obtained. Percentage of points obtained Grade at least 50% - less than 60% 3.0 at least 60% - less than 70% 3.5 at least 70% - less than 80% 4.0 at least 80% - less than 90% 4.5 at least 90% 5.0

The final grade is equal to rounding off (up or down to the closest one) of weighted arithmetic mean of all (every final date) grades obtain from both laboratory (weight two) and lecture (weight one) (the lowest final grade is 3.0). It is allowed to verify the achievement of learning outcomes by students using remote learning methods and techniques.

Prerequisites

Secondary school mathematics and some notions from the parallel course of mathematical analysis.

Basic literature

1. D. R. Anderson, D.J. Sweeney, T. A. Williams, J. Freeman, S. Shoesmith, Statistics for Business and Economics, Cengage Learning, Andover 2010. 2. M. Bonamente, Statistics and Analysis of Scientific Data, Springer Science+Business Media, New York 2017. 3. B. S. Madsen, Statistics for Non-Statisticians, Springer-Verlag, Berlin - Heidelberg 2016. 4. R. C. Mittelhammer, Mathematical Statistics for Economics and Business, Springer-Verlag, New York 2013. 5. G. Mount, Advancing into Analytics: From Excel to Python and R, O’Reilly Media, 2021.

Supplementary literature

D. R. Anderson, D.J. Sweeney, T. A. Williams, J. Freeman, S. Shoesmith, Statistics for Business and Economics, Cengage Learning, Andover 2010.
M. Bonamente, Statistics and Analysis of Scientific Data, Springer Science+Business Media, New York 2017.
B. S. Madsen, Statistics for Non-Statisticians, Springer-Verlag, Berlin - Heidelberg 2016.
R. C. Mittelhammer, Mathematical Statistics for Economics and Business, Springer-Verlag, New York 2013.
G. Mount, Advancing into Analytics: From Excel to Python and R, O’Reilly Media, 2021.

Other information

None

Learning outcomes

Knowledge
Knows basic notions related to probability.
Related directional learning outcomes:
IE1A_W01
Verification metods:
:Colloquium,
Classwork
:Colloquium,
Classwork

Knowledge
Knows basic notions related to descriptive and mathematical statistics.
Related directional learning outcomes:
IE1A_W01
Verification metods:
:Colloquium,
Classwork
:Colloquium,
Classwork

Knowledge
Knows basic notions related to Python programming language
Related directional learning outcomes:
IE1A_W01
Verification metods:
:Colloquium,
Classwork

Skills
Calculates probability of phenomena and parameters of the distribution of random variable.
Related directional learning outcomes:
IE1A_U12
Verification metods:
:Colloquium,
Classwork
:Colloquium,
Classwork

Skills
Processes collected data using methods of descriptive statistics and finds confidence interval and tests parametrical and nonparametrical hypotheses.
Related directional learning outcomes:
IE1A_U12
Verification metods:
:Colloquium,
Classwork
:Colloquium,
Classwork

Skills
Uses Python programming language in probability and statistical calculations.
Related directional learning outcomes:
IE1A_U07
Verification metods:
:Colloquium,
Classwork

Social competence
Has ability to think analytically, is aware of the level of her (his) knowledge and understands the need for continuous personal and professional development.
Related directional learning outcomes:
IE1A_K07
Verification metods:
:Colloquium,
Classwork
:Colloquium,
Classwork

(in Polish) Statistics and Probabilistics for Engineers IE-SI7O>SaPfE

Course coordinators

<b>Final assessment</b>

<b>Prerequisites</b>

<b>Basic literature</b>

<b>Supplementary literature</b>

<b>Other information</b>

Learning outcomes