Statistics and Probabilistics for Engineers IE-SI7O>SaPfE

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Koordynatorzy przedmiotu

Ocena końcowa

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.

Wymagania wstępne

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

Literatura podstawowa

P. Bruce, A. Bruce, P. Gedeck, Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, O’Reilly Media, 2020.
D. Y. Chien, Pandas for Everyone: Python Data Analysis, Addison-Wesley Professional, 2023.
W. W. Hines, D. C. Montgomery, D. M. Goldsman, C. M. Borror, Probability and Statistics in Engineering, John Wiley & Sons, New York 2003.
D. M. Levine, D. Stephan, T. C. Krehbiel, M. L. Berenson, Statistics for Managers Using Microsoft® Excel, Prentice Hall, Upper Saddle River 2005.
M. F. Triola, Essentials of Statistics, Addison-Wesley, Boston 2002.

Literatura uzupełniająca

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.

Inne informacje

Brak

Efekty kształcenia

Wiedza
Knows basic notions related to probability.
Powiązane efekty kierunkowe:
IE1A_W01
Metody weryfikacji:
Kolokwium
Kolokwium

Wiedza
Knows basic notions related to descriptive and mathematical statistics.
Powiązane efekty kierunkowe:
IE1A_W01
Metody weryfikacji:
Kolokwium
Kolokwium

Wiedza
Knows basic notions related to Python programming language
Powiązane efekty kierunkowe:
IE1A_W01
Metody weryfikacji:
Kolokwium

Umiejętności
Calculates probability of phenomena and parameters of the distribution of random variable.
Powiązane efekty kierunkowe:
IE1A_U12
Metody weryfikacji:
Kolokwium
Kolokwium

Umiejętności
Processes collected data using methods of descriptive statistics and finds confidence interval and tests parametrical and nonparametrical hypotheses.
Powiązane efekty kierunkowe:
IE1A_U12
Metody weryfikacji:
Kolokwium
Kolokwium

Umiejętności
Uses Python programming language in probability and statistical calculations.
Powiązane efekty kierunkowe:
IE1A_U07
Metody weryfikacji:
Kolokwium

Kompetencje społeczne
Has ability to think analytically, is aware of the level of her (his) knowledge and understands the need for continuous personal and professional development.
Powiązane efekty kierunkowe:
IE1A_K07
Metody weryfikacji:
Kolokwium
Kolokwium

Statistics and Probabilistics for Engineers IE-SI7O>SaPfE

Koordynatorzy przedmiotu

<b>Ocena końcowa</b>

<b>Wymagania wstępne</b>

<b>Literatura podstawowa</b>

<b>Literatura uzupełniająca</b>

<b>Inne informacje</b>

Efekty kształcenia