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Statistical analysis using MS EXCEL

General data

Course ID:	2400-EXCEL-OG
Erasmus code / ISCED:	14.3 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0311) Economics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Statistical analysis using MS EXCEL
Name in Polish:	Analiza statystyczna w programie MS EXCEL
Organizational unit:	Faculty of Economic Sciences
Course groups:	General university courses General university courses in Faculty of Economics General university courses in the social sciences On-line general university courses
ECTS credit allocation (and other scores):	3.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Type of course:	general courses
Prerequisites (description):	(in Polish) Zaliczenie przedmiotu pt. „Wstęp do Excela i analizy danych ekonomicznych”, bądź opanowanie materiału omawianego na tym kursie. Uwaga: kurs ten wymaga od studentów stosunkowo dużo pracy i jest dedykowany dla osób, które znają podstawy Excela i chcą nauczyć się przeprowadzać analizę statystyczną danych. Zajęcia prowadzone są na poziomie zaawansowanym.
Short description:	This course is dedicated to people who want to learn or to systematize knowledge of statistical methods used in research and data analysis, as well as people who work a lot in Excel and want to know the use of statistics tools in Excel.
Full description:	Detailed list of topics: • time series data, • summary statistics, • correlation measures, • statistical graphs - histograms, boxplot, etc., • statistical hypotheses, • regression models, • operational research - optimization (Solver), • operational research - simulation (Monte Carlo method), • examples of statistics applications in Excel. Note 1: classes are held in the form of e-learning on the platform: https://elearning.wne.uw.edu.pl (no live classes). Note 2: The software version in the course is Microsoft Office 2019 or 365 (language version: English, operating system: Windows). Using an earlier version is possible, but it may cause some difficulties. The Polish language version is not a major problem, but the course a different operating system is (e.g. MacOS) due to the limitations of the Office suite (possible lack of necessary software components). The University of Warsaw does not provide participants with the necessary computer hardware or software.
Bibliography:	• Materiały własne • Walkenbach J, 2020, Excel 2019 PL. Formuły, Helion, Warszawa • Walkenbach J, 2014, Excel 2013. 101 porad i sztuczek które oszczędzą Twój czas, Helion, Warszawa • Brand S., 2002, Analiza danych, Wydawnictwo Naukowe PWN, Warszawa • Masłowski K., 2004, Excel 2003 PL - 161 praktycznych porad, Helion, Gliwice • Koronacki J., Mielniczuk J., 2001, Statystyka dla studentów kierunków technicznych i przyrodniczych, Wydawnictwa Naukowo-Techniczne, Warszawa • Ferguson G., Takane Y., 1999, Analiza statystyczna w psychologii i pedagogice, Wydawnictwo Naukowe PWN, Warszawa • Red. Szapiro T., 2000, Decyzje menedżerskie z Excelem, Polskie Wydawnictwo Ekonomiczne, Warszawa • Lapin L., 1987, Statistics for modern business decision, Harcourt Brace Jovanovich
Learning outcomes:	After completing the course the student obtains the ability to statistical analysis in Excel, including: time series data, summary statistics, correlation measures, statistical graphs (histograms, boxplot, etc.), statistical hypotheses, regression models, optimization (Solver), simulation (Monte Carlo method).
Assessment methods and assessment criteria:	The final evaluation consists of: • Homework (60 pts.): two cumulative homework each scored 30 points. • Questions and answers on the Discussion Forums: maximum 3 points for each Scoring: Points Mark (0-30) 2 (30-36) 3 (36-42) 3,5 (42-48) 4 (48-54) 4,5 (54-60) 5 60 + 5!

Classes in period "Winter semester 2023/24" (past)

Time span:	2023-10-01 - 2024-01-28	Selected timetable range: weekly course term Navigate to timetable
Type of class:	E-learning course, 30 hours, 30 places more information
Coordinators:	Przemysław Kusztelak
Group instructors:	Andrzej Krasnodębski, Przemysław Kusztelak
Students list:	(inaccessible to you)
Examination:	Course - Grading E-learning course - Grading

Course descriptions are protected by copyright.
Copyright by University of Warsaw.