Kurs-Code Mate2038
Kreditpunkte 3
Stundenzahl insgesamt (im Auditorium)81
Vorlesungen (Stundenzahl)16
Stundenzahl fŅr Seminare und praktische Arbeitsaufträge16
Selbststandige Arbeit des Studenten (Stunden)49
Bestätigt am (Datum)20.01.2015
Kurs ausgearbeitet von (Lehrkraft)
Laima Bērziņa
Vorkenntnisse
Mate2037,
Zur einfŅhrenden LektŅre empfohlen
1. Arhipova I., Bāliņa S. Statistika ekonomikā un biznesā. Rīga: Datorzinību Centrs, 2006. 364 lpp.
2. Smotrovs J. Varbūtību teorija un matemātiskā statistika II. Rīga: Zvaigzne ABC, 2007. 136 lpp.
3. Grīnglazs L., Kopitovs J. Matemātiskā statistika: ar datoru lietojuma paraugiem uzdevumu risināšanai. Rīga: Rīgas Starptautiskās ekonomikas un biznesa administrācijas augstskola, 2003. 310 lpp.
4. Helsel D.R., Hirsch R.M. Statistical Methods in Water Resources Techniques of Water Resources Investigations. U.S.: Geological Survey, 2002. 522 p. Pieejama elektroniski https://books.google.com
Weiterfuhrende Literatur
1. Gilbert R.O. Statistical Methods for Environmental Pollution Monitoring. John Wiley&Sons, 1987. 336 p.
2. Mac Berthouex P., Brown L.C. Statistics for Environmental Engineers. Lewis Publishers, 2002. 489 p. Pieejama elektroniski https://books.google.com
3. Gibbons R.D., Coleman D.E. Statistical Methods for Detection and Quantification of Environmental Contamination. John Wiley&Sons, 2001. 384 p. Pieejama elektroniski https://books.google.com
Zur LektŅre vorgeschlagene Zeitschriften
1. Environmental and Ecological Statistics. Publisher Springer US. ISSN: 1573-3009 (electronic version)
2. Journal of Agricultural, Biological, and Environmental Statistics. Publisher Springer US. ISSN: 1537-2693 (electronic version)