Excel
Kurstitel
Kurs-Code Mate2038
Kreditpunkte (ECTS) 3
Stundenzahl insgesamt (im Auditorium) 81
Vorlesungen (Stundenzahl) 16
Stundenzahl fŅr Seminare und praktische Arbeitsaufträge 16
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)