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PRODID:-//Columba Systems Ltd//NONSGML CPNG/SpringViewer/ICal Output/3.3-
 M3//EN
VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20190726T120431Z
DTSTART;VALUE=DATE:20190925
DTEND;VALUE=DATE:20190927
SUMMARY:Royal Statistical Society Course - Introduction to R & Statistica
 l Modelling in R
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}a2v-jye9hut
 6-moeqdd
DESCRIPTION:A two-day foundation course delivered by the Royal Statistica
 l Society in partnership with methods@manchester\n\nCourse Outline\n\nTh
 e purpose of this course is to introduce participants to the R environme
 nt for statistical computing. Day 1 of the course focuses on entering\, 
 working with and visualising data in R. Day 2 focuses on regression mode
 lling in R\, including linear\, general linear\, logistic and survival m
 odels. \n\nLearning Outcomes\n\nBy the end of Day 1\, participants will 
 be able to use R to:\n- Perform data entry from a variety of sources (e.
 g. Excel and SPSS spreadsheets).\n- Produce simple variable summaries (e
 .g. means\, variances\, quartiles) and graphical displays (e.g. histogra
 ms\, box plots\, scatter plots).\n- Find further information using the h
 elp system and online resources.\n- Perform simple hypothesis tests on o
 ne or two variables\; appropriately interpreting results and checking va
 lidity of assumptions.\n\nBy the end of Day 2\, participants will be abl
 e to:\n- Fit regression models in R between a response variable (includi
 ng continuous\, binary\, categorical and survival responses) and a set o
 f possible predictor variables\n- Make appropriate assumptions about the
  structure of the data in a regression model and check the validity of t
 hese assumptions in R.\n\nTopics Covered\n\nTopics covered in Day 1 incl
 ude: entering data and obtaining help in R\; working with data in R\; su
 mmarising data graphically and numerically in R\; basic hypothesis tests
  in R.\nTopics covered in Day 2 include: the linear model in R\; the gen
 eral linear model in R\; logistic regression in R\; survival models in R
 .\n\nTarget Audience\n\nThis course is ideally suited to anyone who:\n- 
 is familiar with basic statistical methods (e.g. t-tests\, boxplots) and
  who want to implement these methods using R.\nhas used menu-driven stat
 istical software (e.g. SPSS\, Minitab) and who want to investigate the f
 lexibility offered by a command line package such as R.\n- is already fa
 miliar with basic statistical methods in R and who wish to extend their 
 knowledge to regression involving multiple predictor variables\, binary\
 , categorical and survival response variables.\n- is familiar with regre
 ssion methods in menu-driven software (e.g. SPSS\, Minitab) and who wish
  to migrate to using R for their analyses.\n\nAssumed Knowledge\n\nThe c
 ourse requires familiarity with basic statistical methods (e.g. t-tests\
 , box plots) but assumes no previous knowledge of statistical computing.
  \nEach participant will need to bring their own laptop installed with t
 he R software (which can be downloaded free for Linux\, MacOS X or windo
 ws from http://www.stats.bris.ac.uk/R/)\n\nFees  	 \n\nRegistration befo
 re\n28 August 2019\n	                                  \nNon Member  £59
 6+vat \n\nRSS Fellow £507+vat \n\nRSS CStat: also MIS\, FIS & GradStat £
 478+vat\n	  	\nRegistration on/after\n28 August 2019\n\nNon Member £663+
 vat \n\nRSS Fellow £563+vat \n\nRSS CStat: also MIS\, FIS & GradStat £53
 0+vat\n	 \n\nMultiple booking discounts available for bookings of 3 or m
 ore places - please contact training@rss.org.uk for further information\
 n\nWe accept invoice and card payments
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:Room 8 Manchester Meeting Place\, Manchester Meeting Place
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