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PRODID:-//Columba Systems Ltd//NONSGML CPNG/SpringViewer/ICal Output/3.3-
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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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