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DTSTART:20240310T070000
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TZOFFSETFROM:-0500
TZOFFSETTO:-0400
DTSTART:20180311T070000
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DTSTART:20231105T060000
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DTSTART:20171105T060000
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BEGIN:VEVENT
UID:66dfd06a0ee91
DTSTART;TZID=America/Toronto:20240918T093000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20240918T120000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/r-beginners-your-data-adventure-begins
SUMMARY:R for Beginners: Your Data Adventure Begins
CLASS:PUBLIC
DESCRIPTION:Summary \n\nJoin us for an introductory workshop to R\, where
you’ll learn the\nfundamentals of this powerful open-source language. \n
\nREGISTRATION IS FREE and open to all University of Waterloo faculty\,\n
staff\, and students (both graduate and undergraduate). No prior\nprogramm
ing experience is required.\n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a13e25
DTSTART;TZID=America/Toronto:20240320T093000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20240320T113000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/introduction-linear-regression
SUMMARY:An Introduction to Linear Regression
CLASS:PUBLIC
DESCRIPTION:Summary \n\nLinear regression models\, also known as linear mod
els\, are widely used\nin various applications and research. It is one of
the most popular\nmodels out there because of its simplicity and easy inte
rpretation. \n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a14d3d
DTSTART;TZID=America/Toronto:20240327T093000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20240327T160000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/survey-programming-qualtrics
SUMMARY:Survey Programming in Qualtrics
CLASS:PUBLIC
DESCRIPTION:Summary \n\nLearn how to use Qualtrics to create and launch a s
urvey. The goal of\nthis workshop is to provide an overview of the whole p
rocess along\nwith some hands-on exercises. The workshop will start with i
nstruction\non how to build a survey\, then will cover getting it ready fo
r the\nfield\, and finish with showing users how to distribute\, monitor\,
and\nextract their data.\n\nRegistration is free to all students\, facult
y and staff at the\nUniversity of Waterloo.\n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a159ef
DTSTART;TZID=America/Toronto:20240214T093000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20240214T113000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/introduction-exploratory-data-analysis-r
SUMMARY:Introduction to Exploratory Data Analysis with R
CLASS:PUBLIC
DESCRIPTION:Summary \n\nIn this workshop\, participants will learn to perfo
rm analysis using an\napproach that identifies general patterns in the dat
a.\n\nRegistration is free to all students\, faculty and staff at the\nUni
versity of Waterloo.\n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a166eb
DTSTART;TZID=America/Toronto:20240228T090000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20240228T160000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/how-guide-developing-survey-questionnaires
SUMMARY:The How-To Guide for Developing Survey Questionnaires
CLASS:PUBLIC
DESCRIPTION:Summary \n\nIn this one-day workshop\, drawing on Dr. Sarah Wil
kins-Laflamme’s 10\nyears of experience running national and internation
al surveys\, we\nwill review the key steps in developing high-quality surv
ey questions\nand questionnaires along with tips for achieving precise\, r
elevant and\naccessible measures when collecting survey data via smartphon
e\,\ntablet\, computer\, in-person interview\, telephone interview\, and\n
mail. \n\nThe workshop will be held in DC 1568. Registration is free for
all\nstudents\, faculty and staff at the University of Waterloo.\n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a175be
DTSTART;TZID=America/Toronto:20180622T133000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20180622T160000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/introduction-regression-analysis-r
SUMMARY:Introduction to Regression Analysis with R
CLASS:PUBLIC
DESCRIPTION:Summary \n\nThis workshop will provide participants with an int
roduction to simple\nand multiple linear regression. Topics covered in thi
s workshop\ninclude the regression models\, model assumptions\, interpreta
tion of\ncoefficients\, significance testing\, interactions between variab
les and\nthe use and interpretation of dummy variables. Model checking met
hods\nsuch as residual plots and collinearity diagnostics will also be\nco
vered. Several methods for model selection will be included.\n\nRegistrati
on is free and open to all University of Waterloo faculty\,\nstaff and gr
aduate students.\n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a18325
DTSTART;TZID=America/Toronto:20180713T130000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20180713T153000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/introduction-poisson-regression-r
SUMMARY:Introduction to Poisson Regression with R
CLASS:PUBLIC
DESCRIPTION:Summary \n\nThis workshop will provide participants with an int
roduction to\nPoisson regression used to model counts observed in a period
of time.\nTopics covered in this workshop includes the Poisson regression
model\,\nmodel assumptions\, interpretation of coefficients\, significanc
e\ntesting\, interactions between variables and the use and interpretation
\nof dummy variables. Model checking methods such as residual plots and\ng
oodness-of-fit tests will also be covered. Several methods for model\nsele
ction will be included.\n\nRegistration is free and open to all Universit
y of Waterloo faculty\,\nstaff and graduate students.\n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a192aa
DTSTART;TZID=America/Toronto:20180817T130000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20180817T153000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/introduction-logistic-regression-r
SUMMARY:Introduction to Logistic Regression with R
CLASS:PUBLIC
DESCRIPTION:Summary \n\nThis workshop will show participants how to estimat
e and make\ninferences about a binary response probability and related qua
ntities\nthrough logistic regression. Topics covered in this workshop incl
udes\nthe logistic regression model\, model assumptions\, interpretation o
f\ncoefficients\, significance testing\, interactions between variables an
d\nthe use and interpretation of dummy variables. Model checking methods\n
such as residual plots and goodness-of-fit tests will also be covered.\nSe
veral methods for model selection will be included.\n\nRegistration is fr
ee and open to all University of Waterloo faculty\,\nstaff and graduate st
udents.\n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a1a118
DTSTART;TZID=America/Toronto:20180926T130000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20180926T153000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/introduction-r-1
SUMMARY:Introduction to R
CLASS:PUBLIC
DESCRIPTION:Summary \n\nIn this introduction to R workshop\, participants w
ill be taught the\nbasics of this open source language. Topics covered in
this workshop\nincludes:\n\n* Help tools\n * Importing / exporting data\n
* Data management\n * Descriptive and exploratory statistics\n * Graphics\
n * Common statistical analyses\n\nRegistration is free and open to all U
niversity of Waterloo faculty\,\nstaff\, graduate and undergraduate studen
ts. No programming experience\nis assumed\n
DTSTAMP:20240910T045154Z
END:VEVENT
BEGIN:VEVENT
UID:66dfd06a1ae7c
DTSTART;TZID=America/Toronto:20181031T130000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20181031T150000
URL:https://uwaterloo.ca/statistical-consulting-survey-research-unit/events
/introduction-feature-selection
SUMMARY:An introduction to feature selection
CLASS:PUBLIC
DESCRIPTION:Summary \n\nFeature selection is the process of selecting a sub
set of relevant\nfeatures (commonly known as predictors or independent var
iables) for\nmodel construction. Performing feature selection allows resea
rchers to\nidentify irrelevant data\, improve the interpretation and incre
ase\npredictive accuracy of learned models. A feature selection algorithm\
ncan be seen as the combination of a search technique for proposing new\nf
eature subsets\, along with an evaluation which scores the different\nfeat
ure subsets. The choice of evaluation measure heavily influences\nthe algo
rithm. There are three main categories of feature selection\nalgorithms: w
rappers\, filters and embedded methods. In this seminar\,\nwe will introdu
ce some basic feature selection methods such as\nscore-based feature ranki
ng\, stepwise subset selection and LASSO\nregression.\n\nRegistration is
free and open to all University of Waterloo faculty\,\nstaff\, graduate an
d undergraduate students. The primary software we\nwill discussed in this
seminar is RStudio. There is no hands-on work\nin this seminar.\n
DTSTAMP:20240910T045154Z
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