ACCC Workshops Spring 2016
http://uofi.uic.edu/calendar/list/4483
ACCC Workshops Spring 2016One-Way Analysis of Variance - SPSS
http://uofi.uic.edu/calendar/detail/4483/33071775
http://uofi.uic.edu/calendar/detail/4483/33071775Mon, 15 Feb 2016 09:00:00 CST<p>Analysis of Variance (ANOVA) is one of the most commonly-used statistical tests. This class will cover “One-Way-Between-Subjects”, one of the most basic and frequently used models, employed to assess whether group-averages differ meaningfully due to some attribute(s) specific to one or more groups being studied.</p>
<p>Topics covered in this workshop include importing various genres of research data into SAS or SPSS, mathematical assumptions that must be met in order for ANOVA test results to be valid and reliable, relative effects of mathematical assumption violations on ANOVA testing, relative effectiveness of widely-accepted countermeasures to ANOVA assumption violations, using tabular or graphical means to identify assumption violations, and producing ANOVA graphs.</p>
<p><strong>Required homework: </strong>3 hours (estimated) of pre-class homework will be assigned 1 week before class starts. Completion of this homework is a required prerequisite.</p>
<p><strong>Recommended prerequisites:</strong> Completion of a 300- or 400-level course in statistics, completion of ACCC's “Introduction to SAS/SPSS” and “Linear Multiple Regression” workshops; OR equivalent knowledge acquired through academics and/or workplace experience. Comfort with using a syntax programming language.</p>
<p><strong>How to Register. </strong> Email your registration request to <a href="mailto:stats@uic.edu">stats@uic.edu</a> with the following information:</p>
<ul>
<li>Your @uic.edu email address.</li>
<li>Phone number. </li>
<li>Full name.</li>
<li>Your affiliation with UIC (for example: Jane Smith, PhD-Candidate, College of Nursing).</li>
<li>The name and date of the class(es) you are requesting to attend.</li>
<li>Your prerequisites. Review the workshop prerequisites. Include a brief description of the statistics courses you have completed that satisfy that workshop's prerequisites. Please do not request to attend a workshop for which you do not have the required prerequisites. If you completed the statistics coursework listed as prerequisite for the class you wish to attend but you know you have forgotten most of the training that you completed, please state this in your registration request. The instructor will suggest some learning resources that you can use to refresh your skills.</li>
</ul>
<p>For more information, please view the <a href="http://accc.uic.edu/set-url-path-before-you-publish-this-page/statistical-software-workshop-guidelines-and-registration">Statistical Software Workshop Guidelines and Registration Procedures</a>.</p>Logistic Binary Regression - SPSS
http://uofi.uic.edu/calendar/detail/4483/33071776
http://uofi.uic.edu/calendar/detail/4483/33071776Mon, 22 Feb 2016 08:30:00 CST<p>Logistic Regression is the third-leg of the mathematically logical triangle, which includes Linear Regression and ANOVA. This class will cover Logistic Binary Regression, which is employed to build predictive models when the outcome of research interest is dichotomous (e.g., “patient died/survived” or “customer purchased/didn’t purchase”). Like the Linear Regression and ANOVA workshops, this class is comprised of hands-on, applied, SPSS or SAS programming exercises. To instill the course with “real world” context and also provide a sense of topical continuity, all instruction will revolve around the same dataset: an authentic medical-trauma research study.</p>
<p>Topics covered in this workshop include: 1) a brief refresher on the mathematics that drive Logistic Binary Regression and of the circumstances under which this is the best procedure to use for predictive-model building; 2) extensive diagnostic data-screening to assess whether mathematical and scientific assumptions have been met sufficiently for a constructed model’s predictions to be valid and reliable; 3) individual case-deletion diagnostics to identify outliers that disproportionately influence the estimation of correlation coefficients during the building of the predictive model; 4) case-by-case qualitative analysis of the model’s predictive failures; 5) Plots, ROC Curve and S-graphs, and, 6) a brief introduction to the topic of “Propensity Score Matching” as a countermeasure for predictive-modeling confounds occasioned by substantial aggregate dissimilarities between Control and Treatment groups.</p>
<p><strong>Recommended prerequisites:</strong> completion of 400-level statistics classes, an aptitude for and an interest in multivariate statistical testing; and, a level of competency writing SPSS or SAS programming language which is equivalent to having completed the other four ACCC-sponsored SPSS or SAS workshops.</p>
<p><strong>Required homework: </strong>8-12 hours of pre-class homework will be assigned 1 week before class starts. Completion of this homework is a required prerequisite.</p>
<p><strong>How to Register. </strong> Email your registration request to <a href="mailto:stats@uic.edu">stats@uic.edu</a> with the following information:</p>
<ul>
<li>Your @uic.edu email address.</li>
<li>Phone number. </li>
<li>Full name.</li>
<li>Your affiliation with UIC (for example: Jane Smith, PhD-Candidate, College of Nursing).</li>
<li>The name and date of the class(es) you are requesting to attend.</li>
<li>Your prerequisites. Review the workshop prerequisites. Include a brief description of the statistics courses you have completed that satisfy that workshop's prerequisites. Please do not request to attend a workshop for which you do not have the required prerequisites. If you completed the statistics coursework listed as prerequisite for the class you wish to attend but you know you have forgotten most of the training that you completed, please state this in your registration request. The instructor will suggest some learning resources that you can use to refresh your skills.</li>
</ul>
<p>For more information, please view the <a href="http://accc.uic.edu/set-url-path-before-you-publish-this-page/statistical-software-workshop-guidelines-and-registration">Statistical Software Workshop Guidelines and Registration Procedures</a>.</p>Repeated Measures ANOVA
http://uofi.uic.edu/calendar/detail/4483/33071777
http://uofi.uic.edu/calendar/detail/4483/33071777Mon, 29 Feb 2016 08:30:00 CST<p><strong>Registration is closed and are fall statistical workshops are full.</strong></p>
<p>Due to its particular usefulness as a hypothesis-test for evaluating experimental treatments in human-subjects studies over time, r-ANOVA is widely used for clinical research as well as many other topically diverse areas like agriculture, economics, engineering, marketing, and psychology.</p>
<p>This workshop will cover 1) a brief refresher of the r-ANOVA formula and of the "mathematical mechanics" that it performs, 2) some conditions under which r-ANOVA may - or may not - be the most appropriate hypothesis-test for a dataset, 3) a few basic diagnostic protocols to help determine if, and how much, the mathematical properties of a dataset could weaken or even confound r-ANOVA test-results, 4) practical examples of some types of research confounds that cannot be directly assessed through statistical diagnostics-tests, 5) methods commonly used to partially-compensate for some violations of assumptions, 6) the SAS programming syntax required to perform metric-diagnostic tests, run the F-Test and alternatives to the F-Test, run post-hoc tests and alternative post-hoc tests, generate graphs for diagnostic-assessments and presentation of r-ANOVA test-results; 7) reporting of test-results and interpretations.</p>
<p><strong>Required homework:</strong> 8-12 hours of pre-class homework will be assigned 1 week before class starts. Completion of this homework is a required prerequisite.</p>
<p><strong>Recommended prerequisites:</strong> completion of graduate-level statistical coursework which covered the mathematics and assumptions of r-ANOVA, a level of competency writing SAS programming language.</p>
<p><strong>How to Register. </strong> Email your registration request to <a href="mailto:stats@uic.edu">stats@uic.edu</a> with the following information:</p>
<ul>
<li>Your @uic.edu email address.</li>
<li>Phone number. </li>
<li>Full name.</li>
<li>Your affiliation with UIC (for example: Jane Smith, PhD-Candidate, College of Nursing).</li>
<li>The name and date of the class(es) you are requesting to attend.</li>
<li>Your prerequisites. Review the workshop prerequisites. Include a brief description of the statistics courses you have completed that satisfy that workshop's prerequisites. Please do not request to attend a workshop for which you do not have the required prerequisites. If you completed the statistics coursework listed as prerequisite for the class you wish to attend but you know you have forgotten most of the training that you completed, please state this in your registration request. The instructor will suggest some learning resources that you can use to refresh your skills.</li>
</ul>
<p>For more information, please view the <a href="http://accc.uic.edu/set-url-path-before-you-publish-this-page/statistical-software-workshop-guidelines-and-registration">Statistical Software Workshop Guidelines and Registration Procedures</a>.</p>