Beginning in 2013, all ISCC workshops are * FREE*! No registration is required and seating is on a first come, first served basis.

**Stephanie Dickinson, **Senior Consultant & Managing Director, ISCC

Fri Sept 5, 2 - 4 pm

**Woodburn Hall 200, SSRC**

This workshop will give an overview of how to identify what types of data analysis tools to use for a project, along with basic “DIY” instructions. We will discuss the most common analysis tools for describing your data and performing significance tests (ANOVA, Regression, Correlation, Chi-square, etc), and how they should be selected based on the type of data and the type of research question you have. We will spend the first hour outlining ‘what analysis to use when’ and the second hour going through an example dataset in SPSS software, “Comparing motivations for shopping at Farmer’s markets, CSA’s, or neither.” Bring your own dataset to work along also.

Click here for slides and data.

**Wes Beaulieu, **Senior Consultant, ISCC

Fri Oct 31, 2 - 4 pm

Woodburn Hall 200, SSRC

Analysis of Variance (ANOVA) is one of the most widely used statistical methods today because of its versatility and interpretability. At its most basic, ANOVA is a way to compare the mean response of more than two groups, whereas a t-test is limited to two groups. This workshop will provide an overview of ANOVA including experimental design, interpretation of main effects and interactions, post-hoc tests and model validation/verification of assumptions. Examples will be provided in both R (freeware) and SPSS (freely available through IUAnyware). These software packages will produce identical results but through different workflow steps. By the end of this workshop you should be able to identify when to use ANOVA, effectively plan a study for analysis with ANOVA and use statistical software to generate valid, interpretable results leading to scientific inference.

Click here for slides and data.

**Michael Frisby, **Senior Consultant, ISCC

Fri Nov 14, 2 - 4 pm

Woodburn Hall 200, SSRC

R is a flexible and powerful open source statistical programming language, and is one of the fastest growing analytic tools available. Its ever expanding functionality has made it an immensely popular resource to researchers across a wide variety of quantitative disciplines. Like many programming languages, R uses a command line syntax to create and store variables, write functions, and load, manipulate, analyze, and visualize data.

This two-hour workshop is designed for newcomers to the R programming language. Our goal is to get the participant comfortable with the R programming environment by exploring how to import and export data, manipulate data, visualize data, utilize packages, and run some basic statistical procedures, such as t-tests and correlation tables, using the R syntax. Time permitting, we may also explore additional analyses such as ANOVA and linear regression.

Click here for slides and data.

**Download** all ISCC Workshop slides & data @ https://iu.box.com/ISCCWorkshops (IU access only)

**Stephanie Dickinson, **Senior Consultant, ISCC

Fri, January 31, **Woodburn Hall 200, SSRC
**

2:30 - 4:30:

This workshop will give an overview of how to identify what types of data analysis tools to use for a project, along with basic “DIY” instructions. We will discuss the most common analysis tools for describing your data and performing significance tests (ANOVA, Regression, Correlation, Chi-square, etc), and how they should be selected based on the type of data and the type of research question you have. We will spend the first hour outlining ‘what analysis to use when’ and the second hour going through an example dataset in SPSS software (via IUanyware) “Comparing motivations for shopping at Farmer’s markets, CSA’s, or neither.”

**Thomas Jackson, **Senior Consultant, ISCC

Fri, March 28, Woodburn Hall 200, SSRC

12:30 - 2:30

R is a free statistical programming language that provides many powerful tools for visualizing and analyzing data. R is used exclusively with programming syntax (i.e. no “point-and-click” interface) and therefore has a steep learning curve for new programmers. This two hour workshop will help users get familiar with the R user environment and begin doing basic analyses immediately. We will start with importing data files from Excel (.csv), doing basic descriptive statistics and plots, and move into fundamental analyses such as T-tests, ANOVA, Correlations, Regression, etc.

**Maria Kaylen**, Senior Consultant, ISCC

**Fri, April 11, Woodburn Hall 200, SSRC
**

Logistic regression is a commonly used type of analysis in the social sciences and other fields in which the outcome of interest is dichotomous. This workshop takes a hands-on approach to utilizing Stata’s logit command. I will provide a brief overview of logistic regression, discuss Stata’s commands (as well as additional post-estimation commands), explain how to interpret the output, and then lead participants in a data analysis example using Stata via IUanyWare. Computers are provided for participants.

*Fri, September 27, 2 - 4, Woodburn Hall 200, SSRC
Instructor: Stephanie Dickinson, Senior Consultant, ISCC*

This workshop will give an overview of how to identify what types of data analysis tools to use for a project, along with basic “DIY” instructions. We will discuss the most common analysis tools for describing your data and performing significance tests (ANOVA, Regression, Correlation, Chi-square, etc), and how they should be selected based on the type of data and the type of research question you have. We will spend the first hour outlining “what analysis to use when” and the second hour going through examples in SPSS software.

*Fri, October 11, 1:30 - 4, Woodburn Hall 200, SSRC
Instructor: Thomas Jackson, Senior Consultant, ISCC*

R is a free statistical programming language that provides many powerful tools for visualizing and analyzing data. R is used by statisticians around the world and is becoming increasingly popular in a variety of quantitative disciplines. R is used exclusively with programming syntax (i.e. no “point-and-click” interface) and therefore has a steep learning curve for new programmers. This two and a half hour workshop will introduce the fundamentals of R. Participants will become familiar with the R user environment, basic data structures, and syntax. Methods for creating and importing data files and downloading and using additional packages will be covered, along with the basic descriptive statistic, plots, and elementary statistical tests.

*Fri, March 8, 2012, 2 - 4, Woodburn 120*

*Instructor: William Wyatt, Visiting Assistant Professor, Department of Statistics*

This workshop will give a guided tour through using linear models in the R programming language. We will discuss why and how to use linear models along with how to interpret output from R. Topics covered will include linear regression, ANOVA, and logistic regression.

*Tuesday, March 26, 2012, 2:30 - 4, Cedar Hall 112*

*Instructor: Stephanie Dickinson, Senior Consultant, ISCC*

This workshop will be an adventure through the path of the data analysis process: from the open fields of formulating your research questions, through the forest of selecting the appropriate analysis tools, wading through the necessary model assumptions and diagnostic tools, investigating relevant plots and tables, and crossing the final bridge for interpretting results and reporting conclusions.

**Download** all ISCC Workshop slides & data @ https://iu.box.com/ISCCWorkshops (IU access only)

For SAS and SPSS training, see UITS IT Training >>

For WIM (Workshop in Methods), see WIM workshops >>