Research Guides: Library Workshop Descriptions: Statistics

Statistics Workshops

Click on the tabs above to find out more about our statistics workshops.

1. Basic Statistical Concepts - A lecture format theoretical workshop that reviews the statistical concepts needed to select measures and run statistical tests.

2. Basic Statistics in Excel - Learn how to complete and interpret descriptive statistics, t-tests, and correlations in Excel in this hands-on workshop.

3. Data Visualization in Excel - Learn how to transform descriptive statistics, t-tests, and correlations into helpful visualizations and learn how to create these statistical graphs in excel.

4. Basic Statistics in SPSS - Learn how to complete and interpret descriptive statistics, t-tests, ANOVA, correlation, and multiple regression in SPSS in this hands-on workshop.

5. Statistics in R Workshop Series - Learn how to perform hypothesis testing (Workshop I), descriptive statistics (Workshop I), statistical assumptions (Workshop II), inferential statistics (Workshop III), and statistical visualization in R (Workshop IV). This is a 4 part series.

You can attend any workshop in the series without attending all of them; however, if you skip ahead in the series we recommend reviewing the pre-requisites (listed under each tab) to make sure you are prepared. Some of the workshops cover the same material with different software. If you would like to schedule a version of this sequence for your lab, student group, or as part of a class, reach out to us at DataServices@uoregon.edu.

If no upcoming events are listed for this class sequence below, you can search for related classes on our workshop schedule page.

Basic Statistical Concepts: Workshop Description

Software:	None
Duration:	90 min
Room description:	Knight Library Dream Lab
Prerequisites:	An undergraduate statistics course, or Familiarity with basic statistical concepts
Skills Taught / Learning Outcomes:	When and How to Consider Statistics Measurement Design Statistics Validity Reliability Data distributions Normal Exponential (Skewness) Kurtosis Poisson Types of variables Variable transformation and manipulation Descriptive Statistics Null-hypothesis significance testing Statistical Assumptions Inferential Statistics Correlation T-test ANOVA Regression Chi – Squared
Class Materials:
Related Classes:
Additional Training Materials:

Basic Statistics in Excel

Software:	Excel with Statistics Plug-in (comes with Excel, but must be enabled)
Duration:	90 min
Room description:	Knight Library Room 144
Prerequisites:	This course does not cover statistical theory, only application in Excel. Prior statistics course or Basic Theoretical Statistics Workshop required.
Skills Taught / Learning Outcomes:	1. Descriptive Statistics 2. Assumptions 3. Correlations 4. T-test
Class Materials:
Related Classes:	Basic Statistical Concepts, Basic Visualization in Excel
Accessibility:	Click here to learn how to use Excel with a screen reader and click here for best practices for designing accessible Excel spreadsheets. All of our workshop classrooms are wheelchair accessible and offer at least some chairs with no arms.

Data Visualization in Excel

Software:	Excel
Duration:	90 min
Room description:	Knight Library Room 144
Prerequisites:	Knowledge of statistical tests covered is necessary. Prior statistics course or Introduction to Statistics Workshop required.
Skills Taught / Learning Outcomes:	Histogram, scatter plots, and Box-and-Whiskers Plots Bar Graph for t-Test Visualization Line Graph for Correlation Visualization Grouped Bar Graph for 2-Way ANOVA
Class Materials:
Related Classes:	Basic Statistical Concepts, Basic Statistics in Excel
Accessibility:	Click here to learn how to use Excel with a screen reader and click here for best practices for designing accessible Excel spreadsheets. All of our workshop classrooms are wheelchair accessible and offer at least some chairs with no arms.

Check back soon for a full description of this workshop.

Statistics in R

Software:	R, R-Studio
Duration:	90 min
Room description:	Currently Online
Prerequisites:	These workshops are intended to build off of the Master the Tidyverse workshop series. The Master the Tidyverse series or comparable competency and an understanding of introductory statistics, RStudio, and RMarkdown is required.
Skills Taught / Learning Outcomes:	Descriptive Statistics Sample Size Mean Median Standard Deviation Range Frequency/Percentage Skewness Kurtosis Assumptions Normality – Histogram and skewness/kurtosis Independence – review dataset Homoscedasticity (Equality of Variances) - IV vs. DV Scatterplot Linearity – IV vs. DVs scatterplot Multicollinearity – Correlations (Next Step) Inferential Statistics Correlations T-test Chi-Squared (Count data) ANOVA Multiple Regression Data Visualization Box and Whisker plots Bar Graphs Single clustered lollipop Line Graphs Add standard deviation
Class Materials:	Sign up for Statistics in R Workshop Sequence - Materials
Related Classes:	Basic Statistical Concepts, Tidyverse Series
Accessibility:	Workshop classrooms are wheelchair accessible and include at least some chairs without arms. Base R is accessible to screen readers without modification, according to this linked report. While this class is taught using RStudio, which will not have an interface accessible to screen readers until some time in 2020, students can participate in the course using the screen reader-compatible base R.