Random Chats About Data are in person events only. Through conversations and discussions we broaden our understanding of a data analysis topic. Talking about the big concepts as well as the nuances gives insight on how to apply these bigger ideas to our own data project. You will get comfortable with detailed aspects of data analysis. Please come prepared to talk about your own specific data questions.
Check out current offerings in the event calendar or contact me for a custom workshop.
Can't make it on campus? - Sign up for a one-on-one online session with me to discuss your statistics and data analysis questions.
Statistical Computing and Coding Workshops
Learn and strengthen statistical coding skills. Sessions can be customized for R, SAS, STATA or SPSS users. Online or in-person formats are available.
Example topics Getting started with statistical coding in R or SAS or STATA - Data summaries - Data wrangling - Functions - Graphing - Linear models: concepts, validation, interpretation - Categorical data methods - Ordination
Check out current offerings in the event calendar or contact me for a custom workshop.
Custom Workshops
If you would like me to come to your lab or department for a custom workshop, please contact me to discuss your needs.
During this workshop we will chat about best practices to organize, format, clean, manage and store data.
Data collection and Sample Size
During this workshop we will chat about data collection best practices including sampling, sources of bias and sample size.
Interpreting Statistical Output
During this workshop we will chat about how to interpret the output from a statistical analysis such as p-values and confidence intervals and parameter estimates.
Systematic Review and Meta Analysis
During this workshop we will chat about best practices when synthesizing results from cumulating studies.
Linear Models
During this workshop we will explore linear regression, t-tests, ANOVA and other linear models.
AI supported Data Analysis
During this workshop we will chat about how best to leverage AI to help write code for statistical analysis. We will discuss validity, reliability, reproducibility and data safety.
Variable Selection
During this workshop we will discuss pros and cons of methods to approach data sets that have an overabundance of variables, such as stepwise selection, penalized regression and PCA.
What is a good model for the data?
During this workshop we will discuss how to approach the choice of an appropriate data analysis, how to check assumptions and how to assess goodness-of-fit as well as validity.
Data Projection and Ordination
During this workshop we will learn when and how to use data projection and ordination methods such as PCA and NMDA.
Non-parametric data analysis methods
During this workshop we will discuss methods for data that do not follow a known distribution.
Data Organization
During this workshop we will chat about best practices to organize, format, clean, manage and store data.
Data collection and Sample Size
During this workshop we will chat about data collection best practices including sampling, sources of bias and sample size.
Interpreting Statistical Output
During this workshop we will chat about how to interpret the output from a statistical analysis such as p-values and confidence intervals and parameter estimates.
Systematic Review and Meta Analysis
During this workshop we will chat about best practices when synthesizing results from cumulating studies.
Linear Models
During this workshop we will explore linear regression, t-tests, ANOVA and other linear models.
AI supported Data Analysis
During this workshop we will chat about how best to leverage AI to help write code for statistical analysis. We will discuss validity, reliability, reproducibility and data safety.
Variable Selection
During this workshop we will discuss pros and cons of methods to approach data sets that have an overabundance of variables, such as stepwise selection, penalized regression and PCA.
What is a good model for the data?
During this workshop we will discuss how to approach the choice of an appropriate data analysis, how to check assumptions and how to assess goodness-of-fit as well as validity.
Data Projection and Ordination
During this workshop we will learn when and how to use data projection and ordination methods such as PCA and NMDA.
Non-parametric data analysis methods
During this workshop we will discuss methods for data that do not follow a known distribution.
Data Organization
During this workshop we will chat about best practices to organize, format, clean, manage and store data.
Data collection and Sample Size
During this workshop we will chat about data collection best practices including sampling, sources of bias and sample size.
Interpreting Statistical Output
During this workshop we will chat about how to interpret the output from a statistical analysis such as p-values and confidence intervals and parameter estimates.
Systematic Review and Meta Analysis
During this workshop we will chat about best practices when synthesizing results from cumulating studies.
Linear Models
During this workshop we will explore linear regression, t-tests, ANOVA and other linear models.