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This webinar provides a step-by-step walkthrough of your NSSE Institutional Report 2013. We review the redesigned reports and provide general strategies for utilizing and disseminating your results.
Join us for a step-by-step walkthrough of your NSSE Institutional Report 2014. We will review the redesigned reports and provide general strategies for utilizing and disseminating your results.
A step-by-step walkthrough of your NSSE Institutional Report 2015. We will review the redesigned reports and provide general strategies for utilizing and disseminating your results. NSSE webinars are live and interactive, providing participants the opportunity to ask questions via a text chat.
We hope you are eagerly poring over your NSSE 2016 results. To support your efforts, please join Jillian Kinzie and Bob Gonyea for a free webinar for a step-by-step walkthrough of your Institutional Report package. We will review the data and reports, and provide general strategies and resources for utilizing and disseminating your results.
We hope you're eagerly poring over your NSSE 2017 results. To support your efforts, please join Jillian and Bob for a step-by-step walkthrough of your Institutional Report package. We will review the data and reports, and provide general strategies and resources for utilizing and disseminating your results.
We hope you are eagerly poring over your NSSE 2018 results. To support your efforts, please join Jillian and Bob for a free webinar on Tuesday August 28, at 2:00 pm (Eastern) for a step-by-step walkthrough of your Institutional Report package. We will review the data and reports, and provide general strategies and resources for utilizing and disseminating your results.
We hope you’re eagerly poring over your NSSE 2019 results. Bob Gonyea and Jillian Kinzie will review the reports and provide strategies for utilizing and disseminating your results. NSSE webinars are live and interactive, providing participants the opportunity to ask questions via polls and text chat. When you register for the webinar you’ll be invited to submit questions in advance. Register here to participate.
This introductory workshop will walk through IBM SPSS and SAS JMP software while giving 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 (Correlation, T-test, ANOVA, Cross-tabs, etc), and how they should be selected based on the type of data and the type of research question you have. This is geared towards students or faculty beginning their foray into quantitative analysis of research data, would like an introduction to SPSS or JMP, or would just like to step back and get a framework for how to navigate “what analysis to use when.”
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 data set to work along also.
This introductory 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. This is geared towards students or faculty beginning their foray into quantitative analysis of research data, or those who have been around but would like to step back and get a framework for how to navigate basic statistical methods.