Early Career Research Training Modules
Module 1: Intro to Excel / Google Sheets for Research and Basic Stats
In this module, students will learn to manage data and information on a spreadsheet and perform some introductory statistical analyses. Using spreadsheets will save them a lot of time, lets them be more in control of managing your data, and is a valuable workplace and research skill. The powerpoint file describes some active learning tasks for in class activities to teach about descriptive statistics and hypothesis testing. Links to self-paced introductory tutorials for using google sheets are also provided. Activities are based off of exercises described in Mathematics and Statistics in Biology and spreadsheet tutorials from HHMI BioInteractive.
Acknowledgements: Materials based on those from HHMI BioInteractive (https://www.biointeractive.org/), adapted by Paul Beardsley Via the Achieve Scholars Program at Cal Poly Pomona
Module 2: Asking Scientific Questions
This activity allows students to formulate and analyze scientific questions which sets an important frame for a “learn by doing” class. The activity begins with students observing different organisms or phenomena and developing questions based on their observations. Reflect on which questions can and cannot be answered using the methods of science. Students practice writing scientific questions, designing experiments to address scientific questions, developing questions that involve cause and effect, and understanding the importance of cause and effect questions in scientific research.
Acknowledgements: Materials based on those from HHMI BioInteractive (https://www.biointeractive.org/), adapted by Paul Beardsley Via the Achieve Scholars Program at Cal Poly Pomona
Module 3: Database Inquiry analysis
Analysis of large data sets are increasingly important components of scientific research. This activity is designed to expose undergraduate students to data sets and provide them with the opportunity to perform a full scientific inquiry. In this module, students using an existing data set will perform a full inquiry. Students will formulate a testable question, suggest specific data analysis that may provide answer and preform data analysis, and present their inquiry in a form of a poster.
Acknowledgements: Module Created by Nina Abramzon and Paul Beardsley Via the Achieve Scholars Program at Cal Poly Pomona
Module 4: Error analysis
After completing this module students should be able to understand the role error analysis plays in experimental science, identify possible sources of errors in an experiment and propagate estimate of error/uncertainty through calculations. Using a fun activity that can be used to introduce students to error analysis: the M&M game, students are told to estimate the number of individual candies plus uncertainty in a bag of M&M's. The winner is the group whose estimate brackets the actual number with the smallest uncertainty. The exercise produces enthusiastic discussions and serves as a good "mixer" for the first day of a laboratory class.
Acknowledgements: Module Created by Nina Abramzon Via the Achieve Scholars Program at Cal Poly Pomona