Date & Time: Pre-recorded (previously delivered in the Texas A&M Superfund Big Data Series 2021)
Instructors:
- Fred Wright | North Carolina State University’s Bioinformatics Research Center | fred_wright@ncsu.edu
- Candice Brinkmeyer-Langford | Texas A&M’s Department of Veterinary Integrative Biosciences | cbrinkmeyer@cvm.tamu.edu
- Dillon Lloyd | North Carolina State University’s Bioinformatics Research Center | dtlloyd@ncsu.edu
Manipulating Big(ish) Data in Excel and Reading into R
Learning Objectives:
- Become familiar with Excel basic functions such as good naming practices and working with large datasets
- Identify and use Excel functions appropriately, including nested functions (e.g. AVERAGEIF, VLOOKUP, etc.)
- Develop charts and graphs to effectively present research data
- Use Excel for linear regression, t-testing, and other basic statistical tests
- Transfer data from Excel to R for further analysis
Session Content:
This session will provide a tutorial on some of the most commonly used and useful aspects of Microsoft Excel, with examples that are relevant to bench scientists and environmental researchers. After a basic refresher, we will offer an overview of graphing and statistical analysis. We assume basic familiarity with Excel and cover some practical tips for interfacing with data scientists.
- The Basics
- An Excel refresher: adding/reading data, etc.
- Good naming practices
- Working with functions
- Working with lists
- Pivot tables
- Multiple worksheets
- Functions & Charting
- Using nested IF functions (COUNTIF, AVERAGEIF)
- Using LOOKUP/VLOOKUP
- Charting Data in Excel
- Basic graphs (e.g. bar charts, scatterplots)
- 3D graphs
- Stacked bar charts
- Adding a secondary axis
- Histograms
- Statistics & Exporting Data
- Linear regression
- T-Tests
- Analysis of variance
- Exporting data from Excel and into R
Session Recording:
Download Slide Deck (PDF) | Download Supporting Files (ZIP) (right-click and save file)
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