Representación gráfica de datos con Excel, Numbers o Sheets

How does raw data become a plotted line showing a trend? Can trends be used to predict the future? Can I learn an easy way to analyze data on a computer?

Learners will become comfortable with a spreadsheet program (MS Excel, Google Sheets, Apple Numbers, etc.). They will learn to organize data, perform simple calculations, plot data graphically, and interpret the meaning of the plots. The goal is for each learner to use a spreadsheet program to successfully determine trends in data by plotting. We will emphasize the most common trend analysis technique known as "linear regression." 

This is a 3-week class with take home projects between class requiring 0.5-2 hours for each learner, depending on the level of familiarity with computer programs. Students are required to have a spreadsheet program installed in their computer and know how to launch/open the program before the first class. No background knowledge of data or spreadsheets is required. Learner progress will be evaluated based on two take home assignments plus participation in the hands on computer data analysis activities.

Week 1 will be an introduction to spreadsheet programs. Students will learn to enter data and perform simple calculations. We will have a hands-on workshop to load, process, and perform a simple graphical plot. There will be a take home exercise to plot a second set of data before the next class meeting.

Week 2 will explore adding trend lines to plotted data. We will have a hands on workshop to use the linear regression function in your spreadsheet program. We will learn to label plots appropriately so that they can be evaluated in a meaningful way. There will be a take home exercise to plot and graph a data set.

Week 3 will present how information can be obtained from plots. We will learn to evaluate whether or not trends exist in data. For cases in which a trend does exist, we will learn how to mathematically calculate or predict some future quantity based on historical data.