Watch the video or read the steps below:
TI 83 Scatter Plot: Overview
Making a scatter plot on a TI-83 graphing calculator is a breeze with the easy to use LIST menu. In order to graph a TI 83 scatter plot, you’ll need a set of bivariate data. Bivariate data is a set of data that you can plot on an XY axis: you’ll need a list of “x” values (for example, weight) and a list of “y” values (for example, height). The XY values can be in two separate lists, or they can be written as XY cordinates (x,y). Once you have those, it’s as easy as typing the lists into the calculator, and choosing your graph.
TI 83 Scatter Plot: Steps
Sample problem: Create a TI 83 scatter plot for the following coordinates (2,3), (4,4), (6,9), (8,11), and (10,12).
Step 1: Press STAT, then press ENTER to enter the lists screen. If you already have data in L1 or L2, clear the data: move to cursor onto L1, press CLEAR and then ENTER. Repeat for L2.
Step 2: Enter your x-variables, one at a time. Follow each number by pressing the ENTER key. For our list, you would enter:
Step 3: Use the arrow keys to scroll across to the next column, L2.
Step 4: Enter your y-variables, one at a time. Follow each number by pressing the enter key. For our list, you would enter:
Step 5: Press 2nd, then press STATPLOT (the Y= key).
Step 6: Press ENTER to enter StatPlots for Plot1.
Step 7: Press ENTER to turn Plot1 “ON.”
Step 8: Arrow down to the next line (“Type”) and highlight the scatter plot (the first image). Press ENTER.
Step 9: Arrow down to “Xlist.” If “L1” isn’t showing, press 2nd and 1. Arrow down to “Ylist.” If “L2” isn’t showing, press 2nd and 2.
Step 10: Press ZOOM then 9. This should bring up a scatter plot on your screen.
Tip: Hit TRACE and press the right and left arrow buttons to move from point to point, displaying the XY values for those points.
That’s how to make a TI 83 Scatter Plot!
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If you prefer an online interactive environment to learn R and statistics, this free R Tutorial by Datacamp is a great way to get started. If you're are somewhat comfortable with R and are interested in going deeper into Statistics, try this Statistics with R track.Comments are now closed for this post. Need help or want to post a correction? Please post a comment on our Facebook page and I'll do my best to help!