Statistics: Using Scatter Plots. Vocabulary. Bivariate Scatter Plot Positive Correlation Negative Correlation No Correlation. Scatter Plot. A set of bivariate (data with two variables) graphed as ordered pairs in a coordinate plane is called a scatter plot.
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You don’t connect the points in a scatter plot.
Scatter plots are similar to line graphs in that they use horizontal and vertical axes to plot data points. However, they have a very specific purpose. Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation .
To find a line of fit and a prediction equation for a set of data, select two points that appear to represent the data well. This is a matter of personal judgment, so your line and prediction equations may be different from someone else’s.
4. Calculate the slope of the line through your two points (rounded to three decimal places).
(9, 260) and (30, 530)
5. Write the equation of the line. This equation can now be used to predict information that was not plotted in the scatter plot.
1. Enter the data in the calculator lists. Place the data in L1 and L2. STAT, #1Edit, type values into the lists
2. Prepare a scatter plot of the data. Set up for the scatterplot. 2ndStatPlot- choose the first icon - choices
3. Have the calculator determine the line of best fit.STAT → CALC #4 LinReg(ax+b)
Include the parameters L1, L2, Y1. (Y1 comes from VARS → YVARS, #Function, Y1)
You now have the values of a and b needed to write the equation of the actual line of best fit. See values at the right. y = 11.73128088x + 193.8521475
To get a predicted value within the window, hit TRACE, up arrow, and type the desired value. The screen below shows x = 22.