![]() The further away from the known x-values you are the less confidence you can have in the accuracy of the predicted y-values. When you use a line or an equation to approximate a value outside the range of known values it is called linear extrapolation. For this you have to use a computer or a graphing calculator. To find the most accurate best-fit line you have to use the process of linear regression. If the data points come close to the best-fit line then the correlation is said to be strong. Approximately half of the data points should be below the line and half of the points above the line. (Make sure the other plots are OFF.) For TYPE: highlight the very first icon, which is the scatter plot, and press ENTER. On the input screen for PLOT 1, highlight On and press ENTER. To help with the predictions you can draw a line, called a best-fit line that passes close to most of the data points. Enter your X X data into list L1 and your Y Y data into list L2. If there is, as in our first example above, no apparent relationship between x and y the paired data are said to have no correlation and x and y are said to be independent.įrom a scatter plot you can make predictions as to what will happen next. If y tends to increase as x increases, x and y are said to have a positive correlationĪnd if y tends to decrease as x increases, x and y are said to have a negative correlation These patterns are described in terms of linearity, slope, and. ![]() You can treat your data as ordered pairs and graph them in a scatter plot.Ī scatter plot is used to determine whether there is a relationship or not between paired data. Scatterplots are used to analyze patterns in bivariate data. You've summarized your result in a table. Let's say that you've the first of every month for one year been counting the amount of people on a subway platform each morning between 9 and 10 o'clock. ![]()
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