Technology 1. Checking conditions for linear regression 2. Linear regression t-test After performing linear regression, plot Enter data intonL1 and L2. residuals as detailed in Chapter 3. Check to confirm sum of residuals is 0. Press [STAT] <TESTS> F:LinRegTTest Another way to do this is to use the SUM( command and the variable RESID. Type [2nd] [STAT] (LIST) <MATH> 5:SUM( Press [ENTER] [ENTER] and then type [2nd] [STAT] (LIST) <NAMES> and choose RESID and [ENTER] In the LinRegTTest screen, specify L1 for Xlist and L2 for Ylist and for the ≠0 hypothesized slope. Highlight the command Calculate and press [ENTER]. The linear regression t test results take two screens to present Modeling exponential growth Enter the exponential data into L1 and L2. Perform regression on the Plot shows exponential growth transformed data and graph the plot again with the regression line. Define L3 as the natural logarithm of L2. Construct and inspect the residual plot. Make a scatterplot of L1 and L3. To use the model to predict, define Y2 = e^(Y1) then enter x-values in Y2( ) and [ENTER]. For example, to predict a for an x of 33, enter Y2(33).
Technology 1. Checking conditions for linear regression After performing linear regression, plot residuals as detailed in Chapter 3. Check to confirm sum of residuals is 0. Another way to do this is to use the SUM( command and the variable RESID. Type [2nd] [STAT] (LIST) <MATH> 5:SUM( [ENTER] and then type [2nd] [STAT] (LIST) <NAMES> and choose RESID and [ENTER] 2. Linear regression t-test Enter data intonL1 and L2. Press [STAT] <TESTS> F:LinRegTTest Press [ENTER] In the LinRegTTest screen, specify L1 for Xlist and L2 for Ylist and ≠0 for the hypothesized slope. Highlight the command Calculate and press [ENTER]. The linear regression t test results take two screens to present Modeling exponential growth Enter the exponential data into L1 and L2. Plot shows exponential growth Define L3 as the natural logarithm of L2. Make a scatterplot of L1 and L3. Perform regression on the transformed data and graph the plot again with the regression line. Construct and inspect the residual plot. To use the model to predict, define Y2 = e^(Y1) then enter x-values in Y2( ) and [ENTER]. For example, to predict a for an x of 33, enter Y2(33).
notes_to_accompany_ap_stats_s2018_010718.docx