Go to Graph -> Scatterplot and under "One Y Variable",Ĭlick on "Groups Overlaid" and then click "OK". Next investigate graphically whether boys and girls exhibit different growth patterns between age 2 and age 9. What is the equation of your regression line? Does linear regression seem appropriate for these data? Next try using linear regression to predict a child's height at age 18 from the child's height at age 9.What is the equation of your regression line? Based on your scatterplot and residual plot, does linear regression seem like an appropriate way to predict heights? Begin by using linear regression to predict a child's height at age 9 from the child's height at age 2.Minitab will provide you with a prediction (under "Fit"), a 95 percent confidence interval for the mean response for this value of the explanatory variable (under "95% CI"), and a 95 percent prediction interval for an individual response at this value of the explanatory variable (under "95% PI"). You can type in a value for the explanatory variable in the boxes provided under "Enter individual values". To obtain these intervals, after you have fit the regression model, go to Stat -> Regression -> Regression -> Predict. Minitab will also calculate confidence intervals for the mean response and prediction intervals for an individual response, given a particular value for the explanatory variable. You can also get a histogram or a normal probability plot of the residuals by checking the appropriate boxes. To make sure you get a residual plot along with your regression, click on "Graphs" and the put the explanatory variable in the box under "Residuals versus the variables". The standard errors for the estimated coefficients, and the t-statistic and p-value for the test that the slope is zero against a two-sided alternative. The table of output that you get will include not only the regression line but also the information that you need to do inference for the regression slope: Enter the Y-variable under "Responses" and the X-variable under "Continuous predictors". We will use instead Stat -> Regression -> Regression -> Fit Regression Model.
However, now that we want to do inference for regression, In Labs 2 and 3, you did linear regression by going to Stat -> Regression -> Fitted Line Plot. Recall that you can make scatterplots by going to Graph -> Scatterplot. Height of the child in centimeters at age 18 Weight of the child in kilograms at age 18 Height of the child in centimeters at age 9 Weight of the child in kilograms at age 9 Height of the child in centimeters at age 2 Weight of the child in kilograms at age 2 The results of the original study were published in. These children were measured at ages 2, 9, and 18. The study involved 136 children, all born in Berkeley, CA in 1928-1929. The data come from the Berkeley guidance study of children and were found here. Then log into Minitab and go to File -> Open -> Project to open the data file.
#CONFIDENCE INTERVAL MINITAB 18 HOW TO#
You will determine how to predict a child's height or weight at a later age from their height or weight at an earlier age.įirst, download the data set GROWTH, which is available in Canvas. In this lab, you will investigate how fast children grow. Math 11, Lab 8 Lab 8: Predicting children's growth (Regression inference)