252DoReg 4 23 07 Doing a Regression Assume that your dependent variable response in Minitab talk is in c1 and your independent variables predictors in Minitab are in c2 c3 and c4 You can always refer to them by their names if the columns are labeled The basic commands for a regression with 3 independent variables are Regress c1 3 c2 c3 c4 Stepwise c2 c1 c2 c3 BReg c1 c2 c3 c4 The stepwise and BReg commands are usful when you have a large number of independent variables and want to remove the least useful There are examples of commands like this in problems like 14 35 written up in pages like pp 9 11 etc in 252SolnK1 It is often easier to use the pull down menus in Minitab In the examples below I ran data from your disk provided with the text after downloading it with the labels provided by the data set To run regress I used the stat pull down menu and picked regression twice The only option I picked was Variance Inflation Factor In the example below the dependent variable Sales was in C2 and the independent variables DistCost and Orders in C1 and C3 4 19 2004 4 53 41 PM Welcome to Minitab press F1 for help 252cp403 4 19 04 MTB Retrieve C Documents and Settings RBOVE WCUPANET My Documents Drive D MINITAB Warecost MTW I used a pull down menu and open a new worksheet Retrieving worksheet from file C Documents and Settings RBOVE WCUPANET My Documents Drive D MINITAB Warecost MTW Worksheet was saved on Tue Dec 02 2003 Results for Warecost MTW MTB Regress c2 2 c1 c3 SUBC Constant Don t bother with this option it is put in automatically SUBC VIF This is the Variance inflation factor For interpretation see the text or the outline SUBC Brief 2 This is a default value too You can play around with brief 3 these control the amount of detail in the output and can be used to give you predicted values for Y Regression Analysis Sales versus DistCost Orders The regression equation is Sales 65 6 4 32 DistCost 0 0188 Orders Predictor Constant DistCost Orders S 45 66 Coef 65 64 4 323 0 01884 SE Coef 57 51 1 865 0 03272 R Sq 71 4 T 1 14 2 32 0 58 P 0 267 0 031 0 571 R Sq adj 68 6 VIF 6 4 6 4 Note that only the coeff of DistCost is significant Analysis of Variance Source DF SS MS F P 1 252DoReg 4 23 07 Regression Residual Error Total Source DistCost Orders 2 21 23 DF 1 1 109116 43776 152892 54558 2085 26 17 0 000 Seq SS 108425 691 Unusual Observations Obs DistCost Sales 14 72 3 328 00 Fit 461 65 SE Fit 9 37 Residual 133 65 St Resid 2 99R R denotes an observation with a large standardized residual Here I repeated the analysis using the stat pull down menu picked regression and then stepwise The subcommands were all generated by Minitab and would be what would have been used if I had just put in the first line as a command MTB Stepwise c2 c1 c3 SUBC AEnter 0 15 SUBC ARemove 0 15 SUBC Constant Stepwise Regression Sales versus DistCost Orders Alpha to Enter 0 15 Response is Sales Step Constant 1 78 09 DistCost 5 31 T Value P Value Alpha to Remove 0 15 on 2 predictors with N 24 The computer came up with Sales 78 09 5 31 DistCost and quit It decided that Orders had very weak explanatory power 7 32 0 000 S 45 0 R Sq 70 92 R Sq adj 69 59 C p 1 3 More Yes No Subcommand or Help SUBC y No variables entered or removed 2
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