A Harris Corporation/University of Florida study was undertaken to determine whether a manufacturing process performed at a remote location could be established locally. Test devices (pilots) were setup at both the old and new locations, and voltage readings on the process were obtained. A ''good'' process was considered to be one with voltage readings of at least 9.2 volts (with larger readings better than smaller readings). The data set VOLTAGE contains voltage readings for 30 production runs at each location.

1. Look at the output: Based on the p-value (Sig) of the difference between the means, is the NEW location significantly different from the OLD location? May we reject the null hypothesis? Is it the same, worse, better in the NEW location?

2. Does it appear that the manufacturing process should be established locally

Group Statistics Std. Error LOCATION N Mean Std. Deviation Mean VOLTAGE OLD 30 9.8037 .54092 09876 NEW 30 9.4223 47888 08743 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 90% Confidence Interval of the Significance Mean Std. Error Difference F Sig. df One-Sided p Two-Sided p Difference Difference Lower Upper VOLTAGE Equal variances 085 771 2.891 58 .003 005 38133 13190 16086 60181 assumed Equal variances not 2.891 57.160 .003 .005 38133 .13190 .16081 60186 assumed Independent Samples Effect Sizes Point 90% Confidence Interval Standardizera Estimate Lower Upper VOLTAGE Cohen's d 51084 746 304 1.183 Hedges' correction 51756 .737 300 1.168 Glass's delta 47888 .796 332 1.248 a. The denominator used in estimating the effect sizes. Cohen's d uses the pooled standard deviation. Hedges' correction uses the pooled standard deviation, plus a correction factor. Glass's delta uses the sample standard deviation of the control group