Applied Statistics for Software Managers
Applied Statistics for Software Managers is the first complete guide to using statistical techniques to solve specific software development and maintenance problems. You don't need a mathematical background; Katrina Maxwell presents an easy-to-follow methodology and detailed case studies that show you exactly how to assess productivity, time to market, development costs, maintenance cost drivers, and more.
What people are saying - Write a review
We haven't found any reviews in the usual places.
Software Development Productivity
Time to Market
8 other sections not shown
_cons accuracy acorreff ageend analyzed annual corrective maintenance ANOVA appdef application type average bank batch processing boxplots calculate categorical variables Chapter Coef confidence intervals Cook's distance corrective effort corrective maintenance effort correlation coefficient CustServ database DB2 IMS decreased efficiency requirements equation estimation errors Example Figure final model function points graphical user interface increasing InfServ leffort ln(effort lsize Mainfrm Relatnl TexlUl mean Model Residual Total models with Isize nlan normally distributed Number of obs number of observations numerical variables Pekka prod quality requirements t09 R-squared regression analysis relationship Relatnl TexlUl Inhouse requirements volatility t08 Root MSE significant software development software maintenance Source Model Residual Spearman's staff analysis skills staff team skills staff tool skills statistical output stepwise regression subapp subhar submorg subset Table Telon telonuse TexlUl Inhouse Cobol text user interface TextUI totfp transaction processing TransPro underestimate variance variation in effort Wilcoxon signed-rank test