04623cam a2200361 a 4500 0 0 ddc 0 0 DATA MES MES COMP 2022-09-26 53 740.00 0 005.54 WIN/M 41592 2022-09-26 00:00:00 740.00 2022-09-26 BK GL33R2 41548 41548 16419250 OSt 20221001112459.0 100816s2011 waua 001 0 eng d 2010934987 GBB095385 bnb 015623687 Uk 9780735643369 (pbk.) (OCoLC)ocn650216020 BTCTA eng BTCTA YDXCP WIM SINLB YOU CDX EEK UKM BWX COA DLC lccopycat HD30.215 .W563 2011 005.54 22 WIN/M Winston, Wayne L 3960 Microsoft Excel 2010 : data analysis and business modeling / Wayne L. Winston. Excel 2010 : data analysis and business modeling Redmond, Wash. : Microsoft Press, c2011. xv, 700 p. : ill. ; 23 cm. Includes index. What's new in Excel 2010 -- Range names -- Lookup functions -- The INDEX function -- The MATCH function -- Text functions -- Dates and date functions -- Evaluating investments by using net present value criteria -- Internal rate of return -- More Excel financial functions -- Circular references -- IF statements -- Time and time functions -- The paste special command -- Three-dimensional formulas -- The auditing tool -- Sensitivity analysis with data tables -- The goal seek command -- Using the scenario manager for sensitivity analysis -- The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK Functions -- The SUMIF, AVERAGEIF, SUMIFS, and AVERAGEIFS functions -- The OFFSET function -- The INDIRECT function -- Conditional formatting -- Sorting in Excel -- Tables -- Spin buttons, scroll bars, option buttons, check boxes, combo boxes, and group list boxes -- An introduction to optimization with Excel Solver -- Using Solver to determine the optimal product mix -- Using Solver to schedule your workforce -- Using Solver to solve transportation or distribution problems -- Using Solver for capital budgeting -- Using Solver for financial planning -- Using Solver to rate sports teams -- Warehouse location and the GRG multistart and Evolutionary Solver engines -- Penalties and the Evolutionary Solver -- The traveling salesperson problem -- Importing data from a text file or document -- Importing data from the internet -- Validating data -- Summarizing data by using histograms -- Summarizing data by using descriptive statistics -- Using PivotTables and slicers to describe data -- Sparklines -- Summarizing data with database statistical functions -- Filtering data and removing duplicates -- Consolidating data -- Creating subtotals -- Estimating straight line relationships -- Modeling exponential growth -- The power curve -- Using correlations to summarize relationships -- Introduction to multiple regression -- Incorporating qualitative factors into multiple regression -- Modeling nonlinearities and interactions -- Analysis of variance: one-way ANOVA -- Randomized blocks and two-way ANOVA -- Using moving averages to understand time series -- Winters's method -- Ratio-to-moving-average forecast method -- Forecasting in the presence of special events -- An introduction to random variables -- The binomial, hypergeometric, and negative binomial random variables -- The Poisson and exponential random variable -- The normal random variable -- Weibull and beta distributions: modeling machine life and duration of a project -- Making probability statements from forecasts -- Using the lognormal random variable to model stock prices -- Introduction to Monte Carlo simulation -- Calculating an optimal bid -- Simulating stock prices and asset allocation modeling -- Fun and games: simulating gambling and sporting event probabilities -- Using resampling to analyze data -- Pricing stock options -- Determining customer value -- The economic order quantity inventory model -- Inventory modeling with uncertain demand -- Queuing theory: the mathematics of waiting in line -- Estimating a demand curve -- Pricing products by using tie-ins -- Pricing products by using subjectively determined demand -- Nonlinear pricing -- Array formulas and functions -- PowerPivot. Microsoft Excel (Computer file) Industrial management Statistical methods Computer programs. Decision making Computer programs. 7 cbc copycat 2 epcn 20 y-gencatlg ddc BK 005.54 WIN/M 005.54 WIN/M