Solution Manual for Business Analytics Data Analysis and Decision Making 5th Edition by Albright

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Solution Manual for Business Analytics Data Analysis and Decision Making 5th Edition by Albright

 Solution Manual for Business Analytics Data Analysis and Decision Making 5th Edition by Albright

Become a master of data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 5E! This quantitative methods text provides users with the tools to succeed with a teach-by-example approach, student-friendly writing style, and complete Excel 2013 integration. It is also compatible with Excel 2010 and 2007. Problem sets and cases provide realistic examples to show the relevance of the material. The Companion Website includes: the Palisade DecisionTools Suite (@RISK, StatTools, PrecisionTree, TopRank, RISKOptimizer, NeuralTools, and Evolver); SolverTable, which allows you to do sensitivity analysis; data and solutions files, PowerPoint slides, and tutorial videos.

Sample questions asked in the 5th edition of Business Analytics:

Consider a random walk model with the following equation: Y t = Y t?1 + e t , where e t is a random series with mean 0 and standard deviation 1. Specify a moving average model that is equivalent to this random walk model. In particular, what is the appropriate span in the equivalent moving average model? What is the smoothing effect of this span?

The probability distribution of the weekly demand for copier paper (in hundreds of reams) used in the duplicating center of a corporation is provided in the file P04_27.xlsx. a. Find the mean and standard deviation of this distribution. b. Find the probability that weekly copier paper demand is at least one standard deviation above the mean. c. Find the probability that weekly copier paper demand is within one standard deviation of the mean.

The Undergraduate Data sheet of the file P10_21.xlsx contains information on 101 undergraduate business programs in the U.S., including various rankings by Business Week. Use multiple regression to explore the relationship between the median starting salary and the following set of potential explanatory variables: annual cost, full-time enrollment, faculty-student ratio, average SAT score, and average ACT score. Which explanatory variables should be included in a final version of this regression equation? Justify your choices. Is multicollinearity a problem? Why or why not?

Table of contents

Chapter 1:  What’s New in Excel 2010
Chapter 2: Range Names
Chapter 3: Lookup Functions
Chapter 4: The INDEX Function
Chapter 5: The MATCH Function
Chapter 6 Text Functions
Chapter 7 :Dates and Date Functions
Chapter 8;Evaluating Investments by Using Net Present Value Criteria
Chapter 9: Internal Rate of Return
Chapter10 :More Excel Financial Functions
Chapter 11 :Circular References
Chapter 12: IF Statements
Chapter 13: Time and Time Functions
Chapter 14 :The Paste Special Command 15 Three-Dimensional Formulas
Chapter 16: The Auditing Tool .
Chapter17: Sensitivity Analysis with Data Tables . .
Chapter 18: The Goal Seek Command .
Chapter 19: Using the Scenario Manager for Sensitivity Analysis .
Chapter 20: The COUNTIF, COUNTIFS, COUNT, COUNTA, andb COUNTBLANK Functions . .
Chapter 21: The SUMIF, AVERAGEIF, SUMIFS, and AVERAGEIFS
Chapter 22: The OFFSET Function . .
Chapter 23: The INDIRECT Function
Chapter 24: Conditional Formatting
Chapter 25: Sorting in Excel
Chapter 26: Tables
Chapter 27: Spin Buttons, Scroll Bars, Option Buttons, Check Boxes, Combo Boxes, and Group List Boxes
Chapter 28; An Introduction to Optimization with Excel Solver .
Chapter 29: Using Solver to Determine the Optimal Product Mix
Chapter 30: Using Solver to Schedule Your Workforce .
Chapter 31: Using Solver to Solve Transportation or Distribution
Chapter 32: Using Solver for Capital Budgeting
Chapter 33: Using Solver for Financial Planning
Chapter 34: Using Solver to Rate Sports Teams
Chapter 35: Warehouse Location and the GRG Multistart and Evolutionary Solver Engines
Chapter 36:Penalties and the Evolutionary Solver
Chapter 37: The Traveling Salesperson Problem
Chapter 38: Importing Data from a Text File or Document
Chapter 39: Importing Data from the Internet

Chapter 40: Validating Data
Chapter 41: Summarizing Data by Using Histograms
Chapter 42; Summarizing Data by Using Descriptive Statistics
Chapter 43: Using PivotTables and Slicers to Describe Data
Chapter 44 :Sparklines .
Chapter 45: Summarizing Data with Database Statistical Functions
Chapter 46: Filtering Data and Removing Duplicates
Chapter 47: Consolidating Data
Chapter 48: Creating Subtotals
Chapter 49: Estimating Straight Line Relationships
Chapter 50:: Modeling Exponential Growth
Chapter 51: The Power Curve .
Chapter 52: Using Correlations to Summarize Relationships .
Chapter 53: Introduction to Multiple Regression . . .
Chapter 54: Incorporating Qualitative Factors into Multiple
Chapter 55: Modeling Nonlinearities and Interactions
Chapter 56: Analysis of Variance: One-Way ANOVA
Chapter 57: Randomized Blocks and Two-Way ANOVA
Chapter 58: Using Moving Averages to Understand Time Series .
Chapter 59: Winters’s Method 60 Ratio-to-Moving-Average Forecast Method
Chapter 61: Forecasting in the Presence of Special Events.

Chapter 62 :An Introduction to Random Variables
Chapter 63: The Binomial, Hypergeometric, and Negative Binomial Random Variables

Chapter 64:The Poisson and Exponential Random Variable
Chapter 65: The Normal Random Variable .
Chapter 66: Weibull and Beta Distributions: Modeling Machine Life and Duration of a Project

Chapter 67: Making Probability Statements from Forecasts
Chapter 68: Using the Lognormal Random Variable to Model
Chapter 69: Introduction to Monte Carlo Simulation .
Chapter 70: Calculating an Optimal Bid
Chapter 71: Simulating Stock Prices and Asset Allocation Modeling
Chapter 72: Fun and Games: Simulating Gambling and Sporting
Chapter 73: Using Resampling to Analyze Data
Chapter 74: Pricing Stock Options
Chapter 75: Determining Customer Value
Chapter 76: The Economic Order Quantity Inventory Model
Chapter 77: Inventory Modeling with Uncertain Demand
Chapter 78: Queuing Theory: The Mathematics of Waiting in Line
Chapter 79: Estimating a Demand Curve
Chapter 80: Pricing Products by Using Tie-Ins
Chapter 81: Pricing Products by Using Subjectively Determined
Chapter 82: Nonlinear Pricing
Chapter 83; Array Formulas and Functions .
Chapter 84: PowerPivot

Product detail:

Language: English
ISBN:1133629601
ISBN-13:9781133629603
Authors:S Christian Albright, Connie Morrison, Wayne L Winston, Dolores Wells

If you have any questions, or would like a receive a sample chapter before your purchase, please contact us via email : support@digitalcontentmarket.org

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Solution Manual for Business Analytics Data Analysis and Decision Making 5th Edition by Albright