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Business Statistics: A Decision Making Approachprovides you with an introduction to business statistics and to the analysis skills and techniques needed to make successful real-world business decisions. Written for students of all mathematical skill levels, the authors present concepts in a systematic and ordered way, drawing from their own experience as educators and consultants. Rooted in the theme that data are the starting point, Business Statistics champions the need to use and understand different types of data and data sources to be effective decision makers. This new edition integrates Microsoft Excel throughout as a way to work with statistical concepts and gives you a resource that can be used in both their academic and professional careers.

 

Table of Content:

  1. 1 The Where, Why, and How of Data Collection
  2. 1.1 What Is Business Statistics?
  3. Descriptive Statistics
  4. Charts and Graphs
  5. Inferential Procedures
  6. Estimation
  7. Hypothesis Testing
  8. 1.1 Exercises
  9. Skill Development
  10. Business Applications
  11. 1.2 Procedures for Collecting Data
  12. Primary Data Collection Methods
  13. Written Questionnaires and Surveys
  14. Direct Observation and Personal Interviews
  15. Other Data Collection Methods
  16. Data Collection Issues
  17. Data Accuracy
  18. Interviewer Bias
  19. Nonresponse Bias
  20. Selection Bias
  21. Observer Bias
  22. Measurement Error
  23. Internal Validity
  24. External Validity
  25. 1.2 Exercises
  26. Skill Development
  27. Business Applications
  28. 1.3 Populations, Samples, and Sampling Techniques
  29. Populations and Samples
  30. Parameters and Statistics
  31. Sampling Techniques
  32. Statistical Sampling
  33. 1.3 Exercises
  34. Skill Development
  35. Business Applications
  36. Computer Applications
  37. 1.4 Data Types and Data Measurement Levels
  38. Quantitative and Qualitative Data
  39. Time-Series Data and Cross-Sectional Data
  40. Data Measurement Levels
  41. Nominal Data
  42. Ordinal Data
  43. Interval Data
  44. Ratio Data
  45. 1.4 Exercises
  46. Skill Development
  47. Business Applications
  48. 1.5 A Brief Introduction to Data Mining
  49. Data Mining—Finding the Important, Hidden Relationships in Data
  50. 1 Overview
  51. Summary
  52. 1.1 What Is Business Statistics? (pg. 2-5)
  53. 1.2 Procedures for Collecting Data (pg. 5-13)
  54. 1.3 Populations, Samples, and Sampling Techniques (pg. 13-19)
  55. 1.4 Data Types and Data Measurement Levels (pg. 19-23)
  56. 1.5 A Brief Introduction to Data Mining (pg. 23-24)
  57. Key Terms
  58. Chapter Exercises
  59. Conceptual Questions
  60. Business Applications
  61. 2 Graphs, Charts, and Tables—Describing Your Data
  62. 2.1 Frequency Distributions and Histograms
  63. Frequency Distributions
  64. Real Estate Transactions
  65. Automobile Accidents
  66. Grouped Data Frequency Distributions
  67. Steps for Grouping Data into Classes
  68. Emergency Response Communication Links
  69. Histograms
  70. NBA Player Weights
  71. Relative Frequency Histograms and Ogives
  72. NBA Player Weights (continued)
  73. Joint Frequency Distributions
  74. Miami City Parking
  75. 2.1 Exercises
  76. Skill Development
  77. Business Applications
  78. Computer Software Exercises
  79. 2.2 Bar Charts, Pie Charts, and Stem and Leaf Diagrams
  80. Bar Charts
  81. Price/Earnings Ratios
  82. Pie Charts
  83. Golf Equipment
  84. Stem and Leaf Diagrams
  85. Walk-In Health Clinic
  86. 2.2 Exercises
  87. Skill Development
  88. Business Applications
  89. Computer Software Exercises
  90. 2.3 Line Charts, Scatter Diagrams, and Pareto Charts
  91. Line Charts
  92. Grogan Builders
  93. Scatter Diagrams
  94. Main Drive Taxi Service
  95. Pareto Charts
  96. 2.3 Exercises
  97. Skill Development
  98. Business Applications
  99. Computer Software Exercises
  100. 2 Overview
  101. Summary
  102. 2.1 Frequency Distributions and Histograms(pg. 29-49)
  103. 2.2 Bar Charts, Pie Charts, and Stem and Leaf Diagrams(pg. 50-59)
  104. 2.3 Line Charts, Scatter Diagrams, and Pareto Charts(pg. 59-67)
  105. Equations
  106. Key Terms
  107. Chapter Exercises
  108. Conceptual Questions
  109. Business Applications
  110. Computer Software Exercises
  111. 3 Describing Data Using Numerical Measures
  112. 3.1 Measures of Center and Location
  113. Parameters and Statistics
  114. Population Mean
  115. United Airlines
  116. Sample Mean
  117. Professor Salaries
  118. The Impact of Extreme Values on the Mean
  119. Professor Salaries (continued )
  120. Median
  121. Professor Salaries (continued )
  122. Skewed and Symmetric Distributions
  123. Professor Salaries (continued)
  124. Mode
  125. Smoky Mountain Pizza
  126. Applying the Measures of Central Tendency
  127. Issues with Excel
  128. Other Measures of Location
  129. Weighted Mean
  130. Myers & Associates
  131. Percentiles
  132. Henson Trucking
  133. Quartiles
  134. Issues with Excel
  135. Box and Whisker Plots
  136. Rental Car Company
  137. Developing a Box and Whisker Plot in Excel 2016
  138. Data-Level Issues
  139. 3.1 Exercises
  140. Skill Development
  141. Business Applications
  142. Computer Software Exercises
  143. 3.2 Measures of Variation
  144. Range
  145. Interquartile Range
  146. Verizon Wireless
  147. Population Variance and Standard Deviation
  148. Boydson Shipping Company
  149. Sample Variance and Standard Deviation
  150. Fabco Industries
  151. 3.2 Exercises
  152. Skill Development
  153. Business Applications
  154. Computer Software Exercises
  155. 3.3 Using the Mean and Standard Deviation Together
  156. Coefficient of Variation
  157. Agra-Tech Industries
  158. The Empirical Rule
  159. Tchebysheff’s Theorem
  160. Standardized Data Values
  161. SAT and ACT Exams
  162. 3.3 Exercises
  163. Skill Development
  164. Business Applications
  165. Computer Software Exercises
  166. 3 Overview
  167. Summary
  168. 3.1 Measures of Center and Location (pg. 74-94)
  169. 3.2 Measures of Variation (pg. 95-105)
  170. Using the Mean and Standard Deviation Together (pg. 106-113)
  171. Equations
  172. Key Terms
  173. Chapter Exercises
  174. Conceptual Questions
  175. Business Applications
  176. Computer Software Exercises
  177. 1-3 Special Review Section
  178. Chapters 1–3
  179. Exercises
  180. Integrative Application Exercises
  181. 4 Introduction to Probability
  182. 4.1 The Basics of Probability
  183. Important Probability Terms
  184. Events and Sample Space
  185. West Side Drive-In
  186. Using Tree Diagrams
  187. Clearwater Research
  188. KPMG Accounting
  189. Mutually Exclusive Events
  190. Contract-Works, Inc.
  191. Independent and Dependent Events
  192. Methods of Assigning Probability
  193. Classical Probability Assessment
  194. King’s Fine Clothes
  195. Relative Frequency Assessment
  196. Starbucks Coffee
  197. Potential Issues with the Relative Frequency Assessment Method
  198. Subjective Probability Assessment
  199. 4.1 Exercises
  200. Skill Development
  201. Business Applications
  202. Computer Software Exercises
  203. 4.2 The Rules of Probability
  204. Measuring Probabilities
  205. Possible Values and the Summation of Possible Values
  206. Addition Rule for Individual Outcomes
  207. KQRT 1340 Radio
  208. Complement Rule
  209. Capital Consulting
  210. Addition Rule for Any Two Events
  211. Greenfield Forest Products
  212. Addition Rule for Mutually Exclusive Events
  213. Conditional Probability
  214. Retirement Planning
  215. Tree Diagrams
  216. Conditional Probability for Independent Events
  217. Greenfield Forest Products (continued)
  218. Multiplication Rule
  219. Multiplication Rule for Any Two Events
  220. Using a Tree Diagram
  221. Multiplication Rule for Independent Events
  222. Christiansen Accounting
  223. Bayes’ Theorem
  224. Mammograms and Breast Cancer
  225. 4.2 Exercises
  226. Skill Development
  227. Business Applications
  228. Computer Software Exercises
  229. 4 Overview
  230. Summary
  231. 4.1 The Basics of Probability (pg. 129–141)
  232. 4.2 The Rules of Probability (pg. 141–164)
  233. Equations
  234. Key Terms
  235. Chapter Exercises
  236. Conceptual Questions
  237. Business Applications
  238. Computer Software Exercises
  239. 5 Discrete Probability Distributions
  240. 5.1 Introduction to Discrete Probability Distributions
  241. Random Variables
  242. Displaying Discrete Probability Distributions Graphically
  243. Mean and Standard Deviation of Discrete Distributions
  244. Calculating the Mean
  245. Calculating the Standard Deviation
  246. Swenson Security Sales
  247. 5.1 Exercises
  248. Skill Development
  249. Business Applications
  250. Computer Software Exercises
  251. 5.2 The Binomial Probability Distribution
  252. The Binomial Distribution
  253. Characteristics of the Binomial Distribution
  254. Combinations
  255. Binomial Formula
  256. Creative Style and Cut
  257. Using the Binomial Distribution Table
  258. Television Ratings
  259. Anderson Research
  260. Mean and Standard Deviation of the Binomial Distribution
  261. Mean of a Binomial Distribution
  262. Anderson Research (continued )
  263. Standard Deviation of a Binomial Distribution
  264. Anderson Research (continued )
  265. Additional Information about the Binomial Distribution
  266. 5.2 Exercises
  267. Skill Development
  268. Business Applications
  269. Computer Software Exercises
  270. 5.3 Other Probability Distributions
  271. The Poisson Distribution
  272. Characteristics of the Poisson Distribution
  273. Poisson Probability Distribution Table
  274. Fashion Leather Products
  275. The Mean and Standard Deviation of the Poisson Distribution
  276. The Hypergeometric Distribution
  277. Gender Equity
  278. The Hypergeometric Distribution with More Than Two Possible Outcomes per Trial
  279. Breakfast Cereal Preferences
  280. 5.3 Exercises
  281. Skill Development
  282. Business Applications
  283. Computer Software Exercises
  284. 5 Overview
  285. Summary
  286. 5.1 Introduction to Discrete Probability Distributions (pg. 173–180)
  287. 5.2 The Binomial Probability Distribution (pg. 180–192)
  288. 5.3 Other Probability Distributions (pg. 193–204)
  289. Equations
  290. Key Terms
  291. Chapter Exercises
  292. Conceptual Questions
  293. Business Applications
  294. Computer Software Exercises
  295. 6 Introduction to Continuous Probability Distributions
  296. 6.1 The Normal Distribution
  297. The Normal Distribution1
  298. The Standard Normal Distribution
  299. Using the Standard Normal Table
  300. Airline Passenger Loading Times
  301. Lockheed Martin
  302. Approximate Areas under the Normal Curve
  303. 6.1 Exercises
  304. Skill Development
  305. Business Applications
  306. Computer Software Exercises
  307. 6.2 Other Continuous Probability Distributions
  308. The Uniform Distribution
  309. Georgia-Pacific
  310. Surgery Recovery
  311. The Exponential Distribution
  312. 6.2 Exercises
  313. Skill Development
  314. Business Applications
  315. Computer Software Exercises
  316. 6 Overview
  317. Summary
  318. 6.1 The Normal Probability Distribution, (pg. 213-226)
  319. 6.2 Other Continuous Probability Distributions (pg. 226-232)
  320. Equations
  321. Key Terms
  322. Chapter Exercises
  323. Conceptual Questions
  324. Business Applications
  325. Computer Software Exercises
  326. 7 Introduction to Sampling Distributions
  327. 7.1 Sampling Error: What It Is and Why It Happens
  328. Calculating Sampling Error
  329. Smart Televisions
  330. The Role of Sample Size in Sampling Error
  331. 7.1 Exercises
  332. Skill Development
  333. Business Applications
  334. Computer Software Exercises
  335. 7.2 Sampling Distribution of the Mean
  336. Simulating the Sampling Distribution for
  337. Sampling from Normal Populations
  338. Scribner Products
  339. The Central Limit Theorem
  340. Westside Drive-In
  341. 7.2 Exercises
  342. Skill Development
  343. Business Applications
  344. Computer Software Exercises
  345. 7.3 Sampling Distribution of a Proportion
  346. Working with Proportions
  347. AT&T Acquisition of DirecTV
  348. Sampling Distribution of
  349. Craigslist
  350. 7.3 Exercises
  351. Skill Development
  352. Business Applications
  353. Computer Software Exercises
  354. 7 Overview
  355. Summary
  356. 7.1 Sampling Error: What It Is and Why It Happens(pg. 240-248)
  357. 7.2 Sampling Distribution of the Mean (pg. 248-262)
  358. 7.3 Sampling Distribution of a Proportion (pg. 262-270)
  359. Equations
  360. Key Terms
  361. Chapter Exercises
  362. Conceptual Questions
  363. Business Applications
  364. Computer Software Exercises
  365. 8 Estimating Single Population Parameters
  366. 8.1 Point and Confidence Interval Estimates for a Population Mean
  367. Point Estimates and Confidence Intervals
  368. Confidence Interval Estimate for the Population Mean, σ Known
  369. Confidence Interval Calculation
  370. Textbook Purchases
  371. Impact of the Confidence Level on the Interval Estimate
  372. National Recycling
  373. Impact of the Sample Size on the Interval Estimate
  374. Confidence Interval Estimates for the Population Mean, σ Unknown
  375. Student’s t-Distribution
  376. Internal Audit
  377. Estimation with Larger Sample Sizes
  378. 8.1 Exercises
  379. Skill Development
  380. Business Applications
  381. Computer Software Exercises
  382. 8.2 Determining the Required Sample Size for Estimating a Population Mean
  383. Determining the Required Sample Size for Estimating μ, σ Known
  384. United Meat Producers
  385. Determining the Required Sample Size for Estimating μ, σ Unknown
  386. Oceanside Petroleum
  387. 8.2 Exercises
  388. Skill Development
  389. Business Applications
  390. Computer Software Exercises
  391. 8.3 Estimating a Population Proportion
  392. Confidence Interval Estimate for a Population Proportion
  393. Royal Haciendas Resort
  394. Determining the Required Sample Size for Estimating a Population Proportion
  395. Naumann Research
  396. 8.3 Exercises
  397. Skill Development
  398. Business Applications
  399. Computer Software Exercises
  400. 8 Overview
  401. Summary
  402. 8.1 Point and Confidence Interval Estimates for a Population Mean (pg. 278-295)
  403. 8.2 Determining the Required Sample Size for Estimating a Population Mean (pg. 295−301)
  404. 8.3 Estimating a Population Proportion (pg. 301-309)
  405. Equations
  406. Key Terms
  407. Chapter Exercises
  408. Conceptual Questions
  409. Business Applications
  410. Computer Software Exercises
  411. 9 Introduction to Hypothesis Testing
  412. 9.1 Hypothesis Tests for Means
  413. Formulating the Hypotheses
  414. Null and Alternative Hypotheses
  415. Testing the Status Quo
  416. Testing a Research Hypothesis
  417. Testing a Claim about the Population
  418. Student Work Hours
  419. Nabisco Foods
  420. Types of Statistical Errors
  421. Significance Level and Critical Value
  422. Hypothesis Test for μ, σ Known
  423. Calculating Critical Values
  424. Mountain States Surgery Center
  425. Quality Car Care, Inc.
  426. p-Value Approach
  427. Dodger Stadium Parking
  428. Types of Hypothesis Tests
  429. p-Value for Two-Tailed Tests
  430. Hargrove Wood Products
  431. Hypothesis Test for μ, σ Unknown
  432. Dairy Fresh Ice Cream
  433. American Southern Fried Chicken
  434. 9.1 Exercises
  435. Skill Development
  436. Business Applications
  437. Computer Software Exercises
  438. 9.2 Hypothesis Tests for a Proportion
  439. Testing a Hypothesis about a Single Population Proportion
  440. The Developmental Basketball League
  441. 9.2 Exercises
  442. Skill Development
  443. Business Applications
  444. Computer Software Exercises
  445. 9.3 Type II Errors
  446. Calculating Beta
  447. Controlling Alpha and Beta
  448. Goldman Tax Software
  449. Davidson Tree and Landscape
  450. Small Business Startups
  451. Power of the Test
  452. 9.3 Exercises
  453. Skill Development
  454. Business Applications
  455. Computer Software Exercises
  456. 9 Overview
  457. Summary
  458. 9.1 Hypothesis Tests for Means (pg. 317-337)
  459. 9.2 Hypothesis Tests for a Proportion (pg. 338-344)
  460. 9.3 Type II Errors (pg. 344-354)
  461. Equations
  462. Key Terms
  463. Chapter Exercises
  464. Conceptual Questions
  465. Business Applications
  466. Computer Software Exercises
  467. 10 Estimation and Hypothesis Testing for Two Population Parameters
  468. 10.1 Estimation for Two Population Means Using Independent Samples
  469. Estimating the Difference between Two Population Means When σ1 and σ2 Are Known, Using Independent Samples
  470. Healthy Body
  471. Estimating the Difference between Two Population Means When σ1 and σ2 Are Unknown, Using Independent Samples
  472. Andreason Marketing, Inc.
  473. What If the Population Variances Are Not Equal?
  474. Citibank
  475. 10.1 Exercises
  476. Skill Development
  477. Business Applications
  478. Computer Software Exercises
  479. 10.2 Hypothesis Tests for Two Population Means Using Independent Samples
  480. Testing for μ1 − μ2 When σ1 and σ2 Are Known, Using Independent Samples
  481. Brooklyn Brick, Inc.
  482. Using p-Values
  483. Testing for μ1 − μ2 When σ1 and σ2 Are Unknown, Using Independent Samples
  484. Color Printer Ink Cartridges
  485. What If the Population Variances Are Not Equal?
  486. 10.2 Exercises
  487. Skill Development
  488. Business Applications
  489. Computer Software Exercises
  490. 10.3 Interval Estimation and Hypothesis Tests for Paired Samples
  491. Why Use Paired Samples?
  492. PGA of America Testing Center
  493. Hypothesis Testing for Paired Samples
  494. Color Printer Ink
  495. 10.3 Exercises
  496. Skill Development
  497. Business Applications
  498. Computer Software Exercises
  499. 10.4 Estimation and Hypothesis Tests for Two Population Proportions
  500. Estimating the Difference between Two Population Proportions
  501. Hypothesis Tests for the Difference between Two Population Proportions
  502. Transportation Security Administration
  503. 10.4 Exercises
  504. Skill Development
  505. Business Applications
  506. Computer Software Exercises
  507. 10 Overview
  508. Summary
  509. 10.1 Estimation for Two Population Means Using Independent Samples (pg. 364-374)
  510. 10.2 Hypothesis Tests for Two Population Means Using Independent Samples (pg. 374-386)
  511. 10.3 Interval Estimation and Hypothesis Tests for Paired Samples (pg. 386-394)
  512. 10.4 Estimation and Hypothesis Tests for Two Population Proportions (pg. 395-401)
  513. Equations
  514. Key Terms
  515. Chapter Exercises
  516. Conceptual Questions
  517. Business Applications
  518. Computer Software Exercises
  519. 11 Hypothesis Tests and Estimation for Population Variances
  520. 11.1 Hypothesis Tests and Estimation for a Single Population Variance
  521. Chi-Square Test for One Population Variance
  522. Lockheed Martin Corporation
  523. Genesis Technology
  524. Interval Estimation for a Population Variance
  525. 11.1 Exercises
  526. Skill Development
  527. Business Applications
  528. Computer Software Exercises
  529. 11.2 Hypothesis Tests for Two Population Variances
  530. F-Test for Two Population Variances
  531. Mass Transit
  532. Goodyear Tire Company
  533. 11.2 Exercises
  534. Skill Development
  535. Business Applications
  536. Computer Software Exercises
  537. 11 Overview
  538. Summary
  539. 11.1 Hypothesis Tests and Estimation for a Single Population Variance (pg. 411–419)
  540. 11.2 Hypothesis Tests for Two Population Variances (pg. 420–429)
  541. Equations
  542. Key Term
  543. Chapter Exercises
  544. Conceptual Questions
  545. Business Applications
  546. Computer Software Exercises
  547. 12 Analysis of Variance
  548. 12.1 One-Way Analysis of Variance
  549. Introduction to One-Way ANOVA
  550. Partitioning the Sum of Squares
  551. The ANOVA Assumptions
  552. Applying One-Way ANOVA
  553. Roderick, Wilterding & Associates
  554. The Tukey-Kramer Procedure for Multiple Comparisons
  555. Digitron, Inc.
  556. Fixed Effects Versus Random Effects in Analysis of Variance
  557. 12.1 Exercises
  558. Skill Development
  559. Business Applications
  560. Computer Software Exercises
  561. 12.2 Randomized Complete Block Analysis of Variance
  562. Randomized Complete Block ANOVA
  563. Was Blocking Necessary?
  564. Online Course Exams
  565. Fisher’s Least Significant Difference Test
  566. Online Course Exams (continued)
  567. 12.2 Exercises
  568. Skill Development
  569. Business Applications
  570. Computer Software Exercises
  571. 12.3 Two-Factor Analysis of Variance with Replication
  572. Two-Factor ANOVA with Replications
  573. Interaction Explained
  574. A Caution about Interaction
  575. 12.3 Exercises
  576. Skill Development
  577. Business Applications
  578. Computer Software Exercises
  579. 12 Overview
  580. Summary
  581. 12.1 One-Way Analysis of Variance (pg. 435–453)
  582. 12.2 Randomized Complete Block Analysis of Variance (pg. 453–464)
  583. 12.3 Two-Factor Analysis of Variance with Replication (pg. 464–473)
  584. Equations
  585. Key Terms
  586. Chapter Exercises
  587. Conceptual Questions
  588. Business Applications
  589. Computer Software Exercises
  590. 8–12 Special Review Section
  591. Chapters 8–12
  592. Using the Flow Diagrams
  593. Exercises
  594. Integrative Application Problems
  595. 13 Goodness-of-Fit Tests and Contingency Analysis
  596. 13.1 Introduction to Goodness-of-Fit Tests
  597. Chi-Square Goodness-of-Fit Test
  598. Central University Food Service
  599. Call Center Support,
  600. University Internet Service
  601. 13.1 Exercises
  602. Skill Development
  603. Business Applications
  604. Computer Software Exercises
  605. 13.2 Introduction to Contingency Analysis
  606. 2 × 2 Contingency Tables
  607. Jury Selection
  608. r × c Contingency Tables
  609. Chi-Square Test Limitations
  610. 13.2 Exercises
  611. Skill Development
  612. Business Applications
  613. Computer Software Exercises
  614. 13 Overview
  615. Summary
  616. 13.1 Introduction to Goodness-of-Fit Tests (pg. 498-510)
  617. 13.2 Introduction to Contingency Analysis (pg. 510-520)
  618. Equations
  619. Key Term
  620. Chapter Exercises
  621. Conceptual Questions
  622. Business Applications
  623. Computer Software Exercises
  624. 14 Introduction to Linear Regression and Correlation Analysis
  625. 14.1 Scatter Plots and Correlation
  626. The Correlation Coefficient
  627. Stock Portfolio Analysis
  628. Cause-and-Effect Interpretations
  629. 14.1 Exercises
  630. Skill Development
  631. Business Applications
  632. Computer Software Exercises
  633. 14.2 Simple Linear Regression Analysis
  634. The Regression Model Assumptions
  635. Meaning of the Regression Coefficients
  636. Least Squares Regression Properties
  637. Foresight Investments
  638. Significance Tests in Regression Analysis
  639. Significance of the Slope Coefficient
  640. 14.3 Uses for Regression Analysis
  641. Regression Analysis for Description
  642. Home Prices
  643. Regression Analysis for Prediction
  644. Confidence Interval for the Average y, Given x
  645. Prediction Interval for a Particular y, Given x
  646. Common Problems Using Regression Analysis
  647. 14.3 Exercises
  648. Skill Development
  649. Business Applications
  650. Computer Software Exercises
  651. 14 Overview
  652. Summary
  653. 14.1 Scatter Plots and Correlation (pg. 527-536)
  654. 14.2 Simple Linear Regression Analysis (pg. 536-554)
  655. 14.3 Uses for Regression Analysis (pg. 554-564)
  656. Equations
  657. Key Terms
  658. Chapter Exercises
  659. Conceptual Questions
  660. Business Applications
  661. Computer Software Exercises
  662. 15 Multiple Regression Analysis and Model Building
  663. 15.1 Introduction to Multiple Regression Analysis
  664. Basic Model-Building Concepts
  665. Model Specification
  666. Model Building
  667. First City Real Estate
  668. Computing the Regression Equation
  669. The Coefficient of Determination
  670. Model Diagnosis
  671. Is the Model Significant?
  672. Are the Individual Variables Significant?
  673. Is the Standard Deviation of the Regression Model Too Large?
  674. Is Multicollinearity a Problem?
  675. Confidence Interval Estimation for Regression Coefficients
  676. 15.1 Exercises
  677. Skill Development
  678. Computer Software Exercises
  679. 15.2 Using Qualitative Independent Variables
  680. Salary Analysis
  681. 15.3 Working with Nonlinear Relationships
  682. Ashley Investment Services
  683. Analyzing Interaction Effects
  684. Partial F-Test
  685. 15.3 Exercises
  686. Skill Development
  687. Computer Software Exercises
  688. 15.4 Stepwise Regression
  689. Forward Selection
  690. Backward Elimination
  691. B.T. Longmont Company
  692. Standard Stepwise Regression
  693. Best Subsets Regression
  694. Winston Investment Advisors
  695. 15.4 Exercises
  696. Skill Development
  697. Computer Software Exercises
  698. 15.5 Determining the Aptness of the Model
  699. Analysis of Residuals
  700. Checking for Linearity
  701. Do the Residuals Have Equal Variances at All Levels of Each x Variable?
  702. Are the Residuals Independent?
  703. Checking for Normally Distributed Error Terms
  704. Corrective Actions
  705. 15.5 Exercises
  706. Skill Development
  707. Computer Software Exercises
  708. 15 Overview
  709. Summary
  710. 15.1 Introduction to Multiple Regression Analysis (pg. 574-590)
  711. 15.2 Using Qualitative Independent Variables (pg. 590–597)
  712. 15.3 Working with Nonlinear Relationships (pg. 597-610)
  713. 15.4 Stepwise Regression (pg. 611-618)
  714. Determining the Aptness of the Model (pg. 618-627)
  715. Equations
  716. Key Terms
  717. Chapter Exercises
  718. Conceptual Questions
  719. Computer Software Exercises
  720. 16 Analyzing and Forecasting Time-Series Data
  721. 16.1 Introduction to Forecasting and Time-Series Data
  722. General Forecasting Issues
  723. Components of a Time Series
  724. Trend Component
  725. Seasonal Component
  726. Cyclical Component
  727. Random Component
  728. Introduction to Index Numbers
  729. Cranston Supplies, Inc.
  730. Using Index Numbers to Deflate a Time Series
  731. 16.1 Exercises
  732. Skill Development
  733. Business Applications
  734. Computer Software Exercises
  735. 16.2 Trend-Based Forecasting Techniques
  736. Developing a Trend-Based Forecasting Model
  737. Comparing the Forecast Values to the Actual Data
  738. Autocorrelation
  739. Wilder Foods, Inc.
  740. True Forecasts and Split Samples
  741. Nonlinear Trend Forecasting
  742. Some Words of Caution
  743. Adjusting for Seasonality
  744. Computing Seasonal Indexes
  745. The Need to Normalize the Indexes
  746. Deseasonalizing
  747. 16.2 Exercises
  748. Skill Development
  749. Business Applications
  750. Computer Software Exercises
  751. 16.3 Forecasting Using Smoothing Methods
  752. Exponential Smoothing
  753. Single Exponential Smoothing
  754. Dawson Graphic Design
  755. Double Exponential Smoothing
  756. Billingsley Insurance Company
  757. Forecasting with Excel 2016
  758. Billingsley Insurance Company (continued)
  759. 16.3 Exercises
  760. Skill Development
  761. Business Applications
  762. Computer Software Exercises
  763. 16 Overview
  764. Summary
  765. 16.1 Introduction to Forecasting and Time-Series Data (pg. 637−644)
  766. 16.2 Trend-Based Forecasting Techniques (pg. 644−666)
  767. 16.3 Forecasting Using Smoothing Methods (pg. 667−680)
  768. Equations
  769. Key Terms
  770. Chapter Exercises
  771. Conceptual Questions
  772. Business Applications
  773. Computer Software Exercises
  774. 17 Introduction to Nonparametric Statistics
  775. 17.1 The Wilcoxon Signed Rank Test for One Population Median
  776. The Wilcoxon Signed Rank Test—Single Population
  777. Executive Salaries
  778. 17.1 Exercises
  779. Skill Development
  780. Business Applications
  781. Computer Software Exercises
  782. 17.2 Nonparametric Tests for Two Population Medians
  783. The Mann−Whitney U-Test
  784. Mann−Whitney U-Test—Large Samples
  785. The Wilcoxon Matched-Pairs Signed Rank Test
  786. Financial Software Associates
  787. Ties in the Data
  788. Large-Sample Wilcoxon Test
  789. 17.2 Exercises
  790. Skill Development
  791. Business Applications
  792. Computer Software Exercises
  793. 17.3 Kruskal−Wallis One-Way Analysis of Variance
  794. Amalgamated Sugar
  795. Limitations and Other Considerations
  796. 17.3 Exercises
  797. Skill Development
  798. Business Applications
  799. Computer Software Exercises
  800. 17 Overview
  801. Summary
  802. 17.1 The Wilcoxon Signed Rank Test for One Population Median (pg. 688-693)
  803. 17.2 Nonparametric Tests for Two Population Medians (pg. 693-705)
  804. 17.3 Kruskal−Wallis One-Way Analysis of Variance (pg. 705-711)
  805. Equations
  806. Chapter Exercises
  807. Conceptual Questions
  808. Business Applications
  809. Computer Software Exercises
  810. 18 Introducing Business Analytics
  811. 18.1 What Is Business Analytics?
  812. Descriptive Analytics
  813. Predictive Analytics
  814. 18.1 Exercises
  815. Conceptual Questions
  816. Business Applications
  817. 18.2 Data Visualization Using Microsoft Power BI Desktop
  818. Using Microsoft Power BI Desktop
  819. The Opening Power BI Screen
  820. Getting the Data
  821. Relationships among the Data Tables
  822. Creating a Visualization
  823. Creating New Variables
  824. Creating a Measure
  825. Creating Multiple-Page Reports
  826. 18.2 Exercises
  827. Computer Software Exercises
  828. 18 Overview
  829. Summary
  830. 18.1 What Is Business Analytics? (pg. 719-725)
  831. 18.2 Data Visualization Using Microsoft Power BI Desktop (pg. 725-740)
  832. Key Terms
  833. Appendix Tables
  834. Appendix A Random Numbers Table
  835. Appendix B Cumulative Binomial Distribution Table
  836. Appendix C Cumulative Poisson Probability Distribution Table
  837. Appendix D Standard Normal Distribution Table
  838. Appendix E Exponential Distribution Table
  839. Appendix F Values of t for Selected Probabilities
  840. Appendix G Values of χ2 for Selected Probabilities
  841. Appendix H F-Distribution Table: Upper 5% Probability (or 5% Area) under F-Distribution Curve
  842. Appendix H (continued) F-Distribution Table: Upper 2.5% Probability (or 2.5% Area) under F-Distribution Curve
  843. Appendix H (continued) F-Distribution Table: Upper 1% Probability (or 1% Area) under F-Distribution Curve
  844. Appendix I Distribution of the Studentized Range (q-values)
  845. Appendix J Critical Values of r in the Runs Test
  846. Appendix K Mann-Whitney U Test Probabilities (n < 9)
  847. Appendix L Mann-Whitney U Test Critical Values (9 ≤ n ≤ 20)
  848. Appendix M Critical Values of T in the Wilcoxon Matched-Pairs Signed-Ranks Test (n ≤ 25)
  849. Appendix N Critical Values dL and dU of the Durbin-Watson Statistic D (Critical Values Are One-Sided)
  850. Appendix O Lower and Upper Critical Values W of Wilcoxon Signed-Ranks Test
  851. Appendix P Control Chart Factors
  852. Answers to Selected Odd-Numbered Exercises
  853. Chapter 1
  854. Chapter 2
  855. Chapter 3
  856. Chapter 4
  857. Chapter 5
  858. Chapter 6
  859. Chapter 7
  860. Chapter 8
  861. Chapter 9
  862. Chapter 10
  863. Chapter 11
  864. Chapter 12
  865. Chapter 13
  866. Chapter 14
  867. Chapter 15
  868. Chapter 16
  869. Chapter 17
  870. Chapter 18
  871. References
  872. Glossary
  873. Index
  874. A
  875. B
  876. C
  877. D
  878. E
  879. F
  880. G
  881. H
  882. I
  883. J
  884. K
  885. L
  886. M
  887. N
  888. O
  889. P
  890. Q
  891. R
  892. S
  893. T
  894. U
  895. V
  896. W
  897. Z
  898. Credits
  899. Photographs
  900. Frontmatter
  901. Chapter 1
  902. Chapter 2
  903. Chapter 3
  904. Chapter 4
  905. Chapter 5
  906. Chapter 6
  907. Chapter 7
  908. Chapter 8
  909. Chapter 9
  910. Chapter 10
  911. Chapter 11
  912. Chapter 12
  913. Chapter 13
  914. Chapter 14
  915. Chapter 15
  916. Chapter 16
  917. Chapter 17
  918. Chapter 18
  919. Figures
  920. Chapters 1–18
  921. Chapter 1
  922. Chapter 2
  923. Chapter 5
  924. Chapter 9
  925. Chapter 10
  926. Chapter 16

 

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