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Product Details:

  • ISBN-10 ‏ : ‎ 9780134496498
  • ISBN-13 ‏ : ‎ 978-0134496498
  • Author: Groebner

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

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