รูปภาพสินค้า รหัส9780321695093
9780321695093
-
ผู้เขียนPaul F. Velleman, Richard D. De Veaux, Norean R. Sharpe

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รหัสสินค้า: 9780321695093
จำนวน: 530 หน้า
ขนาดรูปเล่ม: 217 x 276 x 21 มม.
น้ำหนัก: 1320 กรัม
เนื้อในพิมพ์: คละสี 
ชนิดปก: ปกอ่อน 
ชนิดกระดาษ: กระดาษปอนด์ 
หน่วย: เล่ม 
สำนักพิมพ์: Pearson Education, Inc. 
:: เนื้อหาโดยสังเขป
This book is ideal for a one-semester course in business statistics, offering a streamlined presentation of Business Statistics, by Sharpe, De Veaux, and Velleman, with Excel® screenshots throughout the book.

Professors Norean Sharpe (Georgetown University), Dick De Veaux (Williams College), and Paul Velleman (Cornell University) have teamed up to provide an innovative new textbook for the undergraduate introductory business statistics course. These authors have taught at the finest business schools and draw on their consulting experience at leading companies to show students how statistical thinking is vital to modern decision making.

Managers make better business decisions when they understand statistics, and Business Statistics gives students the statistical tools and understanding to take them from the classroom to the boardroom. Hundreds of examples are based on current events and timely business topics. Short, accessible chapters allow for flexible coverage of important topics, and the conversational writing style maintains student interest and improves understanding.

Business Statistics includes Guided Examples that feature the authors' signature Plan/Do/Report problem-solving method. Each worked example shows students how to clearly define the business decision to be made and plan which method to use, do the calculations and create the graphs, and finally report their findings, often in the form of a business memo. Every chapter reminds students What Can Go Wrong and teaches them how to avoid making common statistical mistakes.
:: สารบัญ
Part 1 Exploring and Collecting Data
- Statistics and Variaton
- Data
- Surveys and Sampling
etc.

Part 2 Understanding Data and Distributions
- Randommess and Probability
- Random Variables and Probability Models
- Sampling Distributions and Confidence Intervals for Proportions
etc.

Part 3 Building Models for Decision Making
- Inference for Regression
- Multiple Regression
- Introduction to Data Mining