Statistics for business: decision making and analysis
Stine, Robert A.
Statistics for business: decision making and analysis - 3rd - Noida Pearson India Education Services Pvt. Ltd. 2022 - xxii, 830 p.
Table of Content
I. Variation
1. Introduction
2. Data
3. Describing Categorical Data
4. Describing Numerical Data
5. Association Between Categorical Variables
6. Association Between Quantitative Variables
II. Probability
7. Probability
8. Conditional Probability
9. Random Variables
10. Association Between Random Variables
11. Probability Models for Counts
12. The Normal Probability Model
III. Inference
13. Samples and Surveys
14. Sampling Variation and Quality
15. Confidence Intervals
16. Statistical Tests
17. Comparison
18. Inference for Counts
IV. Regression Models
19. Linear Patterns
20. Curved Patterns
21. The Simple Regression Model
22. Regression Diagnostics
23. Multiple Regression
24. Building Regression Models
25. Categorical Explanatory Variables
26. Analysis of Variance
27. Time Series
The 3rd Edition of Statistics for Business: Decision Making and Analysis emphasizes an application-based approach, in which students learn how to work with data to make decisions. In this contemporary presentation of business statistics, students learn how to approach business decisions through a 4M Analytics decision making strategy-motivation, method, mechanics and message-to better understand how a business context motivates the statistical process and how the results inform a course of action. Each chapter includes hints on using Excel, Minitab Express, and JMP for calculations, pointing the student in the right direction to get started with analysis of data.
9789353940645
Commercial statistics
Business planning
Industrial management--Statistical methods
Problem solving--Statistical methods
519.502465 / STI
Statistics for business: decision making and analysis - 3rd - Noida Pearson India Education Services Pvt. Ltd. 2022 - xxii, 830 p.
Table of Content
I. Variation
1. Introduction
2. Data
3. Describing Categorical Data
4. Describing Numerical Data
5. Association Between Categorical Variables
6. Association Between Quantitative Variables
II. Probability
7. Probability
8. Conditional Probability
9. Random Variables
10. Association Between Random Variables
11. Probability Models for Counts
12. The Normal Probability Model
III. Inference
13. Samples and Surveys
14. Sampling Variation and Quality
15. Confidence Intervals
16. Statistical Tests
17. Comparison
18. Inference for Counts
IV. Regression Models
19. Linear Patterns
20. Curved Patterns
21. The Simple Regression Model
22. Regression Diagnostics
23. Multiple Regression
24. Building Regression Models
25. Categorical Explanatory Variables
26. Analysis of Variance
27. Time Series
The 3rd Edition of Statistics for Business: Decision Making and Analysis emphasizes an application-based approach, in which students learn how to work with data to make decisions. In this contemporary presentation of business statistics, students learn how to approach business decisions through a 4M Analytics decision making strategy-motivation, method, mechanics and message-to better understand how a business context motivates the statistical process and how the results inform a course of action. Each chapter includes hints on using Excel, Minitab Express, and JMP for calculations, pointing the student in the right direction to get started with analysis of data.
9789353940645
Commercial statistics
Business planning
Industrial management--Statistical methods
Problem solving--Statistical methods
519.502465 / STI