|
|
|
|
LEADER |
00000cam a2200000 i 4500 |
001 |
SCIDIR_ocn973049031 |
003 |
OCoLC |
005 |
20231120112213.0 |
006 |
m o d |
007 |
cr ||||||||||| |
008 |
170209t20172017enka ob 001 0 eng d |
040 |
|
|
|a NLE
|b eng
|e rda
|e pn
|c NLE
|d OPELS
|d TEFOD
|d OCLCF
|d OCLCQ
|d UKMGB
|d OCLCO
|d YDXIT
|d GZM
|d OCLCQ
|d EBLCP
|d OCLCQ
|d OCLCO
|
015 |
|
|
|a GBB7J0406
|2 bnb
|
016 |
7 |
|
|a 018479958
|2 Uk
|
020 |
|
|
|a 9780128043615
|q (electronic book)
|
020 |
|
|
|a 012804361X
|q (electronic book)
|
020 |
|
|
|z 9780128043172
|
035 |
|
|
|a (OCoLC)973049031
|
050 |
|
4 |
|a QA276
|b .R684 2017
|
082 |
0 |
4 |
|a 519.5
|2 23
|
100 |
1 |
|
|a Ross, Sheldon M.,
|e author.
|
245 |
1 |
0 |
|a Introductory statistics /
|c Sheldon M. Ross.
|
250 |
|
|
|a Fourth edition.
|
264 |
|
1 |
|a London ;
|a San Diego, CA :
|b Academic Press,
|c [2017]
|
264 |
|
4 |
|c �2017
|
300 |
|
|
|a 1 online resource (xxv, 796 pages) :
|b illustrations
|
336 |
|
|
|a text
|b txt
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
490 |
1 |
|
|a Always learning
|
504 |
|
|
|a Includes bibliographical references and index.
|
500 |
|
|
|a 1. Introduction to Statistics -- 2. Describing Data Sets -- 3. Using Statistics to Summarize Data Sets -- 4. Probability -- 5. Discrete Random Variables -- 6. Normal Random Variables -- 7. Distributions of Sampling Statistics -- 8. Estimation -- 9. Testing Statistical Hypotheses -- 10. Hypothesis Tests Concerning Two Populations -- 11. Analysis of Variance -- 12. Linear Regression -- 13. Chi-Squared Goodness-of-Fit Tests -- 14. Nonparametric Hypotheses Tests -- 15. Quality Control -- 16. Machine Learning and Big Data -- Appendices.
|
520 |
|
|
|a Introductory Statistics, Fourth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods. Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others. Examples relating to data mining techniques using the number of Google queries or Twitter tweets are also considered. For this fourth edition, new topical coverage includes sections on Pareto distribution and the 80-20 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, A-B testing, and more modern (big data) examples and exercises.
|
588 |
0 |
|
|a Online resource; title from digital title page (viewed on September 17, 2020).
|
650 |
|
0 |
|a Mathematical statistics.
|
650 |
|
7 |
|a Mathematical statistics
|2 fast
|0 (OCoLC)fst01012127
|
830 |
|
0 |
|a Always learning.
|
856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128043172
|z Texto completo
|