Essentials of Probability & Statistics for Engineers & Scientists (Pearson New International Edition)
β Scribed by Ronald Walpole
- Publisher
- Pearson
- Year
- 2013
- Tongue
- English
- Leaves
- 475
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
For junior/senior undergraduates taking a one-semester probability and statistics course as applied to engineering, science, or computer science.
Β
This text covers the essential topics needed for a fundamental understanding of basic statistics and its applications in the fields of engineering and the sciences. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field.Β Students using this text should have the equivalent of the completion of one semester of differential and integral calculus.
Β
β¦ Table of Contents
Cover
Table of Contents
1. Introduction to Statistics and Probability
2. Random Variables, Distributions, and Expectations
3. Some Probability Distributions
4. Sampling Distributions and Data Descriptions
5. One- and Two-Sample Estimation Problems
6. One- and Two-Sample Tests of Hypotheses
7. One-Factor Experiments: General
8. Factorial Experiments (Two or More Factors)
9. Linear Regression
Bibliography
Appendix: Statistical Tables and Proofs
Index
A
B
C
D
E
F
G
H
I
J
L
M
N
O
P
Q
R
S
T
U
V
W
Y
Z
π SIMILAR VOLUMES
<!--[if gte mso 9]> <xml> Normal 0 false false false </xml> <![endif]--> <!--[if gte mso 9]> <xml> </xml> <![endif]--> <!--[if gte mso 10]> <![endif]--> <p style=''margin:0px;''>This text covers the essential topics needed for a fundamental understanding of basic statistics and its applications in t
<p><span>For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. </span></p><p><span>This classic text provides a rigorous introduction to </span><span>basic probability theory and statistical inference, </span><span> with a unique
<p><span>For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. </span></p><p><span>This classic text provides a rigorous introduction to </span><span>basic probability theory and statistical inference, </span><span> with a unique
This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance of theory and methodology. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the f