Between Certainty and Uncertainty
Language: English
Published by Springer, Springer Okt 2012, 2012
Series: Book 25 of 188 - Intelligent Systems Reference Library
- Softcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
AbeBooks seller since January 23, 2017
Condition: New
£ 92.85
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This item is printed on demand - Print on Demand Titel. Neuware -'Between Certainty & Uncertainty' is a one-of-a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes on historical origins and 80 illustrative numerical examples organized in the five units: Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God's proof; linear transformations and z-scored statistics . Chapter 2 Grouped data: Udny Yule's concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right Houbolt's cloud. What in fact measures the correlation coefficient Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal's Arithmetical Triangle. Bernoulli's or Poisson Trials John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli's Weak Law of Large Numbers and others. Chapter 5 Normal distribution and binomial heritage - Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God's proof; linear transformations and z-scored statistics . Chapter 2 Grouped data: Udny Yule's concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right Houbolt's cloud. What in fact measures the correlation coefficient Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal's Arithmetical Triangle. Bernoulli's or Poisson Trials John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli's Weak Law of Large Numbers and others. Chapter 5 Normal distribution and binomial heritage - Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. Chapter 5 Normal distribution and binomial heritage - Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 328 pp. Englisch.…
Seller Inventory # 9783642256967
- Title
- Between Certainty and Uncertainty
- Author
- Ludomir M. Lauda¿ski
- Publisher
- Springer, Springer Okt 2012
- Publication year
- 2012
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3642256961
- ISBN 13
- 9783642256967
- Item weight
- 658 grams
- Dimensions
- 241x160x23 mm
- Series
- Book 25 of 188: Intelligent Systems Reference Library
„Between Certainty & Uncertainty” is a one-of–a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes on historical origins and 80 illustrative numerical examples organized in the five units:
· Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics .
· Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles.
· Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient?
· Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others.
· Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.
· Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics .
· Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles.
· Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient?
· Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others.
· Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.
· Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.
"Synopsis" may belong to another edition of this title.
About the Author
Rzeszow Technical University
ul. Wincentego Pola 2
35-959 Rzeszow
Poland
ludek@prz.edu.pl
"About the title" may belong to another edition of this title.
buchversandmimpf2000
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