„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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Prof. Dr hab. inż. Ludomir M. Laudański
Rzeszow Technical University
ul. Wincentego Pola 2
35-959 Rzeszow
Poland
ludek@prz.edu.pl
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - 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. 328 pp. Englisch. N° de réf. du vendeur 9783642436734
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Short statistic course with notes on historical origins Reference book in the field of Intelligent System Written by leading experts in the fieldProf. Dr hab. inz. Ludomir M. Laudanski Rzeszow Technical University ul. Wincentego . N° de réf. du vendeur 5060900
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Taschenbuch. Etat : Neu. Between Certainty and Uncertainty | Statistics and Probability in Five Units with Notes on Historical Origins and Illustrative Numerical Examples | Ludomir M. Lauda¿ski | Taschenbuch | Intelligent Systems Reference Library | x | Englisch | 2014 | Springer | EAN 9783642436734 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 105023431
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Taschenbuch. Etat : Neu. 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. N° de réf. du vendeur 9783642436734
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - '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. N° de réf. du vendeur 9783642436734
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