rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Data analysis
    sub title: a gentle introduction for future data scientists
  name:
    name part: Upton, Graham J. G.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Brawn, Dan
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: enk
    date issued: 2023
    copyright date: 2023
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (viii, 141 pages) : illustrations
  abstract: "This book introduces the central concepts of modern data science, beginning with an introduction to simple statistical concepts such as mean and variance together with related methods for presenting and summarising data. The next chapters present the laws of probability, the probability distributions most commonly used to summarise data, the methods for estimating the parameters of these distributions, and the extent to which we can be confident concerning those estimated values. The next chapters are concerned with the relationships between two variables and the selection of models that involve several variables. The final chapter investigates the various methods that are used in dividing a population into distinct classes. The many worked examples include a study of the fate of those on the Titanic, and the factors affecting babies being born underweight. The book demands no particular software familiarity, since the methods presented can be implemented in Python, R (used by the authors), or any other statistical software"--Publisher's description.
  table of contents: Cover -- Titlepage -- Copyright -- Contents -- Preface -- 1 First steps -- 1.1 Types of data -- 1.2 Sample and population -- 1.2.1 Observations and random variables -- 1.2.2 Sampling variation -- 1.3 Methods for sampling a population -- 1.3.1 The simple random sample -- 1.3.2 Cluster sampling -- 1.3.3 Stratified sampling -- 1.3.4 Systematic sampling -- 1.4 Oversampling and the use of weights -- 2 Summarizing data -- 2.1 Measures of location -- 2.1.1 The mode -- 2.1.2 The mean -- 2.1.3 The trimmed mean -- 2.1.4 The Winsorized mean -- 2.1.5 The median -- 2.2 Measures of spread
  table of contents: 2.2.1 The range -- 2.2.2 The interquartile range -- 2.3 Boxplot -- 2.4 Histograms -- 2.5 Cumulative frequency diagrams -- 2.6 Step diagrams -- 2.7 The variance and standard deviation -- 2.8 Symmetric and skewed data -- 3 Probability -- 3.1 Probability -- 3.2 The rules of probability -- 3.3 Conditional probability and independence -- 3.4 The total probability theorem -- 3.5 Bayes' theorem -- 4 Probability distributions -- 4.1 Notation -- 4.2 Mean and variance of a probability distribution -- 4.3 The relation between sample and population -- 4.4 Combining means and variances
  table of contents: 4.5 Discrete uniform distribution -- 4.6 Probability density function -- 4.7 The continuous uniform distribution -- 5 Estimation and confidence -- 5.1 Point estimates -- 5.1.1 Maximum likelihood estimation (mle) -- 5.2 Confidence intervals -- 5.3 Confidence interval for the population mean -- 5.3.1 The normal distribution -- 5.3.2 The Central Limit Theorem -- 5.3.3 Construction of the confidence interval -- 5.4 Confidence interval for a proportion -- 5.4.1 The binomial distribution -- 5.4.2 Confidence interval for a proportion (large sample case)
  table of contents: 6.3.1 Do the two samples come from the same population? -- 6.3.2 Do the two populations have the same mean? -- 7 Comparing proportions -- 7.1 The 2 2 table -- 7.2 Some terminology -- 7.2.1 Odds, odds ratios, and independence -- 7.2.2 Relative risk -- 7.2.3 Sensitivity, specificity, and related quantities -- 7.3 The R C table -- 7.3.1 Residuals -- 7.3.2 Partitioning -- 8 Relations between two continuous variables -- 8.1 Scatter diagrams -- 8.2 Correlation -- 8.2.1 Testing for independence -- 8.3 The equation of a line -- 8.4 The method of least squares -- 8.5 A random dependent variable, Y
  note: Graham Upton and Dan Brawn.
  note: Includes bibliographical references and index.
  subject:
    topic: Mathematical statistics
  subject:
    topic: Probabilities
  subject:
    topic: Probabilités
  subject:
    topic: probability
  subject:
    topic: Applied
  subject:
    topic: Mathematical Analysis
  subject:
    topic: Mathematical statistics
  subject:
    topic: Probabilities
  subject:
    topic: Mathematics
  subject:
    topic: Mathematics
  classification: QA276 .U68 2023
  classification: 519.5
  related item:
    title info:
      title: Data analysis
    name:
      name part: Upton, Graham J. G.
    origin info:
      publisher: Oxford, United Kingdom : Oxford University Press, 2023
      edition: First edition.
    identifier: (OCoLC)1402151849
  identifier: 9780192885791
  identifier: 0192885790
  identifier: 9780191980855
  identifier: 0191980854
  identifier: 9780192885784
  identifier: 9780192885777
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: EBLCP
    record creation date: 230819
    record change date: 20260318165931.5
    record identifier: in00005698753
    language of cataloging:
      language term: eng