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Basic Statistics with R: Reaching Decisions with Data

English

By (author): Stephen C. Loftus

Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals. All topics are taught using real-data drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect and make statistics essential to their field of interest, rather than seeing it as a separate and ancillary knowledge area. In addition to introducing students to statistical topics using real data, the book provides a gentle introduction to coding, having the students use the statistical language and software R. Students learn to load data, calculate summary statistics, create graphs and do statistical inference using R with either Windows or Macintosh machines. See more
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A01=Stephen C. LoftusAge Group_UncategorizedAuthor_Stephen C. Loftusautomatic-updateCategory1=Non-FictionCategory=PBTCOP=United StatesDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=In stockPrice_€50 to €100PS=Activesoftlaunch
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Product Details
  • Weight: 480g
  • Dimensions: 151 x 229mm
  • Publication Date: 30 Jun 2021
  • Publisher: Elsevier Science Publishing Co Inc
  • Publication City/Country: United States
  • Language: English
  • ISBN13: 9780128207888

About Stephen C. Loftus

Dr. Stephen Loftus is an Analyst in Research & Development for the Atlanta Braves. Prior to this he held academic positions at Randolph-Macon College and Sweet Briar College. In his experience in academia and industry Dr. Loftus has spent a great deal of time studying and developing Bayesian models for a variety of projects. These highly collaborative projects range from analysis in baseball to studies in numerical ecology. In developing these models he found himself on many occasions needing to explain not only the decisions made in making these models but also the rationale behind the Bayesian philosophy of statistics to individuals with diverse mathematical backgrounds.

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