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Research methods for science /

An introduction to the design, analysis, and presentation of scientific projects, this is an essential textbook for undergraduate majors in science and mathematics. The book discusses experimental design, statistics, mathematical modelling, and preparing scientific papers and presentations.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Marder, Michael P., 1960-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge ; New York : Cambridge University Press, 2011.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Marder, Michael P.,  |d 1960- 
245 1 0 |a Research methods for science /  |c by Michael P. Marder. 
260 |a Cambridge ;  |a New York :  |b Cambridge University Press,  |c 2011. 
300 |a 1 online resource (viii, 227 pages) :  |b illustrations 
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504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
520 8 |a An introduction to the design, analysis, and presentation of scientific projects, this is an essential textbook for undergraduate majors in science and mathematics. The book discusses experimental design, statistics, mathematical modelling, and preparing scientific papers and presentations. 
505 0 |a 1. Curiosity and research: Course goals -- Kinds of questions -- Research methods for science -- Putting methods together -- 2. Overview of experimental analysis and design: Hypothesis-driven experiments -- Measuring values -- Improving experiments -- Safety and ethics -- 3. Statistics: Motivations for statistics -- Reducing many numbers to few -- Probability distributions -- Connecting data and probability distributions -- What happens to averages as N increases -- Central limit theorem -- Comparing many experimental measurements -- Data with many values of independent variable -- Other statistical tests -- 4. Mathematical models: Ingredients of mathematical modeling -- Estimation -- Linear regression -- Matching arbitrary functions to data -- Fourier transforms -- Deterministic modeling -- 5. Scientific information: Writing a proposal -- Writing scientific papers -- Scientific figures -- Giving scientific presentations -- Searching for scientific information -- Obtaining scientific articles -- Reading scientific papers. 
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650 0 |a Research  |x Methodology. 
650 0 |a Science projects. 
650 0 |a Research. 
650 1 2 |a Research Design 
650 2 2 |a Research 
650 6 |a Recherche  |x Méthodologie. 
650 6 |a Sciences  |x Travaux pratiques. 
650 6 |a Recherche. 
650 7 |a research (function)  |2 aat 
650 7 |a SCIENCE  |x Research & Methodology.  |2 bisacsh 
650 7 |a Research  |2 fast 
650 7 |a Research  |x Methodology  |2 fast 
650 7 |a Science projects  |2 fast 
650 7 |a Forschung.  |2 idszbz 
650 7 |a Methode.  |2 idszbz 
650 7 |a Statistik.  |2 idszbz 
650 7 |a Wissenschaftliches Arbeiten.  |2 idszbz 
776 0 8 |i Print version:  |a Marder, Michael P., 1960-  |t Research methods for science.  |d Cambridge : Cambridge University Press, 2010  |z 9780521145848  |w (OCoLC)656771018 
856 4 0 |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=344690  |z Texto completo 
880 8 |6 505-00/(S  |a 3.3.1 Definitions -- 3.3.2 Discrete probability distributions -- Single coin flip -- Sequences of measurements: Products of probabilities -- Probabilities of sequences, neglecting the order -- Binomial distribution for a fair coin -- Binomial distribution for a weighted coin -- 3.3.3 Continuous probability distributions -- Example involving time measurements -- 3.4 Connecting data and probability distributions -- 3.4.1 Sampling -- 3.4.2 True mean and true standard deviation -- Discrete distributions -- Continuous distributions -- 3.5 What happens to averages as N increases -- 3.5.1 A drunken sailor -- 3.5.2 Mean and standard deviation for averages -- Application of standard error: Improving an experiment -- 3.6 Central Limit Theorem -- 3.6.1 Uses of the normal distribution -- 3.6.2 Z test and interpreting p -- 3.6.3 Large Z, small p -- 3.6.4 Two-tailed and one-tailed tests -- 3.6.5 Confidence intervals -- 3.6.6 Type I errors -- 3.6.7 Z tests in spreadsheets -- 3.7 Comparing many experimental measurements -- 3.7.1 t test: Comparing two measurements -- 3.7.2 Two-sample t test -- Example: Rolling balls -- Example: Fish in two lakes -- 3.8 Data with many values of independent variable -- 3.8.1 χ2 test for many means with uncertainties -- Example: Bottle rocket heights versus theory -- 3.8.2 χ2 for categories -- Example: Favorite math course -- 3.8.3 Degrees of freedom -- Unbiased estimators -- 3.9 Other statistical tests -- Assignments -- References -- 4 Mathematical models -- 4.1 Ingredients of mathematical modeling -- 4.1.1 Numbers -- 4.1.2 Basic operations -- Subtraction -- Multiplication -- Division -- 4.1.3 Algebra -- 4.1.4 Setting up problems: Sketching and naming -- 4.1.5 Functions -- 4.2 Estimation -- 4.2.1 Order of magnitude estimates -- 4.2.2 Dimensional analysis -- 4.3 Linear regression. 
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