387 pages, no illustrations
Essential Mathematics and Statistics for Science is a low-level introduction to the essential techniques students need to understand. Little in the way of prior knowledge is assumed, and the approach adopted is a gentle one, that leads through examples in the book and website.
The aim of the authors is to produce a concise introduction, which will appeal to all science students. Spreadsheets are increasingly being used in courses, and this book includes the use of excel and Minitab spreadsheets, with additional data sets available on the web site.
This title presents a basic introduction to maths and stats covering the most important topics of relevance to science undergraduates. It assumes no prior knowledge. It offers applied approach relating to math's and stats directly to science examples. It incorporates the use of Excel and Minitab spreadsheet. It includes animated movies detailing a whiteboard and chalk pen working out mathematical and statistical scenarios. It is clear and concise with plenty of worked examples and practice questions. It features example calculations with significant figures that describe the different rules for addition/subtraction and multiplication/division of quantities.
Preface On-line Learning Support 1 Mathematics and Statistics in Science 1.1 Data and Information 1.2 Experimental Variation and Uncertainty 1.3 Mathematical Models in Science 2 Scientific Data 2.1 Scientific Numbers 2.2 Scientific Quantities 2.3 Chemical Quantities 2.4 Angular Measurements 3 Equations in Science 3.1 Basic Techniques 3.2 Rearranging Simple Equations 3.3 Symbols 3.4 Further Equations 3.5 Quadratic and Simultaneous Equations 4 Linear Relationships 4.1 Straight Line Graph 4.2 Linear Regression 4.3 Linearization 5 Logarithmic and Exponential Functions 5.1 Mathematics of e, ln and log 5.2 Exponential Growth and Decay 6 Rates of Change 6.1 Rate of Change 6.2 Differentiation 7 Statistics for Science 7.1 Analysing Replicate Data 7.2 Describing and Estimating 7.3 Frequency Statistics 7.4 Probability 7.5 Factorials, Permutations and Combinations 8 Distributions and Uncertainty 8.1 Normal Distribution 8.2 Uncertainties in Measurement 8.3 Presenting Uncertainty 8.4 Binomial and Poisson Distributions 9 Scientific Investigation 9.1 Scientific Systems 9.2 The 'Scientific Method' 9.3 Decision Making with Statistics 9.4 Hypothesis Testing 9.5 Selecting Analyses and Tests 10 t -tests and F-tests 10.1 One-sample t -tests 10.2 Two-sample t -tests 10.3 Paired t -tests 10.4 F-tests 11 ANOVA - Analysis of Variance 11.1 One-way ANOVA 11.2 Two-way ANOVA 11.3 Two-way ANOVA with Replication 11.4 ANOVA Post Hoc Testing 12 Non-parametric Tests for Medians 12.1 One-sample Wilcoxon Test 12.2 Two-sample Mann-Whitney U-test 12.3 Paired Wilcoxon Test 12.4 Kruskal-Wallis and Friedman Tests 13 Correlation and Regression 13.1 Linear Correlation 13.2 Statistics of Correlation and Regression 13.3 Uncertainty in Linear Calibration 14 Frequency and Proportion 14.1 Chi-squared Contingency Table 14.2 Goodness of Fit 14.3 Tests for Proportion 15 Experimental Design 15.1 Principal Techniques 15.2 Planning a Research Project Appendix I: Microsoft Excel Appendix II: Cumulative z -areas for Standard Normal Distribution Appendix III: Critical Values: t -statistic and Chi-squared, chi2 Appendix IV: Critical F-values at 0.05 (95 %) Significance Appendix V: Critical Values at 0.05 (95 %) Significance for: Pearson's Correlation Coefficient, r , Spearman's Rank Correlation Coefficient, rS, and Wilcoxon Lower Limit, WL Appendix VI: Mann-Whitney Lower Limit, UL, at 0.05 (95 %) Significance Short Answers to 'Q' Questions Index
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