| Description |
xvi, 335 pages ; 25 cm |
| Contents |
Contents note continued: 2.Regression analysis -- Introduction -- 2.1.Regression statistics -- 2.1.1.Slope and intercept -- 2.1.2.ANOVA table -- 2.1.3.Correlation -- 2.1.4.Regression uncertainties -- 2.1.5.Quality of fit -- 2.2.Experimental uncertainties -- 2.2.1.Calibration uncertainty -- 2.2.2.Exact x/y intercepts -- 2.2.3.Known uncertainty -- 2.2.4.Weighting uncertainties -- 2.3.Linearization techniques -- 2.3.1.Change of variable -- 2.3.2.Using logarithms -- 2.3.3.Exponential relationships -- 2.3.4.Linearizing the exponential -- 2.3.5.Unknown power -- 2.3.6.Combined linearization -- 2.3.7.Error warning -- 2.4.Iteration using Solver -- 2.4.1.Operation of Solver -- 2.4.2.Maximum likelihood estimation -- 2.4.3.Nonlinear regression -- 3.Hypothesis testing -- Introduction -- 3.1.t-tests and z-tests -- 3.1.1.General principle of hypothesis testing -- 3.1.2.One sample t-test -- 3.1.3.Two sample t-test -- 3.1.4.Unequal variances -- 3.1.5.z-tests -- 3.2.Analysis of variance -- |
|
Contents note continued: 3.2.1.F-test -- 3.2.2.Basic principle of ANOVA calculations -- 3.2.3.One-way ANOVA -- 3.2.4.Post hoc comparison tests -- 3.3.Multiple factors ANOVA -- 3.3.1.Two-way ANOVA -- 3.3.2.Interactions between the different factors -- 3.3.3.Analysis of covariance, ANCOVA -- 3.4.General linear model -- 3.4.1.General linear model -- 3.4.2.GLM ANOVA, and the t-test -- 3.4.3.General regression -- 3.4.4.Fixed and random factor -- 3.4.5.Sequential and adjusted sums of squares -- 3.4.6.Lack of fit and error -- 3.4.7.Generalized linear model -- 3.5.Nonparametric analyses -- 3.5.1.Mann-Whitney example -- 3.5.2.Nonparametric and parametric test equivalents -- 3.6.Repeated measurements -- 3.6.1.Paired samples -- 3.6.2.Repeated measures -- 3.7.Chi-squared analyses -- 3.7.1.Tabulated data -- 3.7.2.One-way ̀goodness of fit' -- 3.7.3.Low value of chi-squared -- 3.7.4.Contingency table -- 3.7.5.Yates continuity correction -- 3.7.6.Likelihood ratio -- |
|
Contents note continued: 3.7.7.Sample size limitations -- 3.8.Frequency and proportions -- 3.8.1.Probability distribution -- 3.8.2.One proportion test -- 3.8.3.Two proportions test -- 3.9.Resampling techniques -- 3.9.1.General approach to resampling -- 3.9.2.t-test and Mann-Whitney test -- 3.9.3.Chi-squared probabilities -- 4.Comparing data -- Introduction -- 4.1.Correlation -- 4.1.1.Linear correlation -- 4.1.2.Nonparametric correlation -- 4.1.3.Scientific context of correlation -- 4.1.4.Bivariate and partial correlation -- 4.2.Tests for association -- 4.2.1.Association and interaction -- 4.2.2.Tests for association -- 4.2.3.Fisher's exact test -- 4.2.4.Linear by linear association -- 4.3.Strength of association -- 4.3.1.Association and agreement -- 4.3.2.Measures of association -- 4.3.3.Cramer's V and Phi -- 4.3.4.Goodman and Kruskal's Lambda -- 4.3.5.Concordance of data pairs -- 4.3.6.Nominal by interval association, Eta -- 4.4.Agreement between variables -- |
|
Contents note continued: 4.4.1.R2 goodness of fit -- 4.4.2.Agreement between two related variables -- 4.4.3.Agreement between several variables -- 4.4.4.Agreement within a contingency table -- 4.4.5.Binary agreement -- pt. II Analysing experimental data -- 5.Project data analysis -- Introduction -- 5.1.Preparing data for analysis -- 5.1.1.Case studies -- 5.1.2.Identifying the variables/factors -- 5.1.3.Understanding the uncertainty in the data -- 5.1.4.Scientific significance -- 5.1.5.Data entry into software -- 5.1.6.Reviewing data and objectives -- 5.2.Deriving test characteristics -- 5.2.1.Case studies -- 5.2.2.Beyond the exploratory phase -- 5.2.3.Selecting analyses -- 5.2.4.Combining data -- 5.2.5.Modelling response variables -- 5.3.Transforming and weighting data -- 5.3.1.Case studies -- 5.3.2.Software transformation -- 5.3.3.Common transformations -- 5.3.4.Weighting data -- 5.4.Normality and homoscedasticity -- 5.4.1.Case studies -- 5.4.2.Analytical approach -- |
|
Contents note continued: 5.4.3.Anticipating normality -- 5.4.4.Differences in variance -- 5.4.5.Testing normality -- 5.4.6.Using residuals -- 5.4.7.Data transformations -- 6.Single response variable -- Introduction -- 6.1.One sample -- 6.1.1.Example data -- 6.1.2.Analytical options -- 6.1.3.Describing the data -- 4.1.4.One sample t-test -- 6.1.5.Wilcoxon test -- 6.1.6.SPSS nonparametric tests -- 6.1.7.Proportions -- 6.2.Two samples -- 6.2.1.Example data -- 6.2.2.Analytical options -- 6.2.3.Describing the data -- 6.2.4.Comparing variances -- 6.2.5.Two sample t-test -- 6.2.6.Nonparametric tests -- 6.2.7.Paired t-test -- 6.2.8.Paired Wilcoxon test -- 6.2.9.Unrelated binary data -- 6.3.One factor -- 6.3.1.Example data -- 6.3.2.Analytical options -- 6.3.3.Describing the data -- 6.3.4.Normality and equality of variance (homoscedasticity) -- 6.3.5.GLM/ANOVA -- 6.3.6.Post hoc comparison tests -- 6.3.7.Kruskal-Wallis test -- 6.3.8.Repeated measures -- |
|
Contents note continued: 6.4.Multiple factors and interactions -- 6.4.1.Example data -- 6.4.2.Analytical options -- 6.4.3.Describing the data -- 6.4.4.GLM/ANOVA -- 6.4.5.Checking for normality and homoscedasticity -- 6.4.6.Nonparametric ANOVAs -- 6.4.7.Generalized linear model -- 6.4.8.Analysis of covariance, ANCOVA -- 7.Related variables -- Introduction -- 7.1.Regression, correlation, and agreement -- 7.1.1.Example data -- 7.1.2.Analytical options -- 7.1.3.Describing the data -- 7.1.4.Correlation -- 7.1.5.Linear regression and calibration -- 7.1.6.Agreement between results -- 7.2.Nonlinear relationships -- 7.2.1.Example data -- 7.2.2.Analytical options -- 7.2.3.Iterative nonlinear regression -- 7.2.4.Deriving the mathematical model -- 7.2.5.General regression -- 7.3.General x-y data -- 7.3.1.Example data -- 7.3.2.Analytical options -- 7.3.3.Identifying relevant analytical characteristics -- 7.3.4.Describing the data -- 7.3.5.Smoothing convolutes -- |
|
Contents note continued: 7.3.6.Differentiating convolutes -- 7.3.7.Spectral analysis -- 8.Frequency data -- Introduction -- 8.1.Single variable -- 8.1.1.Example data -- 8.1.2.Analytical options -- 8.1.3.Describing categorical data -- 8.1.4.Editing histograms -- 8.1.5.Chi-squared goodness of fit test -- 8.1.6.Testing distributions -- 8.1.7.Tabulation of data -- 8.1.8.Binning -- 8.2.Contingency tables -- 8.2.1.Example data -- 8.2.2.Analytical options -- 8.2.3.Describing the data -- 8.2.4.Contingency tables and cross-tabulation -- 8.2.5.Progression within the table -- 8.2.6.Data consolidation -- 8.2.7.Low expected frequencies -- 8.2.8.Layered contingency tables -- 8.3.Binary output date -- 8.3.1.Example data -- 8.3.2.Analytical options -- 8.3.3.Logit and probit linearization -- 8.3.4.Binary regression -- 8.3.5.Binary probabilities and ROC plots -- 9.Multiple variables -- Introduction -- 9.1.Modelling multiple variables -- 9.1.1.Example data -- 9.1.2.Analytical options -- |
|
Contents note continued: 9.1.3.Cluster analysis -- 9.1.4.Principal component analysis -- 9.1.5.Factor analysis -- 9.1.6.Multiple regression -- 9.2.Multiple questions -- 9.2.1.Example data -- 9.2.2.Describing the data -- 9.2.3.Testing for normality and homoscedasticity -- 9.2.4.Analysing an individual variable -- 9.2.5.Dependence of specific factors -- 9.2.6.Comparing variables as unrelated data -- 9.2.7.Modelling interrelated variables -- 9.2.8.Comparing related variables -- 9.2.9.Ordinal responses -- 9.2.10.Multiple variables |
|
Machine generated contents note: pt. I Understanding the statistics -- 1.Statistical concepts -- Introduction -- 1.1.Data visualization -- 1.1.1.Graphical information -- 1.1.2.Boxplots -- 1.1.3.Raw data and calculated values -- 1.2.Scientific data -- 1.2.1.Experimental data -- 1.2.2.Data types -- 1.2.3.Type and value of data -- 1.3.Data distributions -- 1.3.1.Histogram -- 1.3.2.Distribution parameters -- 1.3.3.Standard distributions -- 1.4.Uncertainty and error -- 1.4.1.Error or uncertainty -- 1.4.2.True value -- 1.4.3.Experimental uncertainty -- 1.4.4.Combining uncertainties -- 1.4.5.Probability uncertainty -- 1.4.6.Identifying uncertainties -- 1.5.Sample data -- 1.5.1.Sample statistics -- 1.5.2.Confidence interval -- 1.5.3.Samples and populations -- 1.5.4.Known experimental uncertainly -- 1.5.5.Presenting results -- 1.6.Hypothesis tests -- 1.6.1.Test procedure -- 1.6.2.Hypothesis test and p-values -- 1.6.3.Errors in hypothesis tests -- 1.6.4.Bonferroni correction -- |
| Notes |
Includes index |
| Subject |
Data mining.
|
|
Research -- Methodology.
|
|
Science -- Statistical methods -- Textbooks.
|
|
Research -- Statistical methods.
|
|
Science -- Statistical methods.
|
| Genre/Form |
Textbooks.
|
| ISBN |
0198712545 |
|
9780198712541 |
|
