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| Preface | |
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| Data in statistics and R | |
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| Basic R.1.1 Preliminaries | |
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| Modes | |
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| Vectors | |
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| Arithmetic operators and special values | |
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| Objects | |
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| Programming | |
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| Packages | |
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| Graphics | |
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| Customizing the workspace | |
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| Projects | |
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| Assignments | |
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| Data in statistics and in R | |
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| Types of data | |
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| Objects that hold data | |
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| Data organization | |
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| Data import, export and connections | |
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| Data manipulation | |
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| Manipulating strings | |
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| Assignments | |
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| Presenting data | |
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| Tables and the flavors of apply () | |
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| Bar plots | |
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| Histograms | |
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| Dot charts | |
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| Scatter plots | |
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| Lattice plots | |
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| Three-dimensional plots and contours | |
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| Assignments | |
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| Probability, densities and distributions | |
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| Probability and random variables | |
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| Set theory | |
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| Trials, events and experiments | |
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| Definitions and properties of probability | |
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| Conditional probability and independence | |
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| Algebra with probabilities | |
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| Random variables | |
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| Assignments | |
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| Discrete densities and distributions | |
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| Densities | |
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| Distribution | |
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| Properties | |
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| Expected values | |
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| Variance and standard deviation | |
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| The binomial | |
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| The Poisson | |
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| Estimating parameters | |
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| Some useful discrete densities | |
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| Assignments | |
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| Continuous distributions and densities | |
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| Distributions | |
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| Densities | |
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| Properties | |
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| Expected values | |
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| Variance and standard deviation | |
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| Areas under density curves | |
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| Inverse distributions and simulations | |
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| Some useful continuous densities | |
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| Assignments | |
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| The normal and sampling densities | |
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| The normal density | |
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| Applications of the normal | |
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| Data transformations | |
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| Random samples and sampling densities | |
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| A detour: using R efficiently | |
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| The sampling density of the mean | |
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| The sampling density of proportion | |
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| The sampling density of intensity | |
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| The sampling density of variance | |
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| Bootstrap: arbitrary parameters of arbitrary densities | |
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| Assignments | |
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| Statistics | |
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| Exploratory data analysis | |
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| Graphical methods | |
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| Numerical summaries | |
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| Visual summaries | |
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| Assignments | |
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| Point and interval estimation | |
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| Point estimation | |
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| Interval estimation | |
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| Point and interval estimation for arbitrary densities | |
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| Assignments | |
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| Single sample hypotheses testing | |
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| Null and alternative hypotheses | |
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| Large sample hypothesis testing | |
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| Small sample hypotheses testing | |
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| Arbitrary parameters of arbitrary densities | |
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| p-values | |
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| Assignments | |
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| Power and sample size for single samples | |
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| Large sample | |
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| Small samples | |
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| Power and sample size for arbitrary densities | |
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| Assignments | |
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| Two samples | |
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| Large samples | |
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| Small samples | |
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| Unknown densities | |
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| Assignments | |
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| Power and sample size for two samples | |
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| Two means from normal populations | |
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| Two proportions | |
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| Two rates | |
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| Assignments | |
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| Simple linear regression | |
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| Simple linear models | |
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| Estimating regression coefficients | |
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| The model goodness of fit | |
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| Hypothesis testing and confidence intervals | |
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| Model assumptions | |
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| Model diagnostics | |
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| Power and sample size for the correlation coefficient | |
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| Assignments | |