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1. Getting Started 1
1.1. The MATLAB Statistics Toolbox 1
1.2. Data in MATLAB 2
1.3. Simple descriptive methods 3
1.4. Numerical summaries of quantitative data 4
1.5. Graphical summaries of quantitative data 6
2. M files 10
3. Reading from and writing to files 11
4. Statistical distributions in MATLAB 12
4.1. Available distributions and calculations 12
4.2. Computation of binomial probabilities 13
4.3. Computation of Poisson probabilities 15
4.4. Computation of normal probabilities 17
4.5. Computing percentage points for the normal distribution 19
4.6. Computing percentage points for the
t distribution 195. Simulation in MATLAB 19
5.1. Introduction 19
5.2. The uniform distribution 20
5.3. Other distributions 21
5.4. Simulation of normal and lognormal random variables 23
5.5. Further applications of simulation 25
6. Statistical tests in MATLAB 28
6.1. One-sample t-test 28
6.2. Paired t-test 29
6.3. Two-sample t-test 29
6.4. The sign test 29
6.5. The Wilcoxon signed rank test 30
7. Simple linear regression in MATLAB 30
7.1. Simple linear regression: fitting lines to data 30
7.2. Fitting the simple linear regression model in MATLAB 32
7.3. Estimation of
σ2 347.4. Decomposing variation 35
7.5. Different kinds of residuals 36
8. Multiple linear regression in MATLAB 39
8.1. The multiple linear regression model 39
8.2. Estimation of model parameters 39
8.3. Inference for model coefficients 42
8.4. Confidence intervals for the mean and prediction intervals 44
8.5. Assessing overall model adequacy 45
8.6. Stepwise approaches to model selection 48
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8.7. Residuals and influence in multiple linear regression 51
9. ANOVA in MATLAB 53
9.1. One way ANOVA 53
9.2. One way ANOVA as a regression model 56
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