-
.First, 19
- .Last, 19
- .RProfile, 19, 19
- :, 2.5
- <-, ??, 2.2
- =, ??, 2.2
- ?, 3.9
- #, 2.5
- ANOVA, 15
- abline, 4.7, 4.7, 4.11, 4, 4, 4, 13.1, 13.7
- analysis of variance, 15
- anova, 14.1, 15.2
- apply, 4.2
- apropos(), 3.9
- as.factor, 3.3, 8.2
- attach, 4.6, 5.2
- barplot, 3.4, 3.4, 4.2, 5.5
- boxplot, 5.4, 5.5, 8.2
- bwplot, 5.6
- CLT, 9.3, 9.4
- c, 2.2, 2.2, 2.5, 21.1, 21.1, 21.2
- cbind, 5.5
- chi-squared distribution, 12.1
- chisq.test, 12.4
- coef, 4.7, 13.1, 13.7
- coefficients, 13.7
- col, 3.5
- cor, 4.9
- cor(), 4.9
- covariance, 4.9
- cummax, 2.5
- curve, 4, 4, 4, 4, 4, 6.1, 20.1
- cut, 3.9, 14.1
- cut(), 3.9
- data, 3.11
- data frame, 21.5, 21.5
- data frames, 5.1
- data(), 4.6
- data.entry, 21.4
- data.entry(), 1
- data.frame, 5.1
- density, 3.13, 4.5, 5.5
- diff, 1
- dump, 22
- dunif, 6.1
- Example
-
A difference in distributions?, 12.4
- A function to sum normal numbers, 7.4
- Boxplot of samples of random data, 5.5
- CEO salaries, 3.7, 8.2
- CLT with exponential data, 7.4
- CLT with normal data, 7.2
- Dilemma of two graders, 11.5
- GDP vs. CO2 emissions, 5.5
- Home data, 4.6
- Homedata, 8.2
- Is the die fair?, 12.2
- Keeping track of a stock; adding to the data, 2.5
- Letter distributions, 12.2
- Linear Regression with R, 13.1
- Making numeric data categorical, 3.9
- Max heart rate (cont.), 13.5, 13.6, 13.7
- Movie sales, reading in a dataset, 3.11
- Multiple linear regression with known answer, 14.1
- Presidential Elections: Florida, 4.10
- Quadratic regression, 14.1
- Recovery time for new drug, 11.3
- Sale prices of homes, 14.1
- Scholarship Grading, 15.1
- Seeing both the histogram and boxplot, 3.11
- Smoking survey, 3.2
- Symmetric or skewed, Long or short?, 8.2
- Taxi out times, 11.6
- Taxi time at EWR, 8.2
- Tooth growth, 5.5
- Two surveys, 11.1
- Working with mathematics, 2.5
- Extra
-
prop.test is more accurate, 9.2
- Comparing p-values from t and z, 9.4
- Conditional proportions, 4.2
- Confidence interval isn't always right, 9.1
- Easier plotting, 14.1
- Mean sum of squares, 15.2
- Rank tests, 10
- The difference between fivenum and the quantiles., 3.7
- Using simple.lm to predict, 4.10
- Using aov, 15.2
- Why the cs?, 12.2
- edit, 21.4
- exp, 12.4
- explanatory variable, 14
- extraction by a logical vector, 2.5
- factor, 3.3, 3.9, 14.1
- fitted.values, 13.7
- fivenum, 3.7, 3.7, 7.4
- fivenum(), 3.7
- fix, 21.4
- for, 7.2, 7.2, 8.2
- ftable, 5.5, 4
- function, 7.4, 20.1
- gray, 3.5
- grid, 5.6
- help, 3.9
- help(Startup), 19
- hist, 5.6
- histogram, 5.6
- I, 5.4, 14.1
- IQR, 3.8
- i.i.d., 9.1, 9.1, 12.1
- identify, 4.10, 4.10, 1
- jitter, 4.5
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- lattice, 5.6, 14.1
- layout, 5.5
- legend, 4.12
- legend.text, 4.2
- level, 5.5
- library, 3.11
- lines, 3.13, 4, 4
- lm, 4.12, 5.4, 5.6, 13.1, 13.1, 13.7, 14.1
- load, 22
- locator, 4.10
- lqs, 4.12, 4.12, 4.12
- lty, 4.12
- Multiple
linear regression, 14
- mad, 3.8
- matplot, 9.1
- max, 1, 6.1
- mean, 2.4, 1, 3.7, 3.8, 9, 9, 9.1, 20.1
- mean sum of squares, 15.2
- mean(), 3.8
- median, 2.4, 3.7
- min, 1, 6.1
- model formula notation, 4.12, 5.4, 5.5, 15.1, 18.2
- model formula syntax, 14.1
- model syntax, 4.3
- names, 3.5, 5.1
- oneway.test, 15.1, 15.2
- outer, 6.2
- Pearson correlation coefficient, 4.9
- pairs, 5.5
- panel.abline, 5.6
- panel.xyplot, 5.6, 5.6
- paste, 6.2, 20.1, 22
- pch, 5.5, 5.5
- pie, 3.5, 3.5
- piechart, 3.5
- plot, 4, 4, 4, 4, 4, 4, 5.5, 13.1, 13.1, 13.2
- pnorm, 6.5, 9.1
- points, 4, 4, 5.5
- predict, 4.10, 13.1, 13.7, 13.7, 13.7
- prompt, 2.1
- prop.table, 4.1
- prop.test, 9, 9.2, 9.2, 9.2, 9.5, 10.1, 11.1
- qnorm, 9.1
- qqline, 7.3
- qqnorm, 7.3, 9.4
- qqplot, 7.3
- quantile, 3.7
- R, 2.1
- RBasics
-
help, ? and apropos, 3.9
- Accessing Data, 2.5
- Graphical Data Entry Interfaces, 2.5
- Plotting graphs using R, 4
- Reading in datasets with library and data, 3.11
- Syntax for for, 7.2
- The low-level R commands, 13.7
- What does attaching do?, 4.6
- rainbow, 3.5
- read.csv, 21.7
- read.fwf, 21.6
- read.mtp, 21.9
- read.table, 1, 21.5, 21.8
- really.convenient.function, 22
- rep, 6.2
- resid, 4.8, 13.1, 13.7
- residual, 14.1
- residuals, 14.1
- rlm, 4.12, 4.12, 4.12, 4.12, 4.12
- rnorm, 5.5
- row.names, 5.1
- rug, 3.10, 4.5, 5.5
- Spearman rank correlation, 4.9
- System.sleep, 6
- sample, 6.2, 6.2, 12.4
- sapply, 14.1
- save.image(), 22
- scale, 4.5, 6.5, 6.5
- scan, 3.4, 21.2, 21.2, 21.3, 21.3, 21.3
- scan(), 3.4
- scatterplot, 4.6
- sd, 3.7
- sd(), 2.5
- seq(), 2.5
- simple.densityplot, 5.5
- simple.eda, 8.1, 8.2
- simple.lm, 4.7, 4.8, 4.12, 13.1, 13.7
- simple.sim, 7.4, 7.4
- simple.violinplot, 4.5, 5.5
- slicing, 2.5
- source, 22
- stack, 5.3, 15.1
- standard deviation, 2.5, 9
- stem(), 3.9
- stripchart, 5.5
- subset, 11.6
- sum of squares, 15.2
- summary, 3.7, 3.7, 3.7, 13.1, 13.1, 13.7, 14.1
- t(), 4.2
- t.test, 9, 9.5, 10.2, 11.5
- table, 3.2, 3.2, 3.2, 3.4, 3.9, 4.1, 4.1, 5.5, 5.5, 5.5
- trellis.device, 5.6
- trimmed mean, 3.8
- ts, 3.11
- typos, 2.2, 2.2, 2.5
- unbiased estimator, 13.5
- unstack, 5.3, 5.3
- url, 21.8
- var, 2.4, 3.7
- variance, 2.5, 9.1
- vector, 2.2, 2.5, 2.5
- which, 2.5, 2.5
- wilcox.test, 9, 9.5, 10.3, 10, 11.6, 11.6
- x, 13.7
- xtabs, 5.5
- xyplot, 5.6, 5.6
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