Tools for an Introductory Class in Regression and Modeling

ACCOUNT | Predicting whether a customer will open a new kind of account |

all_correlations | Pairwise correlations between quantitative variables |

APPLIANCE | Appliance shipments |

associate | Association Analysis |

ATTRACTF | Attractiveness Score (female) |

ATTRACTM | Attractiveness Score (male) |

AUTO | AUTO dataset |

BODYFAT | BODYFAT data |

BODYFAT2 | Secondary BODYFAT dataset |

build.model | Variable selection for descriptive or predictive linear and... |

build.tree | Exploratory building of partition models |

BULLDOZER | BULLDOZER data |

BULLDOZER2 | Modified BULLDOZER data |

CALLS | CALLS dataset |

CENSUS | CENSUS data |

CENSUSMLR | Subset of CENSUS data |

CHARITY | CHARITY dataset |

check.regression | Linear and Logistic Regression diagnostics |

choose.order | Choosing order of a polynomial model |

CHURN | CHURN dataset |

confusion.matrix | Confusion matrix for logistic regression models |

cor.demo | Correlation demo |

cor.matrix | Correlation Matrix |

CUSTCHURN | CUSTCHURN dataset |

CUSTLOYALTY | CUSTLOYALTY dataset |

CUSTREACQUIRE | CUSTREACQUIRE dataset |

CUSTVALUE | CUSTVALUE dataset |

DIET | DIET data |

DONOR | DONOR dataset |

EDUCATION | EDUCATION data |

EX2.CENSUS | CENSUS data for Exercise 5 in Chapter 2 |

EX2.TIPS | TIPS data for Exercise 6 in Chapter 2 |

EX3.ABALONE | ABALONE dataset for Exercise D in Chapter 3 |

EX3.BODYFAT | Bodyfat data for Exercise F in Chapter 3 |

EX3.HOUSING | Housing data for Exercise E in Chapter 3 |

EX3.NFL | NFL data for Exercise A in Chapter 3 |

EX4.BIKE | Bike data for Exercise 1 in Chapter 4 |

EX4.STOCKPREDICT | Stock data for Exercise 2 in Chapter 4 (prediction set) |

EX4.STOCKS | Stock data for Exercise 2 in Chapter 4 |

EX5.BIKE | BIKE dataset for Exercise 4 Chapter 5 |

EX5.DONOR | DONOR dataset for Exercise 4 in Chapter 5 |

EX6.CLICK | CLICK data for Exercise 2 in Chapter 6 |

EX6.DONOR | DONOR dataset for Exercise 1 in Chapter 6 |

EX6.WINE | WINE data for Exercise 3 Chapter 6 |

EX7.BIKE | BIKE dataset for Exercise 1 Chapters 7 and 8 |

EX7.CATALOG | CATALOG data for Exercise 2 in Chapters 7 and 8 |

EX9.BIRTHWEIGHT | Birthweight dataset for Exercise 1 in Chapter 9 |

EX9.NFL | NFL data for Exercise 2 Chapter 9 |

EX9.STORE | Data for Exercise 3 Chapter 9 |

extrapolation.check | A crude check for extrapolation |

find.transformations | Transformations for simple linear regression |

FRIEND | Friendship Potential vs. Attractiveness Ratings |

FUMBLES | Wins vs. Fumbles of an NFL team |

generalization.error | Calculating the generalization error of a model on a set of... |

getcp | Complexity Parameter table for partition models |

influence_plot | Influence plot for regression diganostics |

JUNK | Junk-mail dataset |

LARGEFLYER | Interest in frequent flier program (large version) |

LAUNCH | New product launch data |

mosaic | Mosaic plot |

MOVIE | Movie grosses |

NFL | NFL database |

OFFENSE | Some offensive statistics from 'NFL' dataset |

outlier_demo | Interactive demonstration of the effect of an outlier on a... |

overfit.demo | Demonstration of overfitting |

PIMA | Pima Diabetes dataset |

POISON | Cockroach poisoning data |

possible.regressions | Illustrating how a simple linear/logistic regression could... |

PRODUCT | Sales of a product one quarter after release |

PURCHASE | PURCHASE data |

QQ plot | |

SALARY | Harris Bank Salary data |

see.interactions | Examining pairwise interactions between quantitative... |

see.models | Examining model AICs from the "all possible" regressions... |

segmented.barchart | Segmented barchart |

SMALLFLYER | Interest in a frequent flier program (small version) |

SOLD26 | Predicting future sales |

SPEED | Speed vs. Fuel Efficiency |

STUDENT | STUDENT data |

summarize.tree | Useful summaries of partition models from rpart |

SURVEY09 | Student survey 2009 |

SURVEY10 | Student survey 2010 |

SURVEY11 | Student survey 2011 |

TIPS | TIPS dataset |

VIF | Variance Inflation Factor |

visualize.model | Visualizations of one or two variable linear or logistic... |

visualize.relationship | Visualizing the relationship between y and x in a partition... |

WINE | WINE data |

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