## ---------------------------------------------------------------------------------------------------------------------
library("lessR")

## ----include=FALSE----------------------------------------------------------------------------------------------------
knitr::opts_chunk$set(fig.width=3.5, fig.height=3)

## ----read-------------------------------------------------------------------------------------------------------------
d <- Read("Employee")

## ----labels-----------------------------------------------------------------------------------------------------------
l <- rd("Employee_lbl")
l

## ----fig.width=4.5, fig.height=4.5------------------------------------------------------------------------------------
reg_brief(Salary ~ Years + Pre)

## ---------------------------------------------------------------------------------------------------------------------
reg(Salary ~ Years + Pre)

## ----fig.width=4.5, fig.height=4--------------------------------------------------------------------------------------
reg_brief(Salary ~ Years, new_scale="z", plot_errors=TRUE)

## ---------------------------------------------------------------------------------------------------------------------
reg(Salary ~ Years, kfold=3)

## ---------------------------------------------------------------------------------------------------------------------
r <- reg(Salary ~ Years + Pre)

## ---------------------------------------------------------------------------------------------------------------------
r

## ---------------------------------------------------------------------------------------------------------------------
names(r)

## ---------------------------------------------------------------------------------------------------------------------
r$out_estimates

## ---------------------------------------------------------------------------------------------------------------------
r$coefficients

## ---------------------------------------------------------------------------------------------------------------------
r <- reg(Salary ~ Years, pred_rows="all", graphics=FALSE)
r$out_predict = sub(", ", ",", r$out_predict, fixed=TRUE)
dp <- read.table(text=r$out_predict)
dp[.(row.names(dp) == "Pham,Scott"),]

## ---------------------------------------------------------------------------------------------------------------------
cnt <- contr.sum(n=3)
cnt

## ----fig.width=4.5, fig.height=4--------------------------------------------------------------------------------------
d$JobSat <- factor(d$JobSat, levels=c("low", "med", "high"))
reg_brief(Salary ~ JobSat, contrasts=list(JobSat=cnt))

## ----fig.width=5------------------------------------------------------------------------------------------------------
reg_brief(Salary ~ 1, plot_errors=TRUE)

## ----likert, fig.width=4.5, fig.height=4.5----------------------------------------------------------------------------
dd <- Read("Mach4")
reg_brief(m10 ~ m02, data=dd)

## ----fig.width=5, fig.height=4----------------------------------------------------------------------------------------
Plot(Salary, Years, by=Dept, fit="lm")

## ----fig.width=5, fig.height=4----------------------------------------------------------------------------------------
reg_brief(Salary ~ Dept + Years)

## ----mod, fig.width=4.5, fig.height=4.5-------------------------------------------------------------------------------
reg_brief(Salary ~ Years + Pre, mod=Pre)

## ----fig.width=5, fig.height=4----------------------------------------------------------------------------------------
d <- Read("BodyMeas")
Logit(Gender ~ Hand)

## ----fig.width=5, fig.height=4----------------------------------------------------------------------------------------
Logit(Gender ~ Hand, prob_cut=c(.3, .5, .7))

## ----fig.width=5, fig.height=4----------------------------------------------------------------------------------------
d$Gender <- ifelse (d$Gender == "M", 1, 0)
Plot(Hand, Gender, n_bins=6)