Background

This presentation describes a Shiny App that plots the relationships between life expectancy and three factors measured in the United States around 1970:

• Illiteracy rate

• Income per capita

• Population Density

Data source

Data are from the state dataset in the datsets package. Data used include:

• Life expectancy, in years, 1969-1971

• Illiteracy, as a percent of population in 1970

• Income per capita in 1974

• Population estimate in 1975

• Area (in square miles)

#setting up data
states <- as.data.frame(state.x77)
colnames(states)[4] <- "LifeExpectancy"
#defining Population Density
states$PopulationDensity <- states$Population/states$Area

What the Shiny App does

This Shiny App will allow the user to select which factor they want to relate to life expectancy and show a plot with that factor on the x-axis and life expectancy on the y-axis.

This app will also fit linear models with life expectancy as the dependent variable and each factor as an independent variable. The user can select whether to show this line on the plot.

Finally, the app will display with coefficient demonstrating the direction and magnitude of the relationship and a p-value indicating whether it is significantly different than a null relationship of 0.

Slide with R Output from models

summary(lm(LifeExpectancy ~ Illiteracy, data=states))$coefficients

##              Estimate Std. Error    t value     Pr(>|t|)
## (Intercept) 72.394947  0.3383361 213.973443 3.474322e-73
## Illiteracy  -1.296023  0.2570095  -5.042706 6.969250e-06

summary(lm(LifeExpectancy ~ Income, data=states))$coefficients

##                 Estimate   Std. Error   t value     Pr(>|t|)
## (Intercept) 6.758132e+01 1.3275714260 50.905975 1.979131e-43
## Income      7.433343e-04 0.0002965107  2.506939 1.561728e-02

summary(lm(LifeExpectancy ~ PopulationDensity, data=states))$coefficients

##                     Estimate Std. Error     t value     Pr(>|t|)
## (Intercept)       70.7960625  0.2312136 306.1933440 1.190757e-80
## PopulationDensity  0.5531096  0.8730646   0.6335265 5.293972e-01

Plots of relationships between life expectancy and other factors