Intro Stuff
setwd("C:/Users/Jerome/Documents/Data_Science_110/Datasets")
library(tidyverse)
## -- Attaching packages ----------------------------------------------------------------------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.3.2 v purrr 0.3.4
## v tibble 3.0.1 v dplyr 1.0.0
## v tidyr 1.1.0 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.5.0
## -- Conflicts -------------------------------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
lcn_fpf_co_names <- read.csv("lcn_fpf_co_names.csv")
Run Regression on Full Data Set
fit4 <- lm(MEASURE ~ as.factor(UrbRur) +as.factor(Educ) +as.factor(Wealth), data = lcn_fpf_co_names)
summary(fit4)
##
## Call:
## lm(formula = MEASURE ~ as.factor(UrbRur) + as.factor(Educ) +
## as.factor(Wealth), data = lcn_fpf_co_names)
##
## Residuals:
## Min 1Q Median 3Q Max
## -53.614 -20.592 7.934 15.424 49.724
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 41.66065 0.50126 83.112 < 2e-16 ***
## as.factor(UrbRur)2 0.06121 0.41911 0.146 0.8839
## as.factor(Educ)1 -0.31553 0.37293 -0.846 0.3975
## as.factor(Educ)2 4.38239 0.84769 5.170 2.37e-07 ***
## as.factor(Educ)3 0.32681 0.55807 0.586 0.5581
## as.factor(Educ)4 1.21807 1.23126 0.989 0.3225
## as.factor(Educ)5 4.33243 2.16209 2.004 0.0451 *
## as.factor(Wealth)2 0.12967 0.42736 0.303 0.7616
## as.factor(Wealth)3 2.10815 0.47627 4.426 9.63e-06 ***
## as.factor(Wealth)4 3.72918 0.58120 6.416 1.43e-10 ***
## as.factor(Wealth)5 7.58124 0.80801 9.383 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 22.73 on 19711 degrees of freedom
## Multiple R-squared: 0.01143, Adjusted R-squared: 0.01093
## F-statistic: 22.79 on 10 and 19711 DF, p-value: < 2.2e-16
print(fit4)
##
## Call:
## lm(formula = MEASURE ~ as.factor(UrbRur) + as.factor(Educ) +
## as.factor(Wealth), data = lcn_fpf_co_names)
##
## Coefficients:
## (Intercept) as.factor(UrbRur)2 as.factor(Educ)1 as.factor(Educ)2
## 41.66065 0.06121 -0.31553 4.38239
## as.factor(Educ)3 as.factor(Educ)4 as.factor(Educ)5 as.factor(Wealth)2
## 0.32681 1.21807 4.33243 0.12967
## as.factor(Wealth)3 as.factor(Wealth)4 as.factor(Wealth)5
## 2.10815 3.72918 7.58124