Introduction

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## [1] 2
dat <- read.csv("../datafiles/cadata.csv")
summary(dat)
##  MedianHouseValue  MedianIncome     MedianHouseAge    TotalRooms   
##  Min.   : 14999   Min.   : 0.4999   Min.   : 1.00   Min.   :    2  
##  1st Qu.:119600   1st Qu.: 2.5634   1st Qu.:18.00   1st Qu.: 1448  
##  Median :179700   Median : 3.5348   Median :29.00   Median : 2127  
##  Mean   :206856   Mean   : 3.8707   Mean   :28.64   Mean   : 2636  
##  3rd Qu.:264725   3rd Qu.: 4.7432   3rd Qu.:37.00   3rd Qu.: 3148  
##  Max.   :500001   Max.   :15.0001   Max.   :52.00   Max.   :39320  
##  TotalBedrooms      Population      Households        Latitude    
##  Min.   :   1.0   Min.   :    3   Min.   :   1.0   Min.   :32.54  
##  1st Qu.: 295.0   1st Qu.:  787   1st Qu.: 280.0   1st Qu.:33.93  
##  Median : 435.0   Median : 1166   Median : 409.0   Median :34.26  
##  Mean   : 537.9   Mean   : 1425   Mean   : 499.5   Mean   :35.63  
##  3rd Qu.: 647.0   3rd Qu.: 1725   3rd Qu.: 605.0   3rd Qu.:37.71  
##  Max.   :6445.0   Max.   :35682   Max.   :6082.0   Max.   :41.95  
##    Longitude     
##  Min.   :-124.3  
##  1st Qu.:-121.8  
##  Median :-118.5  
##  Mean   :-119.6  
##  3rd Qu.:-118.0  
##  Max.   :-114.3
hist(dat$MedianIncome, col = "darkorange")

fit <- lm(MedianHouseValue ~ MedianIncome, dat)

summary(fit)
## 
## Call:
## lm(formula = MedianHouseValue ~ MedianIncome, data = dat)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -540697  -55950  -16979   36978  434023 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   45085.6     1322.9   34.08   <2e-16 ***
## MedianIncome  41793.8      306.8  136.22   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 83740 on 20638 degrees of freedom
## Multiple R-squared:  0.4734, Adjusted R-squared:  0.4734 
## F-statistic: 1.856e+04 on 1 and 20638 DF,  p-value: < 2.2e-16