Mohsen Nady
Here is some code
set.seed(1)
x<-rnorm(1000)
mean <-mean(x)
The random number is -0.0116481.
Here is the plot
par(las=1)
plot(x, main = "simulated data")
Here is another code
library(datasets)
data("airquality")
fit<-lm(Ozone ~ Wind+Temp+Solar.R,data = airquality)
Here is a table of coefficients
summary(fit)
##
## Call:
## lm(formula = Ozone ~ Wind + Temp + Solar.R, data = airquality)
##
## Residuals:
## Min 1Q Median 3Q Max
## -40.485 -14.219 -3.551 10.097 95.619
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -64.34208 23.05472 -2.791 0.00623 **
## Wind -3.33359 0.65441 -5.094 1.52e-06 ***
## Temp 1.65209 0.25353 6.516 2.42e-09 ***
## Solar.R 0.05982 0.02319 2.580 0.01124 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.18 on 107 degrees of freedom
## (42 observations deleted due to missingness)
## Multiple R-squared: 0.6059, Adjusted R-squared: 0.5948
## F-statistic: 54.83 on 3 and 107 DF, p-value: < 2.2e-16