A pre-loaded example dataset in R

Main page: https://www.rdocumentation.org/packages/datasets/versions/3.6.2/topics/longley

longley
##      GNP.deflator     GNP Unemployed Armed.Forces Population Year Employed
## 1947         83.0 234.289      235.6        159.0    107.608 1947   60.323
## 1948         88.5 259.426      232.5        145.6    108.632 1948   61.122
## 1949         88.2 258.054      368.2        161.6    109.773 1949   60.171
## 1950         89.5 284.599      335.1        165.0    110.929 1950   61.187
## 1951         96.2 328.975      209.9        309.9    112.075 1951   63.221
## 1952         98.1 346.999      193.2        359.4    113.270 1952   63.639
## 1953         99.0 365.385      187.0        354.7    115.094 1953   64.989
## 1954        100.0 363.112      357.8        335.0    116.219 1954   63.761
## 1955        101.2 397.469      290.4        304.8    117.388 1955   66.019
## 1956        104.6 419.180      282.2        285.7    118.734 1956   67.857
## 1957        108.4 442.769      293.6        279.8    120.445 1957   68.169
## 1958        110.8 444.546      468.1        263.7    121.950 1958   66.513
## 1959        112.6 482.704      381.3        255.2    123.366 1959   68.655
## 1960        114.2 502.601      393.1        251.4    125.368 1960   69.564
## 1961        115.7 518.173      480.6        257.2    127.852 1961   69.331
## 1962        116.9 554.894      400.7        282.7    130.081 1962   70.551
require(stats); require(graphics)
## give the data set in the form it is used in S-PLUS:
longley.x <- data.matrix(longley[, 1:6])
longley.y <- longley[, "Employed"]
pairs(longley, main = "longley data")

summary(fm1 <- lm(Employed ~ ., data = longley))
## 
## Call:
## lm(formula = Employed ~ ., data = longley)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.41011 -0.15767 -0.02816  0.10155  0.45539 
## 
## Coefficients:
##                Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -3.482e+03  8.904e+02  -3.911 0.003560 ** 
## GNP.deflator  1.506e-02  8.492e-02   0.177 0.863141    
## GNP          -3.582e-02  3.349e-02  -1.070 0.312681    
## Unemployed   -2.020e-02  4.884e-03  -4.136 0.002535 ** 
## Armed.Forces -1.033e-02  2.143e-03  -4.822 0.000944 ***
## Population   -5.110e-02  2.261e-01  -0.226 0.826212    
## Year          1.829e+00  4.555e-01   4.016 0.003037 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3049 on 9 degrees of freedom
## Multiple R-squared:  0.9955, Adjusted R-squared:  0.9925 
## F-statistic: 330.3 on 6 and 9 DF,  p-value: 4.984e-10
opar <- par(mfrow = c(2, 2), oma = c(0, 0, 1.1, 0),
            mar = c(4.1, 4.1, 2.1, 1.1))
plot(fm1)

par(opar)