Year <- c(1971,1972,1973,1974,1975,1976)
PopSize <- c(500,562,544,532,580,590)
df <- data.frame (Year, PopSize )
df
## Year PopSize
## 1 1971 500
## 2 1972 562
## 3 1973 544
## 4 1974 532
## 5 1975 580
## 6 1976 590
plot(df$Year, df$PopSize, type = "l", col = "red", lwd = 3)

plot(df$Year, df$PopSize, type = "l", col = 3)

plot(df$Year, df$PopSize, type = "l", col = "red")

plot(df$Year, df$PopSize, type = "l")

plot(df$Year, df$PopSize, type = "l", lty = "dotted")

plot(df$Year, df$PopSize, type = "l", lty = "dashed")

plot(df$Year, df$PopSize)

plot(df$Year, df$PopSize, type = "l")

plot(df$Year, df$PopSize,
type = "l",
col = "red",
lwd = 3,
xlab = "Year",
ylab = "Population Size",
main = "Moomin Population Size on Ruissalo 1971 - 2001")

plot(df$Year, df$PopSize,
type = "l",
col = "red",
lwd = 3,
xlab = "Year",
ylab = "Population Size",
main = "Moomin Population Size on Ruissalo 1971 - 2001")

fit1 <- lm (PopSize ~ Year, data = df)
summary(fit1)
##
## Call:
## lm(formula = PopSize ~ Year, data = df)
##
## Residuals:
## 1 2 3 4 5 6
## -16.1905 31.7524 -0.3048 -26.3619 7.5810 3.5238
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -27190.438 10641.429 -2.555 0.0630 .
## Year 14.057 5.392 2.607 0.0596 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 22.56 on 4 degrees of freedom
## Multiple R-squared: 0.6295, Adjusted R-squared: 0.5369
## F-statistic: 6.796 on 1 and 4 DF, p-value: 0.05961