R/BSDA-package.R
Nicotine.Rd
Data for Exercise 9.21
Nicotine
A data frame/tibble with eight observations on two variables
nicotine content (in milligrams)
sales figures (in $100,000)
Kitchens, L. J. (2003) Basic Statistics and Data Analysis. Pacific Grove, CA: Brooks/Cole, a division of Thomson Learning.
model <- lm(sales ~ nicotine, data = Nicotine)
plot(sales ~ nicotine, data = Nicotine)
abline(model, col = "red")
summary(model)
#>
#> Call:
#> lm(formula = sales ~ nicotine, data = Nicotine)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -29.3548 -6.3547 -0.3917 5.7778 27.0129
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 24.90 15.37 1.620 0.1564
#> nicotine 33.09 14.78 2.238 0.0665 .
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 17.9 on 6 degrees of freedom
#> Multiple R-squared: 0.455, Adjusted R-squared: 0.3641
#> F-statistic: 5.009 on 1 and 6 DF, p-value: 0.06653
#>
predict(model, newdata = data.frame(nicotine = 1),
interval = "confidence", level = 0.99)
#> fit lwr upr
#> 1 57.98711 34.34773 81.62648