*The log of a positive number
*What is the default base for the log function? calculate the log of your previous number with a different base.
*The log of a negative number (explain the answer)
log(20,10)
## [1] 1.30103
log(20)
## [1] 2.995732
*Create a vector of 15 standard normal random variables. Calculate its mean and SD.
*Change the mean to 10 and the SD to 2 and recalculate the vector of 15 random normal variables. Calculate its mean and SD.
*Why are the means and SD not exactly the same as the means and SDs spe cified in the function?
f<-rnorm(15, mean =0, sd = 1)
mean(f)
## [1] -0.03890449
sd(f)
## [1] 0.7056753
f<-rnorm(15, mean =10, sd = 2)
mean(f)
## [1] 9.645831
sd(f)
## [1] 1.230614
*Vector Operations
*The weights of 6 individuals in kg are 60, 72, 57, 90, 95, 72
*Their heights (in m) are 1.80, 1.85, 1.72, 1.90, 1.74, 1.91
*Enter these vectors into R
*Create a scatterplot of weight vs. height. Interpret the scatterplot. - Calculate the BMI for each individual (BMI = weight in kg divided by the square of the height in m)
*Calculate the mean for weight
*Subtract the mean from each value of weight
*Sum the result. Now you know why we square the deviations from the mea n to calculate a standard deviation!
weight <- c(60, 72, 57, 90, 95, 72)
weight
## [1] 60 72 57 90 95 72
height <- c(1.80, 1.85, 1.72, 1.90, 1.74, 1.91)
height
## [1] 1.80 1.85 1.72 1.90 1.74 1.91
mean(weight)
## [1] 74.33333
mean(height)
## [1] 1.82
plot(weight, height)