1. Basic statistics on a vector in R

2. Suppose we had a vector corresponding to high temperatures in Philadelphia in August
high_temps<-c(91, 89, 87, 88, 79, 78, 72, 80, 86, 86, 84, 83, 84, 82, 78, 89, 90, 91, 88, 85, 87, 92, 84, 82, 79, 81, 79, 77, 67, 78, 84)
We will consider another time how to get data from Excel to R or vice versa, but for now just copy the above code into R
For now we just want to focus on some of the simple statistic functions built into R that can act on a vector

3. Open RStudio. Seems like there’s some old stuff in the Environment

4. Click on the List icon (upper right) and switch to Grid.

5. Check the “objects” and use the broom icon to clear them out.

6. Start a new script

7. Save it

8. Copy and paste the data into RStudio and run it
high_temps<-c(91, 89, 87, 88, 79, 78, 72, 80, 86, 86, 84, 83, 84, 82, 78, 89, 90, 91, 88, 85, 87, 92, 84, 82, 79, 81, 79, 77, 67, 78, 84)
The keyboard shortcut for copying is Ctrl-c (copies whatever is highlighted)
The keyboard shortcut for pasting is Ctrl-v
The run, place the cursor on the line (or highlight it) and click on the Run icon (or type Ctrl-Enter)

9. Result of paste and run

10. Use the mean function to calculate the average

11. Use the median function

12. Use the sd (standard deviation) function

13. Use the min() function – minimum

14. Use the max() function – maximum

15. The quantile function can be used to determine the first quartile

16. The quantile function can be used to determine the third quartile

17. The summary function is a quick way to get a number of standard statistical measures on a set of data

18. To do Give the statistical measures for the low temperature data
low_temps <- c(71, 69, 67, 72, 68, 63, 66, 66, 64, 67, 68, 70, 70, 67, 72, 69, 69, 75, 73, 68, 67, 73, 68, 65, 65, 65, 62, 60, 62, 60, 66)
Get individually the mean, median, standard deviation, min, max, first and third quartiles
Submit your R script