Code Rank// i/q// exam score// Gender
1 4 40 86 Male
2 11 65 88 Female
3 27 80 70 Male
4 53 80 61 Male
5 4 40 89 Male
6 22 70 60 Female
7 16 20 81 Female
8 21 55 75 Female
9 25 50 69 Female
10 18 40 82 Female
from the following list what would be r code to calculate mean and standard deviation of exam score for male and female in separate.
You can use dplyr package to achieve this easily:
> data
# A tibble: 10 × 5
code rank iq score gender
<int> <int> <int> <dbl> <chr>
1 1 4 40 86.298 Male
2 2 11 65 88.716 Female
3 3 27 80 70.178 Male
4 4 53 80 61.312 Male
5 5 4 40 89.522 Male
6 6 22 70 60.506 Female
7 7 16 20 81.462 Female
8 8 21 55 75.820 Female
9 9 25 50 69.372 Female
10 10 18 40 82.268 Female
Grouping this data on gender column using group_by() and summarizing using summarise() can give you your answer:
> data %>%
+ group_by(gender) %>%
+ summarise(avg_score = mean(score),
+ sd_score = sd(score))
# A tibble: 2 × 3
gender avg_score sd_score
<chr> <dbl> <dbl>
1 Female 76.35733 10.13981
2 Male 76.82750 13.36397
There are other ways to do this too, but learning a bit of dplyr to do these things might be helpful in long run.
For a detailed tutorial, read Transformation chapter in Hadley Wickham's book R for Data Science
