getting a sum of 1? A sum less than 2 is not possible as the dice are from 1-6 each. 0/36 X 1/36 = 0
getting a sum of 5? There are 4 ways to get a sum of 5: 1,4; 2,3; 3,2; 4,1 (1/6 x 1/6) + (1/6 x 1/6) + (1/6 x 1/6) + (1/6 x 1/6) = 4/36
getting a sum of 12? There is only one combination that gives 2 6’s. 1/6 x 1/6 = 1/36
Disjoint would mean that there is no overlap between the 2 groups and we know that 4.2% of those surveyed fall into both categories. Therefore the variables are not disjoint.
library(VennDiagram)
venn.plot <- draw.pairwise.venn(14.6, 20.7, 4.2, c("Below Poverty", "Foreign Language"));
grid.draw(venn.plot)The Venn Diagram shows that 14.6% - 4.2% = 10.4% of Americans live below the poverty line and only speak English at home.
From the Venn Diagram we see that 10.4% + 16.5% = 26.9% of Americans live below the poverty line and speak a foreign language at home.
Percentage who live above poverty line and only speak English at home =
100 - 10.4 - 20.7## [1] 68.9
P(lives below pov line & speaks foreign lang) = P(pl) X P(fl) =
.207 * .146 *100## [1] 3.0222
P(lives below pl and speaks fl) = 4.2%
The probabilities are not equal and therefore the events are not independent.
Format
Hardcover Paperback Total
Type Fiction 13 59 72
Nonfiction 15 8 23
Total 28 67 95
28/95 * 59/94## [1] 0.1849944
13/95 * 27/94 + 59/95 * 28/94## [1] 0.2243001
72/95 * 28/95## [1] 0.2233795
Replacing the book allows for the possibility that it could be chosen as a hardback in the second draw, however it only slightly alters the total books that can be drawn from and does not change the probability significantly.
Average revenue per passenger =
0*.54 + 25*.34 + 35*.12 ## [1] 12.7
Standard deviation =
((0- 12.7)**2 *.54+ (25 - 12.7)**2*.34 + (35-12.7)**2*.12)**.5## [1] 14.07871
(0*.54 + 25*.34 + 35*.12)*120## [1] 1524
With what standard deviation? Note any assumptions you make and if you think they are justified.
Standard deviation =
Income Total
$1 to $9,999 or loss 2.2%
$10,000 to $14,999 4.7%
$15,000 to $24,999 15.8%
$25,000 to $34,999 18.3%
$35,000 to $49,999 21.2%
$50,000 to $64,999 13.9%
$65,000 to $74,999 5.8%
$75,000 to $99,999 8.4%
$100,000 or more 9.7%
The distrubution is fairly symmetric around the $35,000 to $49,999 range with a longer right skewed tail.
(.022 + .047 + .158 + .183 + .212)## [1] 0.622
Assumption: females are evenly distributed throughout the income distribution and the sample represents the US population.
(.022 + .047 + .158 + .183 + .212)*.41## [1] 0.25502
From the previous example, the probability of a randomly chosen person making less than $50,000 and who is female is is 25.5%. So the number of females making less than $50k is:
96420486 * .255## [1] 24587224
If the same data source says that 71.8% of females make less than $50,000 per year then:
(96420486 * .718)## [1] 69229909
The assumption that women are evenly distributed throughout the income distribution or that the sample represents the US population is incorrect.