STAT213 Tutorial sheet #2 Solutions

 

1)      P(paper or plastic) = 78% + 60% - 52% = 86%

2)      P(plastic | paper) = 52/78 = 66.67%. P(plastic | not paper) = 8/22 = 36.36%. Since the first probability is higher, those who recycle paper are more likely to recycle plastic. Since P(plastic) = 60% and neither conditional probability equals this, we can conclude that recycling one thing depends on recycling the other.

3)      P(not paper | not plastic) = 8/22 = 36.36%

4)      Since P(paper and plastic) = 52% which is not zero, a household recycling one thing is not mutually exclusive of recycling the other.

5)      P(balance < $1000) = (806 + 2690)/10000 = 0.3496 = 34.96%

6)      P(balance < $1000 | income between $35K and $50K) = (508 + 1377)/3029 = 0.6223 = 62.23%

7)      P(balance < $1000 | income < $75K) = (107 + 508 + 191 + 169 + 1377 + 826)/(276 + 3029 + 3241) = = 0.4855 = 48.55%

8)      P(income at least $50K | balance at least $1000) = (1419 + 911 + 254 + 805 + 1229 + 742)/(3474 + 3030) = 0.8241 = 82.41%

9)      For each income group, we need to compute the percentage that has a balance of $1000 or more:

< 35K

35K – 50K

50K – 75K

75K – 100K

100K +

0/276 = 0

(890 + 254)/

3029 = 0.3777

(1419 + 805)/

3241 = 0.6862

(911 + 1229)/

2394 = 0.8939

(254 + 742)/

1060 = 0.9396

Thus the $100K+ group has the largest percentage of those whose balance is $1000 or more. As we can see from the calculations, the percentage who have a balance of at least $1000 increases with each income group.

10)  We first need to compute the overall market share for the under 25 age group. This output summarizes the results:

Brand

% market share

% used by under 25 age group

Weighted average

Brand A

0.25

0.7

0.175

Brand B

0.15

0.55

0.0825

Brand C

0.6

0.4

0.24

 

 

Total

0.4975

We see the overall market share for the under 25 age group is 49.75% and that Brand C comprises the largest percentage at 24%. Therefore, the percentage of the under 25 age group that uses Brand C is 24/49.75 = 48.24%.

11)  P(suburb) = 0.762 P(transit | suburb) = 0.252 P(suburb and transit) = 0.192024

P(IC) = 0.238 P(transit | IC) = 0.128 P(IC and transit) = 0.030464

P(transit) = 0.222488 or 22.25%

12)  P(suburb | transit) = 0.192024/0.222488 = 0.86.31%

13)  We first construct a crosstab:

 

Suburb

IC

Total

Transit at least once per week

0.192024

0.030464

0.222488

Transit less than once per week

0.569976

0.207536

0.777512

Total

0.762

0.238

1.0

P(IC | transit less than once per week) = 0.207536/0.777512 = 26.69%