Key
The 1st Hourly
Math 1107
Spring Semester 2009
Protocol: You will use only the following resources: Your individual calculator; individual tool-sheet (single 8.5 by 11 inch sheet); your writing utensils; blank paper (provided by me) and this copy of the hourly. Do not share these resources with anyone else. In each case, show complete detail and work for full credit. Follow case study solutions and sample hourly keys in presenting your solutions. Work all four cases. Using only one side of the blank sheets provided, present your work. Do not write on both sides of the sheets provided, and present your work only on these sheets. All of your work goes on one side each of the blank sheets provided. Space out your work. Do not share information with any other students during this hourly. Do not use any external resources during this hourly.
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Case One | Probability Rules | Color Slot Machine
Here is our slot machine – on each
trial, it produces a color sequence, using the table below:
Sequence |
Probability |
RBRRYRGG |
.10 |
RRGGBRRB |
.10 |
BBYYYGBR |
.15 |
GRRGGRGG |
.10 |
BGYYYRYY |
.25 |
RRYYGRRB |
.10 |
YYGBYYBR |
.20 |
Total |
1.00 |
1. Define GREENCOUNT as the
number of times that green shows in the color sequence.
Compute Pr
Sequence |
Green Count |
Probability |
RBRRYRGG |
2 |
.10 |
RRGGBRRB |
2 |
.10 |
BBYYYGBR |
1 |
.15 |
GRRGGRGG |
5 |
.10 |
BGYYYRYY |
1 |
.25 |
RRYYGRRB |
1 |
.10 |
YYGBYYBR |
1 |
.20 |
Total |
|
1.00 |
Here are the complete
calculations for GREENCOUNT:
Pr
Pr
Pr
Pr
Pr
Pr
Here is the required
calculation:
Pr
Pr
2. Compute Pr
Sequence |
“BY” Shows |
Probability |
RBRRYRGG |
No |
.10 |
RRGGBRRB |
No |
.10 |
BBYYYGBR |
Yes |
.15 |
GRRGGRGG |
No |
.10 |
BGYYYRYY |
No |
.25 |
RRYYGRRB |
No |
.10 |
YYGBYYBR |
Yes |
.20 |
Total |
|
1.00 |
Pr
3. Compute Pr
Sequence |
Blue Shows |
Probability |
RBRRYRGG |
Yes |
.10 |
RRGGBRRB |
Yes |
.10 |
BBYYYGBR |
Yes |
.15 |
GRRGGRGG |
No |
.10 |
BGYYYRYY |
Yes |
.25 |
RRYYGRRB |
Yes |
.10 |
YYGBYYBR |
Yes |
.20 |
Total |
|
1.00 |
Other Event = “Blue Does Not
Show”
Pr
Pr
Case Two | Long Run Argument, Perfect Samples | Maternal
Age
Suppose that the following
probability model applies to year 2006 United States Resident Live Births:
Maternal Age |
Probability |
Under 15 |
0.0015 |
15-24 |
0.3554 |
25-34 |
0.4999 |
35-44 |
0.1416 |
45+ |
0.0016 |
Total |
1 |
Interpret each probability
using the Long Run Argument.
In
long runs of random sampling year 2006 United States Resident Live Births, approximately
.15% of sampled births are to mothers aged less than 15 years.
In
long runs of random sampling year 2006 United States Resident Live Births,
approximately 35.54% of sampled births are to mothers aged between 15 and 24
years.
In long
runs of random sampling year 2006 United States Resident Live Births,
approximately 49.99% of sampled births are to mothers aged between 25 and 34
years.
In
long runs of random sampling year 2006 United States Resident Live Births,
approximately 14.16% of sampled births are to mothers aged between 35 and 44
years.
In
long runs of random sampling year 2006 United States Resident Live Births,
approximately 0.16% of sampled births are to mothers aged 45 or more years.
Compute
and discuss Perfect Samples for n=2500.
Maternal
Age |
Probability |
E2500 |
Under
15 |
0.0015 |
3.75 |
15-24 |
0.3554 |
888.5 |
25-34 |
0.4999 |
1249.75 |
35-44 |
0.1416 |
354 |
45+ |
0.0016 |
4 |
Total |
1 |
2500 |
E3500<15 = 2500*P<15 = 2500*0.0015 = 3.75
E350015-24 = 2500*P15-24 = 2500*0.3554 = 888.5
E350025-34 = 2500*P25-34 = 2500*0.4999 = 1249.75
E350035-44= 2500*P35-44 = 2500*0.1416 = 354
E350045+ = 2500*P45+ = 2500*0.0016 = 4
In
random samples of 2500 year 2006 United States Resident Live Births, approximately
3.75 sampled births are to mothers aged less than 15 years.
In
random samples of 2500 year 2006 United States Resident Live Births,
approximately 888.5 sampled births are to mothers aged between 15 and 24 years.
In
random samples of 2500 year 2006 United States Resident Live Births,
approximately 1249.5 sampled births are to mothers aged between 25 and 34
years.
In
random samples of 2500 year 2006 United States Resident Live Births,
approximately 354 sampled births are to mothers aged between 35 and 44 years.
In
random samples of 2500 year 2006 United States Resident Live Births,
approximately 4 sampled births are to mothers aged 45 or more years.
Case Three | Random Variables Pair of Dice | Random Variable
We
have a pair of dice– note the probability models for the dice
below.
1st
d5 |
2nd d3 |
||
Face |
Probability |
Face |
Probability |
2 |
1/5 |
1 |
15/30 |
3 |
1/5 |
7 |
5/30 |
4 |
1/5 |
8 |
10/30 |
5 |
1/5 |
Total |
30/30=1 |
6 |
1/5 |
|
|
Total |
5/5=1 |
|
|
We assume that the dice operate separately and independently of each other. Suppose that our experiment consists of tossing the dice, and noting the resulting face-value-pair.
SUM = “Sum of the Two Face Values
in the Pair” and
1. List all the
possible pairs of face values, and compute the probability for each pair,
showing full detail.
(2,1), (2,7), (2,8), (3,1), (3,7), (3,8), (4,1), (4,7),
(4,8), (5,1), (5,7), (5,8), (6,1), (6,7), (6,8)
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
2. Compute the values of SUM, showing in detail how these
values are computed from each pair of face values.
SUM
SUM
SUM
SUM
SUM
SUM
SUM
SUM
SUM
SUM
SUM
SUM
SUM
SUM
SUM
3. Compute the probability for each value of SUM from step 2,
showing full detail.
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Pr
Show all work and
detail for full credit.
Case Four | Color Slot Machine | Conditional Probabilities
Using the slot machine from Case One,
Compute Pr
Sequence |
Probability |
RBRRYRGG |
.10 |
RRGGBRRB |
.10 |
BBYYYGBR |
.15 |
GRRGGRGG |
.10 |
BGYYYRYY |
.25 |
RRYYGRRB |
.10 |
YYGBYYBR |
.20 |
Total |
1.00 |
Pr
RRYYGRRB or YYGBYYBR Shows} = Pr
Pr
Sequence |
Probability |
RBRRYRGG |
.10 |
BBYYYGBR |
.15 |
BGYYYRYY |
.25 |
RRYYGRRB |
.10 |
YYGBYYBR |
.20 |
Total |
.80 |
Pr
RRYYGRRB or YYGBYYBR Shows} = Pr
Pr
Pr
Compute Pr
Sequence |
Probability |
RBRRYRGG |
.10 |
RRGGBRRB |
.10 |
BBYYYGBR |
.15 |
BGYYYRYY |
.25 |
RRYYGRRB |
.10 |
YYGBYYBR |
.20 |
Total |
.90 |
Pr
RRYYGRRB or YYGBYYBR Shows} = Pr
Pr
Sequence |
Probability |
RBRRYRGG |
.10 |
BBYYYGBR |
.15 |
BGYYYRYY |
.25 |
RRYYGRRB |
.10 |
YYGBYYBR |
.20 |
Total |
.80 |
Pr
RRYYGRRB or YYGBYYBR Shows} = Pr
Pr
Pr
Compute Pr
Sequence |
Probability |
RBRRYRGG |
.10 |
RRGGBRRB |
.10 |
BBYYYGBR |
.15 |
GRRGGRGG |
.10 |
BGYYYRYY |
.25 |
RRYYGRRB |
.10 |
YYGBYYBR |
.20 |
Total |
1.00 |
Pr
RRYYGRRB or YYGBYYBR Shows} = Pr
Pr
Sequence |
Probability |
RBRRYRGG |
.10 |
RRGGBRRB |
.10 |
BBYYYGBR |
.15 |
BGYYYRYY |
.25 |
RRYYGRRB |
.10 |
YYGBYYBR |
.20 |
Total |
.90 |
Pr
RRYYGRRB or YYGBYYBR Shows} = Pr
Pr
Pr
Work all four (4) cases. Show complete work and detail for full credit.