Key
The 1st Hourly
Math 1107
Fall Semester
2007
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.
Sign and Acknowledge:
I agree to follow this protocol.
Name (PRINTED) Signature Date
Case One: Random Variables, Pair of Dice
We have a pair of
independently operating, fair, dice: the first die with face values 1,2,4,5 and the second die with face values 0,3. Each trial of our experiment
involves tossing the pair of dice, and noting the pair of face values. We
compute a random variable from the pair of face values as follows: Consider
the random variable THING, where THING = 10 − SUM, where SUM is the sum
of the face values in the pair.
1. List all the possible pairs of face values,
and compute the probability for each pair, showing full detail.
2.
Compute the values of THING, showing in detail how these values are
computed from each pair of face values.
3. Compute the probability for each value of THING from step 2,
showing full detail.
Show
full work and detail for full credit.
1.
|
|
1 |
2 |
4 |
5 |
|
0 |
(1,0) |
(2,0) |
(4,0) |
(5,0) |
|
3 |
(1,3) |
(2,3) |
(4,3) |
(5,3) |
There are eight (8) pairs: (1,0), (2,0), (4,0),
(5,0), (1,3), (2,3), (4,3), (5,3).
Pr{(1,0) Shows} = Pr{1 from 1st
Die Shows}*Pr{0 from 2nd Die Shows} = (1/4)*(1/2) = 1/8
Pr{(2,0) Shows} = Pr{2 from 1st
Die Shows}*Pr{0 from 2nd Die Shows} = (1/4)*(1/2) = 1/8
Pr{(4,0) Shows} = Pr{4 from 1st
Die Shows}*Pr{0 from 2nd Die Shows} = (1/4)*(1/2) = 1/8
Pr{(5,0) Shows} = Pr{5 from 1st
Die Shows}*Pr{0 from 2nd Die Shows} = (1/4)*(1/2) = 1/8
Pr{(1,3) Shows} = Pr{1 from 1st
Die Shows}*Pr{3 from 2nd Die Shows} = (1/4)*(1/2) = 1/8
Pr{(2,3) Shows} = Pr{2 from 1st
Die Shows}*Pr{3 from 2nd Die Shows} = (1/4)*(1/2) = 1/8
Pr{(4,3) Shows} = Pr{4 from 1st
Die Shows}*Pr{3 from 2nd Die Shows} = (1/4)*(1/2) = 1/8
Pr{(5,3) Shows} = Pr{5 from 1st
Die Shows}*Pr{3 from 2nd Die Shows} = (1/4)*(1/2) = 1/8
2.
THING = 10 − SUM
|
|
1 |
2 |
4 |
5 |
|
0 |
(1,0) THING=10−(1+0)=9 |
(2,0) THING=10−(2+0)=8 |
(4,0) THING=10−(4+0)=6 |
(5,0) THING=10−(5+0)=5 |
|
3 |
(1,3) THING=10−(1+3)=6 |
(2,3) THING=10−(2+3)=5 |
(4,3) THING=10−(4+3)=3 |
(5,3) THING=10−(5+3)=2 |
THING{(1,0)}=10 − SUM{(1,0)}= 10
− (1+0) = 10 − 1 = 9
THING{(2,0)}=10 − SUM{(2,0)}= 10
− (2+0) = 10 − 2 = 8
THING{(4,0)}=10 − SUM{(4,0)}= 10
− (4+0) = 10 − 4 = 6
THING{(5,0)}=10 − SUM{(5,0)}= 10
− (5+0) = 10 − 5 = 5
THING{(1,3)}=10 − SUM{(1,3)}= 10
− (1+3) = 10 − 4 = 6
THING{(2,3)}=10 − SUM{(2,3)}= 10
− (2+3) = 10 − 5 = 5
THING{(4,3)}=10 − SUM{(4,3)}= 10
− (4+3) = 10 − 7 = 3
THING{(5,3)}=10 − SUM{(5,3)}= 10
− (5+3) = 10 − 8 = 2
3.
Pr{THING=2}=Pr{(5,3) Shows} = 1/8 = .125
Pr{THING=3}=Pr{(4,3) Shows} = 1/8 = .125
Pr{THING=5}=Pr{One of (5,0), (2,3) Shows} =
Pr{(5,0) Shows} + Pr{(2,3) Shows}=(1/8)+(1/8) = 2/8 = 1/4 = .25
Pr{THING=6}=Pr{One of (4,0), (1,3) Shows} =
Pr{(4,0) Shows} + Pr{(1,3) Shows}=(1/8)+(1/8) = 2/8 = 1/4 = .25
Pr{THING=8}=Pr{(2,0) Shows} = 1/8 = .125
Pr{THING=9}=Pr{(1,0) Shows} = 1/8 = .125
Case Two: Long Run Argument, Perfect
Samples, Kerpuztin’s Syndrome, Type F
Severity of cases
of Kerpuztin’s Syndrome, Type F (KSF) is noted as: (F)atal, (S)evere,
(Mo)derate, or (Mi)ld. Suppose that severity levels for the population of
Kerpuztin’s Syndrome (KS) patients are distributed as indicated below:
|
Severity |
Probability |
|
Fatal |
.35 |
|
Severe |
.05 |
|
Moderate |
.40 |
|
Mild |
.20 |
|
Total |
1.00 |
In our experiment, we draw individual patients (with replacement)
from the KSF patient population, noting the severity of the case.
1. Interpret the probabilities in terms of
repeated trials of draws with replacement from the KSF patient
population.
2. Describe the perfect sample for 1100 draws with
replacement from the KSF patient population. Briefly describe the relationship
between this perfect sample and actual samples of 1100 draws with replacement
from the KSF patient population.
Show
full work and detail for full credit.
1.
In long runs of sampling with replacement,
approximately 35% of sampled patients diagnosed with Kerpuztin’s Syndrome Type
F die.
In long runs of sampling with replacement,
approximately 5% of sampled patients diagnosed with Kerpuztin’s Syndrome Type F
present severe symptoms.
In long runs of sampling with replacement,
approximately 40% of sampled patients diagnosed with Kerpuztin’s Syndrome Type
F present moderate symptoms.
In long runs of sampling with replacement,
approximately 20% of sampled patients diagnosed with Kerpuztin’s Syndrome Type
F present mild symptoms.
2.
|
Severity |
Probability |
Expected Count(n=1100) |
|
Fatal |
0.35 |
1100*.35
= 385 |
|
Severe |
0.05 |
1100*.05
= 55 |
|
Moderate |
0.4 |
1100*.40
= 440 |
|
Mild |
0.2 |
1100*.20
= 220 |
|
Total |
1 |
1100*1 =
1100 |
“Expected Fatal Count for n=1100” =
1100*Pr{Fatal} = 1100*.35 = 385
“Expected Fatal Count for n=1100” =
1100*Pr{Severe} = 1100*.05 = 55
“Expected Fatal Count for n=1100” =
1100*Pr{Moderate} = 1100*.40 = 440
“Expected Fatal Count for n=1100” =
1100*Pr{Mild} = 1100*.20 = 220
In random samples of 1100 patients
diagnosed with Kerpuztin’s Syndrome Type F with replacement, approximately 385
sampled patients die.
In random samples of 1100 patients
diagnosed with Kerpuztin’s Syndrome Type F with replacement, approximately 55
sampled patients present severe symptoms.
In random samples of 1100 patients
diagnosed with Kerpuztin’s Syndrome Type F with replacement, approximately 440
sampled patients present moderate symptoms.
In random samples of 1100 patients
diagnosed with Kerpuztin’s Syndrome Type F with replacement, approximately 220
sampled patients present mild symptoms.
Case Three:
Conditional Probability, Color Slot Machine
Here is our slot
machine – on each trial, it produces an 8-color sequence, using the table
below:
|
Sequence* |
Probability |
|
RRBBRRYR |
.10 |
|
RRRGBRRB |
.11 |
|
BYGGYGBR |
.14 |
|
GRGYBRGG |
.10 |
|
YYYRYGYY |
.20 |
|
RYGRRBBY |
.15 |
|
YYYYBGRR |
.20 |
|
Total |
1.00 |
Compute the following conditional
probabilities: Show full work and detail
for full credit.
1. Pr{“BBR” Shows | Yellow Shows}
2. Pr{ “BR” Shows | Green Shows }
3. Pr{Blue Shows | Red Shows}
1.
|
Sequence* |
Probability |
|
RRBBRRYR |
.10 |
|
BYGGYGBR |
.14 |
|
GRGYBRGG |
.10 |
|
YYYRYGYY |
.20 |
|
RYGRRBBY |
.15 |
|
YYYYBGRR |
.20 |
|
Total |
.89 |
Pr{Yellow
Shows} = Pr{One of RRBBRRYR, BYGGYGBR,
GRGYBRGG, YYYRYGYY, RYGRRBBY, YYYYBGRR Shows} =
Pr{RRBBRRYR
Shows}+ Pr{BYGGYGBR Shows}+ Pr{GRGYBRGG Shows}+ Pr{YYYRYGYY Shows}+ Pr{RYGRRBBY
Shows}+
Pr{YYYYBGRR
Shows} = .10 + .14 + .10 + .20 + .15 + .20 = .89
|
Sequence* |
Probability |
|
RRBBRRYR |
.10 |
|
Total |
.10 |
Pr{“BBR” and
Yellow Show} = Pr{RRBBRRYR} = .10
Pr{“BBR” Shows
| Yellow Shows}= Pr{“BBR” and Yellow Show}/ Pr{Yellow Shows} = .10/.89
2.
|
Sequence* |
Probability |
|
RRRGBRRB |
.11 |
|
BYGGYGBR |
.14 |
|
GRGYBRGG |
.10 |
|
YYYRYGYY |
.20 |
|
RYGRRBBY |
.15 |
|
YYYYBGRR |
.20 |
|
Total |
.90 |
Pr{Green Shows}
= Pr{One of RRRGBRRB, BYGGYGBR, GRGYBRGG, YYYRYGYY, RYGRRBBY, YYYYBGRR Shows}=
Pr{RRRGBRRB
Shows}+ Pr{BYGGYGBR Shows}+ Pr{GRGYBRGG Shows}+ Pr{YYYRYGYY Shows}+ Pr{RYGRRBBY
Shows}+
Pr{YYYYBGRR
Shows}= .11 + .14 + .10 + .20 + .15 + .20 = .90
|
Sequence* |
Probability |
|
RRRGBRRB |
.11 |
|
BYGGYGBR |
.14 |
|
GRGYBRGG |
.10 |
|
Total |
.35 |
Pr{“BR” and
Green Show} = Pr{One of RRRGBRRB, BYGGYGBR, GRGYBRGG = .11
+ .14 + .10 = .35
Pr{“BR”
Shows | Green Shows} = Pr{“BR” and Green Show}/Pr{Green Shows} = .35/.90
3.
|
Sequence* |
Probability |
|
RRBBRRYR |
.10 |
|
RRRGBRRB |
.11 |
|
BYGGYGBR |
.14 |
|
GRGYBRGG |
.10 |
|
YYYRYGYY |
.20 |
|
RYGRRBBY |
.15 |
|
YYYYBGRR |
.20 |
|
Total |
1.00 |
Pr{Red Shows} =
Pr{One of RRBBRRYR, RRRGBRRB, BYGGYGBR, GRGYBRGG, YYYRYGYY, RYGRRBBY, YYYYBGRR
Shows}=
Pr{ RRBBRRYR
Shows} + Pr{RRRGBRRB Shows}+ Pr{BYGGYGBR Shows}+ Pr{GRGYBRGG Shows}+
Pr{YYYRYGYY Shows}+ Pr{RYGRRBBY Shows}+ Pr{YYYYBGRR Shows}= .10 + .11 + .14 +
.10 + .20 + .15 + .20 = 1
|
Sequence* |
Probability |
|
RRBBRRYR |
.10 |
|
RRRGBRRB |
.11 |
|
BYGGYGBR |
.14 |
|
GRGYBRGG |
.10 |
|
RYGRRBBY |
.15 |
|
YYYYBGRR |
.20 |
|
Total |
.80 |
Pr{Blue and Red
Show} = Pr{One of RRBBRRYR, RRRGBRRB, BYGGYGBR, GRGYBRGG, RYGRRBBY, YYYYBGRR
Shows}=
Pr{ RRBBRRYR
Shows} + Pr{RRRGBRRB Shows}+ Pr{BYGGYGBR Shows}+ Pr{GRGYBRGG Shows}+
Pr{YYYRYGYY Shows}+ Pr{RYGRRBBY Shows}+ Pr{YYYYBGRR Shows}= .10 + .11 + .14 +
.10 + .15 + .20 = .80
Pr{Blue Shows |
Red Shows} = Pr{Blue and Red Show}/Pr{Red Shows} = .80/1
Case Four: Probability
Computation Rules, Color Slot Machine
Here is our slot
machine – on each trial, it produces a 10-color sequence, using the table
below:
|
Sequence* |
Probability |
|
RRBBRRYRGG |
.10 |
|
RRGGRGBRRB |
.10 |
|
BBYYGGYGBR |
.15 |
|
GRRGGYBRGG |
.10 |
|
BGYYYRYGYY |
.25 |
|
RRYYGRRBBY |
.10 |
|
YYGBYYBGRR |
.20 |
|
Total |
1.00 |
1.
|
Sequence* |
REDCOUNT |
Probability |
|
RRBBRRYRGG |
5 |
.10 |
|
RRGGRGBRRB |
5 |
.10 |
|
BBYYGGYGBR |
1 |
.15 |
|
GRRGGYBRGG |
3 |
.10 |
|
BGYYYRYGYY |
1 |
.25 |
|
RRYYGRRBBY |
4 |
.10 |
|
YYGBYYBGRR |
2 |
.20 |
|
Total |
|
1.00 |
Pr{REDCOUNT=3
or 4} = Pr{REDCOUNT=3} + Pr{REDCOUNT=4} = Pr{GRRGGYBRGG
Shows} + Pr{RRYYGRRBBY Shows} = .10 + .10 = .20
2.
|
Sequence* |
Probability |
|
BGYYYRYGYY |
.25 |
|
YYGBYYBGRR |
.20 |
|
Total |
.45 |
Pr{“BG” Shows}
= Pr{One of BGYYYRYGYY, YYGBYYBGRR Shows} = Pr{BGYYYRYGYY
Shows} + Pr{YYGBYYBGRR Shows} = .25+.20 = .45
3.
|
Sequence* |
Probability |
|
RRBBRRYRGG |
.10 |
|
RRGGRGBRRB |
.10 |
|
BBYYGGYGBR |
.15 |
|
GRRGGYBRGG |
.10 |
|
BGYYYRYGYY |
.25 |
|
RRYYGRRBBY |
.10 |
|
YYGBYYBGRR |
.20 |
|
Total |
1.00 |
Pr{Yellow Does Not Show} = Pr{ RRGGRGBRRB Shows} = .10
Pr{Yellow Shows} = 1 − Pr{Yellow Does
Not Show} = 1 − .10 = .90
Check:
|
Sequence* |
Probability |
|
RRBBRRYRGG |
.10 |
|
BBYYGGYGBR |
.15 |
|
GRRGGYBRGG |
.10 |
|
BGYYYRYGYY |
.25 |
|
RRYYGRRBBY |
.10 |
|
YYGBYYBGRR |
.20 |
|
Total |
.90 |
Pr{Yellow Shows} = Pr{One of RRBBRRYRGG,
BBYYGGYGBR, GRRGGYBRGG, BGYYYRYGYY, RRYYGRRBBY, YYGBYYBGRR Shows} =
Pr{RRBBRRYRGG Shows}+Pr{BBYYGGYGBR
Shows}+Pr{GRRGGYBRGG Shows}+Pr{BGYYYRYGYY Shows}+Pr{RRYYGRRBBY
Shows}+Pr{YYGBYYBGRR Shows} = .10 + .15 + .10 + .25 + .10 + .20 = .90
Show
full work and detail for full credit. Be
certain that you have worked all four (4) cases. Show full work and detail for full
credit.