Key, Version A

The 1st Hourly

Math 1107

Spring 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 fair dice – a d2 {faces 4, 5} and a d6 {faces 0, 2, 4, 5, 6, 8}. 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-pair.

 

a) List the possible face-pairs, and compute a probability for each.

 

Writing the pair as (d6 face value, d2 face value), here are the possible pairs:

 

(0,4)

(2,4)

(4,4)

(5,4)

(6,4)

(8,4)

(0,5)

(2,5)

(4,5)

(5,5)

(6,5)

(8,5)

 

Pr{(0,4)}=Pr{0 from d2}*Pr{4 from d6} = (1/2)*(1/6) = 1/12

Pr{(2,4)}=Pr{2 from d2}*Pr{4 from d6} = (1/2)*(1/6) = 1/12

Pr{(4,4)}=Pr{4 from d2}*Pr{4 from d6} = (1/2)*(1/6) = 1/12

Pr{(5,4)}=Pr{5 from d2}*Pr{4 from d6} = (1/2)*(1/6) = 1/12

Pr{(6,4)}=Pr{6 from d2}*Pr{4 from d6} = (1/2)*(1/6) = 1/12

Pr{(8,4)}=Pr{8 from d2}*Pr{4 from d6} = (1/2)*(1/6) = 1/12

 

Pr{(0,5)}=Pr{0 from d2}*Pr{5 from d6} = (1/2)*(1/6) = 1/12

Pr{(2,5)}=Pr{2 from d2}*Pr{5 from d6} = (1/2)*(1/6) = 1/12

Pr{(4,5)}=Pr{5 from d2}*Pr{5 from d6} = (1/2)*(1/6) = 1/12

Pr{(5,5)}=Pr{5 from d2}*Pr{5 from d6} = (1/2)*(1/6) = 1/12

Pr{(6,5)}=Pr{6 from d2}*Pr{5 from d6} = (1/2)*(1/6) = 1/12

Pr{(8,5)}=Pr{8 from d2}*Pr{5 from d6} = (1/2)*(1/6) = 1/12

 

 

b) Define HIGHTIE as the higher of the two face values or common value if tied, and LOWTIE as the lower of the two face values or common value if tied. Consider the random variable MIDDLE = (HIGHTIE − LOWTIE)/2. Compute the values and probabilities for MIDDLE.

 

 

(0,4) ® Hightie=4, Lowtie=0 ® Middle=(4-0)/2=2

(2,4) ® Hightie=4, Lowtie=2 ® Middle=(4-2)/2=1

(4,4) ® Hightie=4, Lowtie=4 ® Middle=(4-4)/2=0

(5,4) ® Hightie=5, Lowtie=4 ® Middle=(5-4)/2=1/2

(6,4) ® Hightie=6, Lowtie=4 ® Middle=(6-4)/2=1

(8,4) ® Hightie=8, Lowtie=4 ® Middle=(8-4)/2=2

 

(0,5) ® Hightie=5, Lowtie=0 ® Middle=(5-0)/2=5/2

(2,5) ® Hightie=5, Lowtie=2 ® Middle=(5-2)/2=3/2

(4,5) ® Hightie=5, Lowtie=4 ® Middle=(5-4)/2=1/2

(5,5) ® Hightie=5, Lowtie=5 ® Middle=(5-5)/2=0

(6,5) ® Hightie=6, Lowtie=5 ® Middle=(6-5)/2=1/2

(8,5) ® Hightie=8, Lowtie=5 ® Middle=(8-5)/2=3/2

 

Pr{MIDDLE=0} = Pr{one of (4,4),(5,5) shows} = Pr{(4,4)}+Pr{(5,5)} = (1/12)+(1/12) = 2/12

Pr{MIDDLE=1/2} = Pr{one of (5,4),(4,5),(6,5) shows} = Pr{(5,4)}+Pr{(4,5)} +Pr{(6,5)} = (1/12)+(1/12) +(1/12) = 3/12

Pr{MIDDLE=1} = Pr{one of (2,4),(6,4) shows} = Pr{(2,4)}+Pr{(6,4)} = (1/12)+(1/12) = 2/12

Pr{MIDDLE=3/2} = Pr{one of (2,5),(8,5) shows} = Pr{(2,5)}+Pr{(8,5)} = (1/12)+(1/12) = 2/12

Pr{MIDDLE=2} = Pr{one of (0,4),(8,4) shows} = Pr{(0,4)}+Pr{(8,4)} = (1/12)+(1/12) = 2/12

Pr{MIDDLE=5/2} = Pr{(0,5) shows} = 1/12

 

Case Two

Probability Rules

Color Slot Machine

Here is our color slot machine – on each trial, it produces a 4-color sequence, using the table below: 

Color Sequence*

Color Sequence Probability

GBRB

0.150

BBGG

0.150

GBBR

0.300

RGYB

0.060

YYYY

0.040

BBYY

0.180

RRYY

0.020

YBGR

0.100

Total

1.000

*B-Blue, G-Green, R-Red, Y-Yellow, Sequence is numbered as 1st to 4th, from left to right: (1st 2nd 3rd 4th)

Compute the following probabilities. In each of the following, show your intermediate steps and work. If a rule is specified, you must use that rule for your computation.

 

a) Pr{Green Shows} Briefly interpret each probability using a long run or relative frequency argument.

 

Color Sequence*

Color Sequence Probability

GBRB

0.150

BBGG

0.150

GBBR

0.300

RGYB

0.060

YBGR

0.100

Total

 

 

Pr{Green Shows} = Pr{one of GBRB, BBGG,GBBR,RGYB,YBGR shows} = Pr{GBRB}+ Pr{BBGG} + Pr{GBBR} + Pr{RGYB} + Pr{YBGR shows} = .15+.15+.30+.06+.10 = .76

In long runs of box-plays, approximately 76% of plays will show green.

 

b) Pr{Green or Blue Show} - Use the Complementary Rule. Briefly interpret each probability using a long run or relative frequency argument.

 

Color Sequence*

Color Sequence Probability

GBRB

0.150

BBGG

0.150

GBBR

0.300

RGYB

0.060

BBYY

0.180

YBGR

0.100

 

 

Color Sequence*

Color Sequence Probability

YYYY

0.040

RRYY

0.020

 

Pr{Neither Green nor Blue Shows}=Pr{One of YYYY,YYRR Shows}=Pr{YYYY}+Pr{RRYY}=.04+.02=.06

 

Pr{Green or Blue Shows} = 1 - Pr{Neither Green nor Blue Shows}= 1 - .06 = .94

 

Pr{Green or Blue Shows}=Pr{one of GBRB, BBGG,GBBR,RGYB,BBYY,YBGR shows} = = Pr{GBRB}+ Pr{BBGG} + Pr{GBBR} + Pr{RGYB} + +Pr{BBYY} + Pr{YBGR shows} =.15+.15+.30+.06+.18+.10 = .94

In long runs of box-plays, approximately 94% of plays will show blue or green.

 

c) Pr{Green Shows | Blue Shows} - This is a conditional probability.

 

Color Sequence*

Color Sequence Probability

GBRB

0.150

BBGG

0.150

GBBR

0.300

RGYB

0.060

BBYY

0.180

YBGR

0.100

Total

.94

 

 

Pr{Blue Shows}=Pr{one of GBRB, BBGG,GBBR,RGYB,BBYY,YBGR shows} = Pr{GBRB}+ Pr{BBGG} + Pr{GBBR} + Pr{RGYB} + Pr{BBYY} + Pr{YBGR shows} =.15+.15+.30+.06+.18+.10 = .94

 

Pr{Blue and Green Show}=Pr{one of GBRB, BBGG,GBBR,RGYB, YBGR shows} = Pr{GBRB}+ Pr{BBGG} + Pr{GBBR} + Pr{RGYB} + Pr{YBGR shows} =.15+.15+.30+.06+.10 = .76

 

Pr{Green Shows | Blue Shows} = Pr{Green and Blue Show}/ Pr{Blue Shows} = .76/.94 ».8085

 

Case Three

Long Run Argument / Perfect Samples

Prevalence of Viral Subtypes in an Infected Population

 

Suppose that we have a virus, say XCV. Suppose further that XCV has known main types A, B, C and D. Infected individuals may present one or more types of XCV. Suppose that the probabilities for XCV types present in infected individuals are noted below:

 

XCV Profile

Probability

XCV−A

0.65

XCV−B

0.18

XCV−C

0.07

XCV−D

0.03

XCV−Multiple Types Present

0.05

XCV−Type or Types Unknown

0.02

Total

1.00

 

a) Interpret each probability using the Long Run Argument. Be specific and complete for full credit.                                                                                                                                              

 

In long runs of sampling XCV cases with replacement, approximately 65% of sampled cases present type A, approximately 18% present type B, approximately 7% present type C, approximately 3% present type D, approximately 5% present multiple types of XCV and approximately 2% present unknown types of XCV.

 

b) Compute the perfect sample of n=3,500 XCV-infected individuals, and describe the relationship of this perfect sample to real random samples of XCV-infected individuals.

 

XCV Profile

Probability

Expected Count

n=3500

XCV−A

0.65

.65*3500=2275

XCV−B

0.18

.18*3500=630

XCV−C

0.07

.07*3500=245

XCV−D

0.03

.03*3500=105

XCV−Multiple Types Present

0.05

.05*3500=175

XCV−Type or Types Unknown

0.02

.02*3500=70

Total

1

3500

 

 

E3500{XCV−A} = 3500*Pr{ XCV−A} = 3500*.65 = 2275

E3500{XCV−B} = 3500*Pr{ XCV−B} = 3500*.18 = 630

E3500{XCV−C} = 3500*Pr{ XCV−C} = 3500*.07 = 245

E3500{XCV−D} = 3500*Pr{ XCV−D} = 3500*.03 = 105

E3500{XCV−Multiple} = 3500*Pr{ XCV−Multiple} = 3500*.05 = 175

E3500{XCV−Unknown} = 3500*Pr{ XCV−Unknown} = 3500*.02 = 70

 

Random samples of 3,500 XCV cases, will contain approximately 2,275 cases presenting type A, approximately 630 cases presenting type B, approximately 245 cases presenting type C, approximately 105 cases presenting type D, approximately 175 cases presenting multiple types of XCV and approximately 70 cases  presenting unknown types of XCV.

 

 

Case Four

Three Dice

Probability Model/Random Variable

 

Suppose we have three fair dice: d2(faces 1,2), d2(faces 3,4) and d2(faces 5,6). In our experiment, we toss this triplet of dice, and note the face value from each die. For simplicity, we write the outcome as (1st d2 result, 2nd d2 result, 3rd d2 result). Assume that the dice operate independently and separately. A triplet is like a pair, only with three items, rather than two.

 

a) List the possible face value triplets, and compute a probability for each face value triplet.                                                                                                                                                               

 

There are 2*2*2=8 possible triplets: (1,3,5), (1,3,6), (1,4,5), (1,4,6), (2,3,5), (2,3,6), (2,4,5), (2,4,6).

 

Pr{(1,3,5)} = Pr{1 from 1st d2}*Pr{3 from 2nd d2}*{5 from 3rd d2} = (1/2)*(1/2)*(1/2) = 1/8

Pr{(1,3,6)} = Pr{1 from 1st d2}*Pr{3 from 2nd d2}*{6 from 3rd d2} = (1/2)*(1/2)*(1/2) = 1/8

Pr{(1,4,5)} = Pr{1 from 1st d2}*Pr{4 from 2nd d2}*{5 from 3rd d2} = (1/2)*(1/2)*(1/2) = 1/8

Pr{(1,4,6)} = Pr{1 from 1st d2}*Pr{4 from 2nd d2}*{6 from 3rd d2} = (1/2)*(1/2)*(1/2) = 1/8

Pr{(2,3,5)} = Pr{2 from 1st d2}*Pr{3 from 2nd d2}*{5 from 3rd d2} = (1/2)*(1/2)*(1/2) = 1/8

Pr{(2,3,6)} = Pr{2 from 1st d2}*Pr{3 from 2nd d2}*{6 from 3rd d2} = (1/2)*(1/2)*(1/2) = 1/8

Pr{(2,4,5)} = Pr{2 from 1st d2}*Pr{4 from 2nd d2}*{5 from 3rd d2} = (1/2)*(1/2)*(1/2) = 1/8

Pr{(2,4,6)} = Pr{2 from 1st d2}*Pr{4 from 2nd d2}*{6 from 3rd d2} = (1/2)*(1/2)*(1/2) = 1/8

 

b) We define SUM as the sum of the faces in the face value triplet as SUM = [1st face] + [2nd face] + [3rd face]. Identify the possible values of SUM, and compute a probability for each value of SUM.

 

SUM{(1,3,5)}  = 1+3+5 =9

SUM{(1,3,6)} = 1+3+6=10

SUM{(1,4,5)} = 1+4+5=10

SUM{(1,4,6)} = 1+4+6=11

SUM{(2,3,5)} = 2+3+5=10

SUM{(2,3,6)} = 2+3+6=11

SUM{(2,4,5)} = 2+4+5=11

SUM{(2,4,6)} = 2+4+6=12

 

Pr{SUM=9} = Pr{(1,3,5)} = 1/8

Pr{SUM=10} = Pr{one of (1,3,6),(1,4,5),(2,3,5) shows} = Pr{(1,3,6)} + Pr{(1,4,5)} + Pr{(2,3,5)} = (1/8)+(1/8)+(1/8) = 3/8

Pr{SUM=11} = Pr{one of (2,3,6),(1,4,6),(2,4,5) shows} = Pr{(1,3,6)} + Pr{(1,4,5)} + Pr{(2,3,5)} = (1/8)+(1/8)+(1/8) = 3/8

Pr{SUM=12} = Pr{(2,4,6)} = 1/8

 

Be certain that you have worked all four (4) cases. Show full work and detail for full credit.