Key | The Comprehensive Final Examination | Math 1107 | Fall Semester 2010 | CJ Alverson

 

Protocol

 

You will use only the following resources: Your individual calculator; Your individual tool-sheets (two (2) 8.5 by 11 inch sheets); Your writing utensils; Blank Paper (provided by me); This copy of the hourly and the tables provided by me. Do not share these resources with anyone else. 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. When you’re done: Print your name on a blank sheet of paper. Place your tool-sheets, test and work under this sheet, and turn it all in to me. Do not share information with any other students during this test.

 

Sign and Acknowledge: I agree to follow this protocol. Initial: ______

 

______________________________________________________________________________

Name (PRINTED)                                          Signature                                          Date

 

Case One | Probability and Random Variables | 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

 

Define ThingYC as the number of times that yellow shows on a sequence. Compute the values and probabilities for ThingYC.

Sequence*

Probability

ThingYC(Yellow Count)

RRBBRRYR

.10

1

RRRGBRRB

.11

0

BYGGYGBR

.14

2

GRGYBRGG

.10

1

YYYRYGYY

.20

6

RYGRRBBY

.15

2

YYYYBGRR

.20

4

Total

1.00

 

 

Pr{ ThingYC = 0 } = Pr{ RRRGBRRB } = 0.11

Pr{ ThingYC = 1 } = Pr{ RRBBRRYR } + Pr{ GRGYBRGG } = 0.10 + 0.10 = 0.20

Pr{ ThingYC = 2 } = Pr{ BYGGYGBR } + Pr{ RYGRRBBY } = 0.14 + 0.15 = 0.29

Pr{ ThingYC = 4 } = Pr{ YYYYBGRR } = 0.20

Pr{ ThingYC = 6 } = Pr{ YYYRYGYY } = 0.20

 

Define RVGR as 1 if “GR” shows on a sequence, and as 0 if “GR” does not show on a sequence. Compute the values and probabilities for RVGR.

Show all work in full detail for full credit.

 

Sequence*

Probability

RVGR(“GR” Shows)

RRBBRRYR

.10

0/No

RRRGBRRB

.11

0/No

BYGGYGBR

.14

0/No

GRGYBRGG

.10

1/Yes

YYYRYGYY

.20

0/No

RYGRRBBY

.15

1/Yes

YYYYBGRR

.20

1/Yes

Total

1.00

 

 

Pr{ RVGR = 1 (“GR” Shows) } =

Pr{ One of GRGYBRGG, RYGRRBBY or YYYYBGRR Shows } =

Pr{ GRGYBRGG } + Pr{ RYGRRBBY } + Pr{ YYYYBGRR } = 0.10 + 0.15 + 0.20 = 0.45

 

Pr{ RVGR = 0 (“GR” Does Not Show) } = 1 – Pr{ RVGR = 1 (“GR” Shows) } = 1 – 0.45 = 0.55

 

or do it the long way …  

 

Pr{ RVGR = 0 (“GR” Does Not Show) } =

Pr{ One of RRBBRRYR, RRRGBRRB, BYGGYGBR or YYYRYGYY Shows } =

Pr{ RRBBRRYR } + Pr{ RRRGBRRB } + Pr{ BYGGYGBR } + Pr{ YYYRYGYY } =

0.10 + 0.11 + 0.14 + 0.20 = 0.35 + 0.20 = 0.55

 

Case Two | Summary Interval | 2009 Fictitious City Iron Man

An Iron Man event comprises a 2.4 mile swim, 112 mile bike course and a full marathon (26.2 mile run). Suppose that we have a random sample of finishers of the 2009 Fictitious City Iron Man, whose finishing times (in hours) are listed below: 

8.25, 8.56, 8.75, 9.10, 9.12, 9.20, 9.22, 9.25, 9.45, 9.85, 10.15, 10.18, 10.20, 10.25, 10.30, 10.46, 10.56, 10.80, 11.05 11.23, 11.30, 11.52, 11.56, 11.60, 11.75, 11.80, 11.95, 12.05, 12.15, 12.18, 12.20, 12.25, 12.28, 12.30, 12.35, 12.45 12.50 12.59, 12.60, 12.70, 12.73, 12.85, 12.90, 13.10, 13.25, 14.15, 15.25, 16.75, 17.30, 18.10

Let m denote the sample mean, and sd the sample standard deviation. Compute and interpret the intervals m±2sd and m±3sd, using Tchebysheff’s Inequalities and the Empirical Rule. Be specific and complete. Show your work, and discuss completely for full credit.

 

lower2 = m – (2*sd) ≈ 11.6878   (2*2.10451)   7.47878

upper2 = m + (2*sd) ≈ 11.6878 + (2*2.10451) 15.8968

 

lower3 = m – (3*sd) ≈ 11.6878   (3*2.10451)   5.37427

upper3 = m + (3*sd) ≈ 11.6878 + (3*2.10451) 18.0013

 

There are 50 people who finished the 2009 Fictitious City Iron Man in our sample. At least 75% of the people in our sample finished the 2009 Fictitious City Iron Man in between 7.48 and 15.90 hours. At least 89% of the people in our sample finished the 2009 Fictitious City Iron Man in between 5.37 and 18.00 hours.

 

If the finish times for the 2009 Fictitious City Iron Man cluster symmetrically around a central value, becoming rare as distance from the center increases, then: Approximately 95% of the people in our sample finished the 2009 Fictitious City Iron Man in between 7.48 and 15.90 hours and approximately 100% of the people in our sample finished the 2009 Fictitious City Iron Man in between 5.37 and 18.00 hours.

 

 

Case Three | Confidence Interval, Population Mean | 2009 Fictitious City Iron Man

 

Using the context and data of Case Two, consider the population mean finish time for the 2009 Fictitious City Iron Man. Compute and interpret a 95% confidence interval for this population mean. Show your work. Completely discuss and interpret your results, as indicated in class and case study summaries.

 

lower95  = m – ( Z*sd  / sqrt(n) ) ≈ 11.6878 – (2*2.10451/sqrt(50)) ≈ 11.0926   

upper95 = m + ( Z*sd  / sqrt(n) ) ≈ 11.6878 – (2*2.10451/sqrt(50)) ≈ 12.2830

Our population is the population of people who finished the 2009 Fictitious City Iron Man, and our population mean is the population mean finish time.

Each member of the Family of Samples is a single random sample of 50 people who finished the 2009 Fictitious City Iron Man.

From each member sample, compute: sample mean finish time m, sample standard deviation sd, then from the means table row  2.00   0.02275    0.95450, use Z = 2. Then compute the interval

 

[lower95 = m – ( Z*sd  / sqrt(n) ), upper95 = m + ( Z*sd  / sqrt(n) )].

 

Doing this for each member of the family of samples yields a family of intervals.

 

Approximately 95% of the intervals in the family cover the unknown population mean. If our interval resides in this 95% supermajority of member intervals, then the true population mean finish time for the 2009 Fictitious City Iron Man is between 11.1 and 12.3 hours.

 

 

Case Four | Median Test | Pick’s Disease and Survival Time

Pick's disease (Frontotemporal Dementia) is a relatively rare, degenerative brain illness that causes dementia. The first description of the disease was published in 1892 by Arnold Pick. Pick's disease is marked by "Pick bodies", rounded, microscopic structures found within affected cells. Neurons swell, taking on a "ballooned" appearance. Pick's disease is usually sharply confined to the front parts of the brain, particularly the frontal and anterior temporal lobes. The first symptoms of Pick's disease are often personality change, and a decline in function at work and home. Eventually, they enter a terminal vegetative state. Suppose that we identify a random sample of deceased cases of Pick’s Disease – time from initial diagnosis to death is given in years:

0, 0, 1, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 6, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 11, 12, 13, 15.

 

Test the following: null (H0): The median time to death from diagnosis is 9 years (h = 9) against the alternative (H1): h < 9. Show your work. Completely discuss and interpret your results, as indicated in class and case study summaries.

 

 

 

0, 0, 1, 1, 1 | 2, 2, 3, 3, 4 | 4, 5, 5, 6, 6 | 6, 7, 7, 7, 7 | 7, 7, 8, 8, 8 | 8, 11, 12, 13, 15.

 

Alternative Hypothesis: “Guess is too Large

Error: Count Below Guess

Error = #{sample cases surviving strictly less than 9 years past diagnosis } = 26

n = 30

 

From 30 26 0.00003, p ≈ 0.00003 (0.003%)

                                    

Null Hypothesis: The median time to death from diagnosis is 9 years

Alternative  Hypothesis: The median time to death from diagnosis < 9 years (Guess is too Large)

Error Function: Number of Cases Surviving Strictly Less Than 9 Years

 

Our population consists of people with Pick’s disease. Our null hypothesis is that the population median time to death from diagnosis is 9 years.

 

Each member of the family of samples (FoS) is a single random sample of 30 people who died with Pick’s disease. The FoS consists of all possible samples of this type.

 

From each member of the (FoS), compute an error as the number of sample cases who survived strictly less than 9 years after diagnosis with Pick’s disease. Computing this error for each member of the FoS forms a family of errors (FoE).

 

If the true population median time to death after diagnosis with Pick’s disease is 9 years, then approximately 0.003% member samples from the FoS yield errors as bad as or worse than our error. The sample presents highly significant evidence against the null hypothesis.

 

 

 

 

Table 1: Means and Proportions

 

 Z(k) PROBRT ROBCENT

0.05   0.48006    0.03988

0.10   0.46017    0.07966

0.15   0.44038    0.11924

0.20   0.42074    0.15852

0.25   0.40129    0.19741

0.30   0.38209    0.23582

0.35   0.36317    0.27366

0.40   0.34458    0.31084

0.45   0.32636    0.34729

0.50   0.30854    0.38292

0.55   0.29116    0.41768

0.60   0.27425    0.45149

0.65   0.25785    0.48431

0.70   0.24196    0.51607

0.75   0.22663    0.54675

0.80   0.21186    0.57629

0.85   0.19766    0.60467

0.90   0.18406    0.63188

0.95   0.17106    0.65789

1.00   0.15866    0.68269

Z(k) PROBRT PROBCENT

1.05   0.14686    0.70628

1.10   0.13567    0.72867

1.15   0.12507    0.74986

1.20   0.11507    0.76986

1.25   0.10565    0.78870

1.30   0.09680    0.80640

1.35   0.08850    0.82298

1.40   0.08075    0.83849

1.45   0.07352    0.85294

1.50   0.06680    0.86639

1.55   0.06057    0.87886

1.60   0.05479    0.89040

1.65   0.04947    0.90106

1.70   0.04456    0.91087

1.75   0.04005    0.91988

1.80   0.03593    0.92814

1.85   0.03215    0.93569

1.90   0.02871    0.94257

1.95   0.02558    0.94882

2.00   0.02275    0.95450

Z(k) PROBRT PROBCENT

2.05   0.020182    0.95964

2.10   0.017864    0.96427

2.15   0.015778    0.96844

2.20   0.013903    0.97219

2.25   0.012224    0.97555

2.30   0.010724    0.97855

2.35   0.009387    0.98123

2.40   0.008198    0.98360

2.45   0.007143    0.98571

2.50   0.006210    0.98758

2.55   0.005386    0.98923

2.60   0.004661    0.99068

2.65   0.004025    0.99195

2.70   .0034670    0.99307

2.75   .0029798    0.99404

2.80   .0025551    0.99489

2.85   .0021860    0.99563

2.90   .0018658    0.99627

2.95   .0015889    0.99682

3.00   .0013499    0.99730

 

Table 2. Medians

 

n error base p-value

30 1 1.00000

30 2 1.00000

30 3 1.00000

30 4 1.00000

30 5 0.99997

30 6 0.99984

30 7 0.99928

30 8 0.99739

30 9 0.99194

30 10 0.97861

n error base p-value

30 11 0.95063

30 12 0.89976

30 13 0.81920

30 14 0.70767

30 15 0.57223

30 16 0.42777

30 17 0.29233

30 18 0.18080

30 19 0.10024

30 20 0.04937

 

n error base p-value

30 21 0.02139

30 22 0.00806

30 23 0.00261

30 24 0.00072

30 25 0.00016

30 26 0.00003

30 27 0.00000

30 28 0.00000

30 29 0.00000

30 30 0.00000