Key | The 3rd
Hourly | Math 1107 | Fall 2009
Protocol
You will use only the
following resources: Your individual calculator; individual tool-sheet (one (1)
8.5 by 11 inch sheet), writing utensils, blank paper
(provided by me) and this copy of the hourly. 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. Do not share information with any other students
during this hourly.
When you
are finished: Prepare a Cover Sheet: Print your name on an otherwise blank
sheet of paper. Then stack your stuff as follows: Cover Sheet (Top),
Your Work Sheets, The Test Papers, Your Toolsheet.
Then hand all of this in to me.
Sign and
Acknowledge: I agree to follow
this protocol.
________________________________________________________________________
Name
(PRINTED)
Signature
Date
Case One | Hypothesis Test – Population
Median | Glioblastoma Multiforme
Glioblastoma multiforme
(GBM) is the highest grade glioma
tumor and is the most malignant form of astrocytomas.
These tumors originate in the brain. GBM tumors grow rapidly, invade nearby
tissue and contain cells that are very malignant. GBM are among the most common
and devastating primary brain tumors in adults.
Suppose that we have a
random sample of GBM patients, with survival time (in months) listed below:
0, 1, 2, 2, 3 | 3, 3, 3, 4, 4 | 4, 4, 4, 5, 5 | 5, 5,
5, 5, 6 | 6, 6, 7, 7, 8 | 8, 8, 9, 10, 10 | 11, 11, 11, 12, 12
12, 13, 13, 13, 14 | 14, 15, 16, 17, 17| 18, 18, 19,
23, 24 | 24, 25, 27, 30, 36 | 38, 40, 58, 60, 61
Test the following: null (H0): The median GBM survival
time is 20 months (h = 20) against the alternative (H1):
h < 20.
Show your work.
Completely discuss and interpret your test results, as indicated in class and
case study summaries.
Null Hypothesis: Median Survival Time = 20
Months
Alternative
Hypothesis: Median Survival Time < 20 Months
(Guess is too Large)
Error Function: Number of Sample Patients
Surviving Strictly Less Than 20 Months
0, 1, 2, 2, 3 | 3, 3, 3, 4, 4 | 4, 4, 4, 5,
5 | 5, 5, 5, 5, 6 | 6, 6, 7, 7, 8 | 8, 8, 9, 10, 10 | 11, 11, 11, 12, 12
12, 13, 13, 13, 14 | 14, 15, 16, 17, 17| 18,
18, 19, ||||20||||, 23, 24 | 24, 25, 27, 30, 36 | 38, 40, 58, 60, 61
sample error = Number of Sample
Patients Surviving Strictly Less Than 20 Months = 48
n = sample size = 60
from 60
48 <0.00001, p < 0.00001 < .01 (p is strictly less than
1/100,000)
Our population consists of patients who
have been diagnosed with and who have died with glioblastoma
multiforme (GBM). Our null hypothesis is that the
population median survival time for this population is 20 months.
Each member of the family of samples (FoS) is a single random sample of
60 patients who have been diagnosed with and who have died with glioblastoma multiforme (GBM).
The FoS consists of all
possible samples of this type.
From each member of the (FoS), compute an error as the
number of sample GBM patients surviving strictly less than 20 months. Computing
this error for each member of the FoS
forms a family of errors (FoE).
If the true population median survival time
for GBM patients is 20 months, then fewer than .001% of member samples from the FoS
yield errors as bas as or worse than our error. The sample presents highly
significant evidence against the null hypothesis.
Case Two | Confidence
Interval: Population Proportion | Glioblastoma Multiforme
Using the Glioblastoma multiforme (GBM)
data from Case One, consider the proportion of GBM patients who
survive 18 months or longer. Compute and interpret a 97% confidence interval
for this population proportion. Show your work. Completely discuss and interpret your test
results, as indicated in class and case study summaries.
0, 1, 2, 2, 3 | 3, 3, 3, 4, 4 | 4, 4, 4, 5,
5 | 5, 5, 5, 5, 6 | 6, 6, 7, 7, 8 | 8, 8, 9, 10, 10 | 11, 11, 11, 12, 12
12, 13, 13, 13, 14 | 14, 15, 16, 17, 17| 18, 18, 19, 23, 24 | 24, 25, 27, 30, 36
| 38, 40, 58, 60, 61
event = GBM patient survives 18 months or longer
e = event count = 15
n = sample size = 60
p = sample proportion of GBM patients surviving 18 months or longer
= 15/60 = .25
sdp = square root of (p*(1 – p)/n ) = sqrt( (.25*.75)/60) )
= 0.055902
from 2.20 0.013903 0.97219, Z=2.20
lower97 = p – (Z*sdp) = .25 – (2.2*0.055902) = 0.12702
upper97 = p + (Z*sdp) = .25 + (2.2*0.055902) = 0.37298
Our population consists of patients who
have been diagnosed with and who have died with glioblastoma
multiforme (GBM). Our population proportion is the
population proportion of GBM patients surviving 18 or more months.
Each member of the family of samples (FoS) is a single random sample of
60 patients who have been diagnosed with and who have died with glioblastoma multiforme (GBM).
The FoS consists of all
possible samples of this type.
From each member of the (FoS), compute:
e = sample count of GBM patients surviving 18 months or longer
p = sample proportion of GBM patients surviving 18 months or longer
= e/60
sdp = square root of (p*(1 – p)/n )
from 2.20 0.013903 0.97219, Z=2.20
and then compute the interval as: lower97 = p – (2.20*sdp), upper97
= p + (2.20*sdp).
Computing this interval for each member of
the FoS forms a family of
intervals (FoI).
Approximately 97% of the FoI captures the true population proportion of GBM patients survivning 18 months or
longer. If our interval resides in this 97% supermajority, then between 12.7%
and 37.2% of GBM patients survive 18 or more months past diagnosis.
Case Three | Confidence
Interval: Population Mean | Gestational Age
Gestational age is the time spent between conception
and birth, usually measured in weeks. In general, infants born after 36 or
fewer weeks of gestation are defined as premature, and may face significant
challenges in health and development. Infants born after 37-40 weeks of
gestation are generally viewed as full term, and those born after 41 or more
weeks of gestation are generally viewed as post term. Suppose that a random
sample of 2007 US resident live born infants yields the following gestational
ages (in weeks):
31, 32, 33, 34, 34, 34, 35,
35, 36, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 38, 38, 38, 38, 38,
38, 38, 38, 38, 38, 38, 38, 38, 39, 39, 39, 39, 39, 39, 40, 40, 40, 40, 40, 40,
40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 42, 42
Estimate the population mean gestational age for 2007 US resident live
born infants with 96% confidence. That
is, compute and discuss a 96% confidence interval for this population mean.
Provide concise and complete details and discussion as demonstrated in the case
study summaries.
n
m sd se Z lower96
upper96
60 38.0167
2.32519 0.30018
2.1 37.3863 38.6470
from 2.10 0.017864 0.96427, Z = 2.1;
se = sd/sqrt(n) = 2.32519/sqrt(60) = 0.30018;
lower96 = m - (z*se) = 38.0167 - (2.1*0.30018) = 37.3863
upper96 = m + (z*se) = 38.0167 + (2.1*0.30018) = 38.6470
Our population consists of US resident live
births occurring in 2007. Our population mean is the population
mean gestational age in weeks.
Each member of the family of samples (FoS) is a single random sample of 60 year 2007 US resident
live born infants.. The FoS consists of all possible samples of this type.
From each member of the (FoS), compute:
m = sample mean gestational age in weeks
sd = sample standard deviation for the sample mean
gestational age in weeks
se = sample standard error = sd/sqrt(60)
from 2.10 0.017864 0.96427, Z = 2.1;
and then compute the interval as: lower96 = m - (2.1*se), upper96 = m + (2.1*se).
Computing this interval for each member of
the FoS forms a family of
intervals (FoI).
Approximately 96% of the FoI captures the true population mean gestational age for
year 2007 US resident live born infants. If our interval resides in this 96%
supermajority, then the population mean gestational
age for year 2007 US resident live born infants is between 37.4 and 38.6 weeks.
Case Four | Hypothesis Test: Categorical Goodness of Fit | Gestational Age
Gestational age is the time spent
between conception and birth, usually measured in weeks. In general, infants
born after 36 or fewer weeks of gestation are defined as premature,
and may face significant challenges in health and development. Infants born
after 37-40 weeks of gestation are generally viewed as full term,
and those born after 41 or more weeks of gestation are generally viewed as post
term. Using the data and context from Case Three, test the
null hypothesis that the 2007 US resident live births are are
distributed as 15% Premature, 82% Full Term and 3% Post Term. Show your work. Completely discuss and
interpret your test results, as indicated in class and case study summaries. Fully discuss the testing procedure and results. This discussion must include a clear discussion of
the population and the null hypothesis, the family of samples, the family of
errors and the interpretation of the p-value.
Prematurity (< 37 weeks): 31, 32, 33, 34, 34 | 34, 35, 35, 36
(9)
Full Term (37-40 weeks): 37, 37, 37, 37, 37| 37, 37, 37, 37, 37|
37, 37, 37, 38, 38| 38, 38, 38, 38, 38|
38, 38, 38, 38, 38| 38, 39, 39, 39, 39| 39, 39, 40, 40, 40| 40, 40,
40, 40, 40| 40, 40, 40, 40, 40| (45)
Post Term (41+ weeks): 41, 41, 41, 41, 42 | 42 (6)
Total = 9 + 45
+ 6 = 54 + 6 = 60
Expected Counts
from the Null Hypothesis for n=60
ePremature = 60*PPremature
= 60*.15 = 9
eFull = 60*PFull
= 60*.82 = 49.2
ePost = 60*PPost
= 60*.03 = 1.8
Error Calculations
errorPremature = (nPremature
– ePremature )2/ ePremature = (9 – 9 )2/ 9 = 0
errorFull = (nFull
– eFull )2/ eFull
= (45 – 49.2 )2/ 49.2 = 0.358536
errorPost = (nPost
– ePost )2/ ePost
= (6 – 1.8 )2/1.8 = 9.80000
errorTotal = errorPremature
+ errorFull
+ errorPost
= 0 + 0.358536
+ 0.000813 + 9.8 = 10.158536
From
3 9.2103 0.010,
p < 0.01 – the p-value is less than 1%.
Interpretation
Our
population consists of US resident live births occurring in 2007. Our categories are based on gestational
age: Prematurity(<37 weeks), Full Term(37-41 weeks)
and Post Term (42 or more weeks). Our
null hypothesis is that the categories are distributed as: 15% Prematurity, 82%
Full Term and 3% Post Term.
Our
Family of Samples (FoS) consists of every possible random sample
of 60 US resident live births occurring in 2007. Under the null hypothesis, within each member of
the FoS, we expect
approximately:
ePremature = 60*PPremature
= 60*.15 = 9
eFull = 60*PFull
= 60*.82 = 49.2
ePost = 60*PPost
= 60*.03 = 1.8
From each member sample of the FoS, we compute sample counts and
errors for each level of survival:
errorPremature = (nPremature
– ePremature )2/ ePremature
errorFull = (nFull
– eFull )2/ eFull
errorPost = (nPost
– ePost )2/ ePost
Then add the individual errors for the
total error as errorTotal = errorPremature
+ errorFull
+ errorPost.
Computing this error for each member sample
of the FoS, we obtain a Family of Errors (FoE).
If
the gestational age categories for US resident live births occurring in 2007
are distributed as 15% Prematurity, 82%
Full Term and 3% Post Term, then less than 1% of the member samples of
the Family of Samples yields errors as large as or larger than that of our
single sample. Our sample presents highly significant evidence against the null
hypothesis.
Work all four (4)
cases.
Table 1. Means and Proportions
Z(k)
PROBRT PROBCENT 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 0.088508
0.82298 1.40 0.080757
0.83849 1.45 0.073529 0.85294 1.50 0.066807
0.86639 1.55 0.060571
0.87886 1.60 0.054799
0.89040 1.65 0.049471
0.90106 1.70 0.044565
0.91087 1.75 0.040059
0.91988 1.80 0.035930
0.92814 1.85 0.032157
0.93569 1.90 0.028717
0.94257 1.95 0.025588
0.94882 2.00 0.022750
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 60
0 1.00000 60 1
1.00000 60 2
1.00000 60 3
1.00000 60 4 1.00000 60 5
1.00000
60 6 1.00000 60 7
1.00000 60 8
1.00000 60 9
1.00000 60 10
1.00000 60 11
1.00000 60 12
1.00000
60 13
0.99999 60 14
0.99998 60 15
0.99993 60 16
0.99980 60 17
0.99947 60 18
0.99866
60 19 0.99689 60 20
0.99326 |
n error base p-value 60
21 0.98633 60 22
0.97405 60 23
0.95377 60 24
0.92250 60 25 0.87747 60 26
0.81685
60 27 0.74052 60 28
0.65056 60 29
0.55129 60 30
0.44871 60 31
0.34944 60 32
0.25948 60 33
0.18315
60 34
0.12253 60 35
0.07750 60 36
0.04623 60 37
0.02595 60 38
0.01367 60 39
0.00674
60 40 0.00311 |
n error base p-value 60
41 0.00134 60 42
0.00053 60 43
0.00020 60 44
0.00007 60 45
0.00002 60 46
0.00001 60 47
<0.00001 60 48
<0.00001 60 49
<0.00001 |
Table 3.
Categories/Goodness of Fit
Categories
ERROR p-value 3 0.0000 1.000 3 0.2107
0.900
3 0.4463 0.800 3 0.7133
0.700
3 1.0217 0.600 3 1.3863
0.500
3 1.5970 0.450 3 1.8326
0.400 3 2.0996
0.350
3 2.4079 0.300 3 2.7726 0.250 3 3.2189
0.200
3 4.6052 0.100 3 4.8159 0.090 3 5.0515
0.080
3 5.3185 0.070 3 5.6268
0.060
3 5.9915 0.050
3 6.4378 0.040 3 7.0131
0.030
3 7.8240 0.020 3 9.2103
0.010 |
Categories
ERROR p-value 4 0.0000 1.000 4 0.5844 0.900 4 1.0052 0.800 4 1.4237 0.700 4 1.8692 0.600 4 2.3660 0.500 4 2.6430 0.450 4 2.9462 0.400 4 3.2831 0.350 4 3.6649 0.300 4 4.1083 0.250 4 4.6416 0.200 4 4.9566 0.175 4 5.3170 0.150 4 5.7394 0.125 4 6.2514 0.100 4 6.4915 0.090 4 6.7587 0.080 4 7.0603 0.070 4 7.4069 0.060 4 7.8147 0.050 4 8.3112 0.040 4 8.9473 0.030 4 9.8374 0.020 4 11.3449 0.010 |
Categories
ERROR p-value 5 0.0000 1.000 5 1.0636 0.900 5 1.6488 0.800 5 2.1947 0.700 5 2.7528 0.600 5 3.3567 0.500 5 3.6871 0.450 5 4.0446 0.400 5 4.4377 0.350 5 4.8784 0.300 5 5.3853 0.250 5 5.9886 0.200 5 6.3423 0.175 5 6.7449 0.150 5 7.2140 0.125 5 7.7794 0.100 5 8.0434 0.090 5 8.3365 0.080 5 8.6664 0.070 5 9.0444 0.060 5 9.4877 0.050 5 10.0255 0.040 5 10.7119 0.030 5 11.6678 0.020 5 13.2767 0.010 |