7th July 2010
Summaries
Session 2.4
Working Case List:
From http://www.cjalverson.com/_2ndhourlysummer2009verAkey.htm :
Case Five | Hypothesis
Test – Population Median | Fictitious Spotted Lizard
The Fictitious Spotted
Lizard is a native species of Lizard Island, and is noteworthy for the both the
quantity and quality of its spots. Consider a random sample of Fictitious
Spotted Lizards, in which the number of spots per lizard is noted:
8, 11, 13, 14, 15, 15, 16, 16, 17, 19, 19, 20, 20, 20, 20,
21, 21, 22, 22, 22, 22, 26, 26, 26, 27, 24, 24, 24, 25, 27
Test the following: null
(H0): The median number of spots per Fictitious Spotted Lizard is
22 (h = 22) against the
alternative (H1): h > 22. 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.
Numbers
Test the following: null
(H0): The median number of spots per Fictitious Spotted Lizard is
22 (h = 22) against the
alternative (H1): h > 22.
Alternative: “Guess is
too small”
Error Form: “Count Strictly
Above 22”
8, 11, 13, 14, 15 | 15, 16, 16, 17, 19 | 19, 20, 20, 20, 20,
21, 21, 22, 22, 22 | 22, 26, 26, 26, 27 | 24, 24, 24, 25, 27
sample size = n = 30
sample error = 9
from 30 9 0.99194 , p » 0.99194
Interpretation
Each member of the family
of sample (FoS) is a single
random sample of 30 Fictitious Spotted lizards. The FoS consists of all possible samples of this type.
From each member sample,
compute the sample number of lizards with strictly more than 22 spots.
Computing this error for each member sample of the FoS yields a family of errors (FoE).
If the true population
median spot count for Fictitious Spotted lizards is 22 spots, then
approximately 99.1% of the errors equal or exceed our error. The sample does
not appear to present significant evidence against the null hypothesis, if the
alternative is a higher guess.
From http://www.mindspring.com/~cjalverson/_2ndhourlysummer2007versionAkey.htm :
Case
Four
Hypothesis Test –
Population Median
Duchenne Muscular Dystrophy:
Survival Time
Duchenne muscular dystrophy (DMD) is an inherited disorder
characterized by rapidly progressive muscle weakness which starts in the legs
and pelvis and later affects the whole body1. Suppose that we follow
individuals diagnosed with DMD from diagnosis until death, noting age at death in months. Consider a random sample of
individuals who were diagnosed with, and died with DMD. Age at death (in
months) follows below:
37 42
47 50 75 80 85 97 100 127 130 143 150 156 173 177 179 180 181 181 182 184 192 193 193 200 210 235 240 278.
Test the following: null (H0):
The median age at death is 180 months (h = 180 months) against the
alternative (H1): h < 180 months. 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. 1. http://www.pennhealth.com/ency/article/000705.htm
Numbers
37 42 47 50 75 80 85 97 100 127 130 143 150 156 173 177 179 | 180 | 181 181 182 184 192 193 193 200 210 235 240 278
n = 30
error = Number of DMD patients
with age at death < 180 months = 17
from 30 17 0.29233
, p @ 0.29233
Interpretation
Population: Patients with Duchenne Muscular Dystrophy(DMD)
Population Median: Median Age at Death
Family of Samples(FoS): Each member is a single
random sample of 30 deceased DMD patients. The FoS consists of all such samples.
For each member of the FoS, compute the number of sample
patients who died at strictly less than 180 months of age. Doing so for every
member of the FoS yields the
Family of Errors.
If the true population
median age at death for DMD patients is 180 months, then the probability of
getting a sample as bad or worse than our sample is
approximately 29.233%. This sample does not seem to present significant
evidence against the Null Hypothesis. We do not reject the Null Hypothesis
at either 5% or 1% significance.
From : http://www.mindspring.com/~cjalverson/_2ndhourlysummer2006_key.htm
Case Two
Median Test
Traumatic Brain Injury
(TBI) and Glasgow Coma Scale (GCS)
The Glasgow Coma Scale (GCS) is the most widely used system for scoring the level of
consciousness of a patient who has had a traumatic brain injury. GCS is based
on the patient's best eye-opening, verbal, and motor responses. Each response
is scored and then the sum of the three scores is computed. That is, GCS=Eye+Verbal+Motor.
Eye opening:
4. Spontaneous. Indicates arousal, not
necessarily awareness; 3. To speech. When
spoken to – not necessarily the command to open eyes; 2. To pain. Applied to limbs, not face where grimacing can
cause closure and 1. None.
Motor response:
6. Obeys commands. Exclude
grasp reflex or postural adjustments; 5. Localises. Other limb moves
to site of nailbed pressure 4. Withdraws. Normal flexion of elbow or knee
to local painful stimulus; 3. Abnormal flexion.
Slow withdrawal with pronation of wrist, adduction of
shoulder 2. Extensor response. Extension of elbow with pronation and
adduction and 1. No movement.
Verbal responses: 5.
Orientated. Knows who, where, when; year, season, month; 4. Confused conversation. Attends & responds but answers
muddled/wrong; 3. Inappropriate words. Intelligible words but mostly expletives or random; 2.
Incomprehensible speech. Moans and groans only – no
words and 1. None.
Glasgow Coma Scale Categories: Mild
(13-15); Moderate (9-12) and Severe/Coma (3-8)
Traumatic brain injury (TBI) is an insult to the brain from an
external mechanical force, possibly leading to permanent or temporary
impairments of cognitive, physical, and psychosocial functions with an
associated diminished or altered state of consciousness. A patient with mild traumatic brain injury is a person who
has had a traumatically induced physiological disruption of brain function, as
manifested by a least one of the following: Any period of loss of consciousness;
Any loss of memory for events immediately before or after the accident; Any
alteration in mental state at the time of the accident (eg,
feeling dazed, disoriented, or confused); Any focal neurological deficit(s)
that may or may not be transient; but where the severity of the injury does not
exceed the following: posttraumatic amnesia (PTA) not greater than 24 hours,
after 30 minutes, an initial Glasgow Coma Scale (GCS) of 13-15; and Any loss of
consciousness of approximately 30 minutes or less. TBI includes: 1) the head
being struck, 2) the head striking an object, and 3) the brain undergoing an
acceleration/deceleration movement (ie, whiplash)
without direct external trauma to the head.
Consider a random sample of patients
with TBI, with GCS at initial treatment and diagnosis listed below:
3, 3, 3, 4, 4, 5, 6, 6,
6, 6, 7, 7, 7, 8, 8, 9, 9, 9, 9, 9, 10, 10, 11, 11, 12, 13, 13, 13, 14, 14
Test the following: null
(H0): The median GCS at initial treatment and diagnosis is (h = 9) against the alternative (H1): h ¹ 9. 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.
Key
3, 3, 3, 4, 4, 5, 6,
6, 6, 6, 7, 7, 7, 8, 8,
9, 9, 9, 9, 9, 10, 10, 11, 11, 12, 13,
13, 13, 14, 14
n=30
error = maximum of ({# sps
< 9}, {# sps > 9}) = maximum of ({15}, {10}) = 15.
From 30 15 0.57223, our p-value is approximately 2*0.57223 »1.14446, which we truncate at 100%.
This sample produces a
nearly perfect split as predicted by the null hypothesis.
Our population consists
of patients with traumatic brain injury (TBI). Each member of the family of
samples is a single random sample of 30 patients with TBI, and the family of
samples (FoS) consists of
all such samples.
Our null hypothesis is
that the median Glasgow coma score (GCS) for newly diagnosed
cases of TBI is 9, against the alternative hypothesis that the
population median is not 9.
The null hypothesis
suggests that the sample should be evenly split across 9. Each member of the FoS yields a pair of counts: the
number of sample patients with GCS < 9, and the number of sample patients
with GCS>9. The error is the larger of these counts.
Error = Maximum of {# sps < 9}, {# sps > 9})
Each member of the FoS yields an error, computed as above, yielding a family
of errors(FoE), in which
each member is an error computed from a member of the FoS.
If the null hypothesis
holds true, then approximately 100% of the errors exceed 15. The sample does
not present significant evidence against the null hypothesis. In fact, this
sample produces a nearly perfect split as predicted by the null hypothesis.
Hypothesis Testing:
Median Test
Super! Logic! Challenge! Box!FTM II
Objective: Be able to
perform the test of the population median. Be able to 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.
ThingCorps FTM
manufactures a product, the Super!Logic!Challenge!Box! FTM
A random sample of boxes is
evaluated by a panel of test players. Each player plays the box, and either
beats, or is beaten by the box. The entire panel of players plays each box. The
percentage of test players beaten by each box is listed below:
55 57 60 64 65 65 68 69 70 71 72 72 73 73 77 77
79 79 80 80 87 88 88 90 96 97 97 97 100 100
Perform the following
tests:
In the following tests,
the following elements are common:
A population of logic
boxes
A Family of Samples, each
member of which is a single random sample of n=30 boxes. The FoS is the collection of all
samples of this type.
Each test leads to a
Family of Errors, based on the individual test.
1. Test a null hypothesis: h
= 50 versus
alternative hypothesis: h ¹
50 ;
The form of the
alternative requires us to compute:
#{sps*
< 50} = 0 (none of the boxes beat fewer than 50% of the players
and
#{sps > 50}=30(every box beats more than 50% of
the players)
*n.b.
sps = Sample Points
The largest of these
counts is 30, so refer error =30 to the n=30 part of the median table. Get the
row 30 30
0.00000 . We get an approximate value of 2*.00000, or
a p-value of approximately 0.00000.
If the median LogicBox success rate is 50%, then fewer
than .0001% of the Family of Samples will yield an error this severe or worse.
The sample is decidedly
incompatible with the null hypothesis.
2. Test a null hypothesis: h
= 65 versus
alternative hypothesis: h > 65 ;
The form of the
alternative requires us to compute:
#{sps
> 65} = 24 (24 of 30 logic boxes beat at least 65% of players}.
So refer error =24 to the
n=30 part of the median table. Get the row 30 24 0.00072
We get an approximate
p-value of 0.00072
If the median LogicBox success rate is 65%, then fewer
than .0072% of the Family of Samples will yield an error this severe or worse.
The sample is decidedly
incompatible with the null hypothesis.
3. Test a null hypothesis: h
= 85 versus
alternative hypothesis: h < 85
The form of the
alternative requires us to compute:
#{sps
< 85} = 20 (20 of 30 logic boxes beat less than 85% of players}.
So refer error =20 to the
n=30 part of the median table. Get the row 30 20 0.04937
We get an approximate
p-value of 0.04937
If the median LogicBox success rate is 85%, then fewer than 4.94% of the
Family of Samples will yield an error this severe or worse.
The sample is kinda' incompatible with the null hypothesis.
Hypothesis Testing
Median Test
Fictitious Large Fruit
Bats II
Objective: Be able to
perform the test of the population
median. Be able to 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.
Fictitious Large Fruit Bats
Consider the following random sample
of Fictitious Large Fruit Bats. The wingspan, in centimeters, of each bat is
presented below:
5, 6.1, 7.15, 7.32, 8, 8.25, 8.8, 9.2, 10, 11.2, 11.4, 12, 12.8,
13.1, 14.15, 14.25, 15, 15.5, 16, 16.5,
17.2, 18, 18.2, 18.75, 19, 21, 22, 27, 28, 33
Perform the following
tests:
In the following tests,
the following elements are common:
A population of Fictitious
Large Fruit Bats
A Family of Samples, each
member of which is a single random sample of n=30 bats. The FoS is the collection of all samples of this type.
Each test leads to a
Family of Errors, based on the individual test.
Test a null hypothesis: h = 8 versus alternative hypothesis: h
¹ 8
;
The form of the
alternative requires us to compute:
#{sps < 8} = 4 (4 of 30 bats have wingspans < 8
cm) and
#{sps > 8}=25(25 of 30 bats have wingspans > 8
cm)
The largest of these
counts is 25, so refer error =25 to the n=30 part of the median table. Get the
row 30 25 0.00016. We get an approximate value of 2*.00016, or a
p-value of approximately 0.00032.
If the median bat
wingspan is 8 cm, then fewer than .032% of the Family
of Samples will yield an error this severe or worse.
The sample is decidedly
incompatible with the null hypothesis.
Test a null hypothesis: h
= 6 versus alternative hypothesis: h > 6 ;
The form of the
alternative requires us to compute:
#{sps > 6}=29(29 of 30 bats have wingspans > 6
cm)
So refer error =29 to the
n=30 part of the median table. Get the row 30 29 0.00000. We get an approximate value of .00000.
If the median bat
wingspan is 6 cm, then fewer than .0001% of the Family
of Samples will yield an error this severe or worse.
The sample is decidedly
incompatible with the null hypothesis.
Test a null hypothesis: h
= 10 versus alternative hypothesis: h < 10
The form of the
alternative requires us to compute:
#{sps < 10} = 8 (8 of 30 bats have wingspans <
10 cm)
So refer error =8 to the
n=30 part of the median table. Get the row 30 8 0.99739 We get an approximate p-value of 99.74%.
If the median bat
wingspan is 10 cm, then fewer than 99.74% of the Family of Samples will yield
an error this severe or worse.
The sample does not
suggest rejection of the null hypothesis.
From: http://www.mindspring.com/~cjalverson/2ndhourlySummer2008Specialkey.htm
Case
Five
Hypothesis Test –
Population Median
Here is another random sample of FHS
adult subjects, listed below:
150/100, 120/82, 154/94, 225/120,
144/88, 142/100, 136/80, 246/110, 135/90, 126/70, 200/130, 204/102, 120/70,
128/90, 240/130, 156/108, 108/70, 176/104, 180/110, 220/110, 145/95, 130/86,
210/94, 160/102, 146/86, 154/96, 150/90, 180/100, 185/115, 145/95
Test the following: null (H0):
The median diastolic blood pressure is 80 mm Hg (h
= 80 mm Hg) against the alternative (H1): h
> 80 mm Hg. 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.
Numbers
h > 80 = “Guess Too Small”
Error = “Number of FHS
Subjects in the Sample whose DBP > 80”
150/100, 120/82,
154/94, 225/120, 144/88, 142/100, 246/110,
135/90, 200/130, 204/102, 128/90, 240/130,
156/108, 176/104, 180/110, 220/110, 145/95,
130/86, 210/94, 160/102, 146/86, 154/96,
150/90, 180/100, 185/115, 145/95
n=30
error = “Number of FHS Subjects whose DBP >
80” = 26 from 30 26 0.00003 , p » .003.
Interpretation
We estimate the median
diastolic blood pressure (DBP) of Framingham Heart Study (FSH) subjects.
Each member of our family
of samples is a single random sample of 30 Framingham Heart Study (FSH)
subjects, and the family of samples consists of all possible samples of this
type.
From each member of the
family of samples, we compute Error = “Number of FHS Subjects in the Sample
whose DBP > 80”.
If the true population
median diastolic blood pressure for Framingham Heart Study (FSH) subjects is
80, then approximately 0.003%(approximately 3 samples
per thousand) of the member samples yield errors as bad as or worse than our
error. Our sample presents highly significant evidence against the null
hypothesis.
Table 2. Medians
n error base p-value 25 1 1.00000 25 2 1.00000 25 3 0.99999 25 4 0.99992 25 5 0.99954 25 6 0.99796 25 7 0.99268 25 8 0.97836 25 9 0.94612 25 10 0.88524 25 11 0.78782 25 12 0.65498 25 13 0.50000 25 14 0.34502 25 15 0.21218 25 16 0.11476 25 17 0.05388 25 18 0.02164 |
n error base p-value 25 19 0.00732 25 20 0.00204 25 21 0.00046 25 22 0.00008 25 23 0.00001 25 23 0.00001 25 24 0.00000 25 25
0.00000 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 30 11 0.95063 |
n error base p-value 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 30 21 0.02139 30 22 0.00806 30 23 0.00261 30 24 0.00072 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 |
From: http://www.mindspring.com/~cjalverson/3rd%20Hourly%20Spring%202007%20Version%20B%20Key.htm
Case One
Hypothesis Test –
Population Median
Fictitious Spotted
Lizard
The Fictitious Spotted
Lizard (FSpL) is a native species of Lizard Island,
and is noteworthy for the both the quantity and quality of its spots. Consider
a random sample of FSpL, in which the number of
spots per lizard is noted:
3, 6, 8, 9, 10, 10, 11,
11, 12, 14, 14, 15, 15, 15, 15, 16, 16, 17, 17, 17, 17, 21, 21, 21, 22, 24, 24,
24, 25, 27
Test the following: null
(H0): The median number of spots per FSpL
is 12 (h = 12) against the alternative (H1):
h > 12.
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.
Numbers
3, 6, 8, 9, 10, 10, 11,
11| 12 |14, 14, 15, 15, 15, 15, 16, 16, 17, 17, 17, 17,
21, 21, 21, 22, 24, 24, 24, 25, 27
8 below 12, 1 at 12, 21 above 12, 30
total
Our error has the form Error
= Number of sample lizards who have strictly more than 12 spots. Our
computed error is 21, computed from a random sample of 30
Fictitious Spotted Lizards. Using the row 30 21 0.02139, the computed
p-value is .02139, or approximately 2.1%.
Discussion
Our population is
the population of Fictitious Spotted Lizards.
Our Family of Samples
(FoS) consists of every
possible random sample of 30 Fictitious Spotted Lizards. From each member
sample of the FoS, we
compute the number of sample lizards who have strictly more than 12 spots.
Computing this error for each member sample of the FoS, we obtain a Family of Errors (FoE).
If the true population
median number of spots per lizard for the population of Fictitious Spotted Lizard
is 12 spots, then approximately 2.1% of the Family of Samples yield errors as
bad as or worse than our single error. The sample presents significant evidence
against the null hypothesis.
Table 2. Medians
n error base p-value 25 1 1.00000 25 2 1.00000 25 3 0.99999 25 4 0.99992 25 5 0.99954 25 6 0.99796 25 7 0.99268 25 8 0.97836 25 9 0.94612 25 10 0.88524 25 11 0.78782 25 12 0.65498 25 13 0.50000 25 14 0.34502 25 15 0.21218 25 16 0.11476 25 17 0.05388 25 18 0.02164 |
n error base p-value 25 19 0.00732 25 20 0.00204 25 21 0.00046 25 22 0.00008 25 23 0.00001 25 23 0.00001 25 24 0.00000 25 25
0.00000 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 30 11 0.95063 |
n error base p-value 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 30 21 0.02139 30 22 0.00806 30 23 0.00261 30 24 0.00072 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 |
Case Four: Hypothesis Test(Median), Fictitious Stress Index
The Fictitious Stress
Index (FSI) is a measure of a person's stress level. The FSI ranges from 0
to 70. A researcher acquires a random sample of undergraduates at Kennesaw
State University, and administers the FSI to these students near the end of
Fall Semester 2006. The FSI scores follow:
12, 14, 17, 19, 20; 22, 24, 25, 26, 27; 28, 29, 29, 30, 32;
32, 33, 34, 35, 35; 36, 38, 40, 40, 42; 44, 46, 52, 58, 70
Test the following: null
(H0): The median FSI for the population of undergraduates at KSU is
25 (h = 25 ) against the alternative (H1): h ¹ 25. 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.
Numbers
12, 14, 17, 19, 20; 22, 24, 25, 26, 27; 28, 29, 29, 30, 32;
32, 33, 34, 35, 35; 36, 38, 40, 40, 42; 44, 46, 52, 58, 70
12, 14, 17, 19, 20; 22, 24, 25, 26, 27; 28, 29, 29, 30, 32; 32, 33, 34, 35, 35; 36, 38, 40, 40, 42;
44, 46, 52, 58, 70
n=30, number of sampled KSU undergrads with FSI <
25 = 7, number of sampled KSU undergrads with FSI > 25 = 22
error = larger of number of sampled KSU undergrads with FSI <
25, number of sampled KSU undergrads with FSI > 25 = 22
from 30 22 0.00806, p = 2*.00806 = .01612 ~
1.6%
Discussion
Population:
Undergraduates at KSU (Fall 2006)
Population Median: Median
FSI Level for Undergraduates at KSU (Fall 2006)
Family of Samples: Each
member is a single random sample of 30 Undergraduates at KSU (Fall 2006).
For each member of the FoS, compute the number of sample Undergraduates at KSU
(Fall 2006) with FSI levels strictly less than 25 and the number of sample
Undergraduates at KSU (Fall 2006) with FSI levels strictly higher than 25. The
error is the larger of the two numbers. Doing so for every member of the FoS yields the Family of Errors.
If the true population
median FSI level for undergraduates at KSU (Fall 2006) is 25, then the
probability of getting a sample as bad or worse than
our sample is approximately 1.6%. This sample presents significant evidence
against the Null Hypothesis.
Table 2. Medians
n error base p-value 25 1 1.00000 25 2 1.00000 25 3 0.99999 25 4 0.99992 25 5 0.99954 25 6 0.99796 25 7 0.99268 25 8 0.97836 25 9 0.94612 25 10 0.88524 25 11 0.78782 25 12 0.65498 25 13 0.50000 25 14 0.34502 25 15 0.21218 25 16 0.11476 25 17 0.05388 25 18 0.02164 |
n error base p-value 25 19 0.00732 25 20 0.00204 25 21 0.00046 25 22 0.00008 25 23 0.00001 25 24 0.00000 25 25
0.00000 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 30 11 0.95063 |
n error base p-value 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 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 |
Case List and Expected Progress
Descriptive Statistics – Complete
Summary/Descriptive Intervals – Complete
Confidence Interval – Population Mean –
Complete
Confidence Interval – Population Proportion –
Nearly Complete
Remaining Case Work
Hypothesis Test – Population Median – Begin Work
Hypothesis Test – Population Category /
Goodness of Fit