Q.
A. http://en.wikipedia.org/wiki/Atherosclerosis
Cigarette-endothelial dysfunction and a relatively hypercoagulable state
hypertention-morphologic alterations of the arterial intima and functional alterations of the endothelium
hyperlipidemia- Endothelial injury
Bottom line- All risk factors cause endothelial dysfunction which is the earliest manifestation of atherosclerosis
Cigarette-endothelial dysfunction and a relatively hypercoagulable state
hypertention-morphologic alterations of the arterial intima and functional alterations of the endothelium
hyperlipidemia- Endothelial injury
Bottom line- All risk factors cause endothelial dysfunction which is the earliest manifestation of atherosclerosis
a study reported that the prevalence of hyperlipidemia is 30% in children 2 to 6 years of age. if 12 children?
Q. are analyzed: a) what is probability that at least 3 are hyperlipidemia? b) what is the probability that exactly 3 are hyperlipidemic? and c) how many would be expected to meet the criteria for hyperlipidemia?
A. a. ANSWER: PROBABILITY = 0.75 at least 3 are hyperlipidemia
Why???
BINOMIAL DISTRIBUTION, POPULATION PROPORTION
n = NUMBER OF TRIALS [ 12] (sample size)
k = NUMBER OF SUCCESSES [2] (from 0 up to and including k NUMBER OF SUCCESSES)
p = POPULATION PROPORTION [30%]
significant digits2
COMPUTATION OF BINOMIAL PROPORTION:
P(k => 3) = 1 - P(k ⤠2) = 1 - n!/[k!*(n - k)!] * p^k * (1 - p)^(n - k)
0.75 = 12!/[2!*(12 - 2)!] * 0.3^2 * (1 - 0.3)^(12 - 2)
ALTERNATIVE COMPUTATION USING EXCEL:
"Look-up" value of PROBABILITY = 0.75 = 1 - BINOMDIST ( 2 , 12 , 30/100 , TRUE )
"Using Excel function: BINOMDIST(number_s, trials, probability_s, cumulative)
Number_s is the number of successes in trials. [ 12 ]
Trials is the number of independent trials. [ 2 ]
Probability_s is the probability of success on each trial. [ 30]"
Cumulative is a logical value that determines the form of the function. If cumulative is TRUE, then BINOMDIST returns the cumulative distribution function, which is the probability that there are at most number_s successes; if FALSE, it returns the probability mass function, which is the probability that there are number_s successes.
b. ANSWER: PROBABILITY = 0.24 exactly 3 are hyperlipidemic
Why???
BINOMIAL DISTRIBUTION, POPULATION PROPORTION
n = NUMBER OF TRIALS [ 12] (sample size)
k = NUMBER OF SUCCESSES [3] (Exactly 3 NUMBER OF SUCCESSES)
p = POPULATION PROPORTION [30%]
significant digits2
COMPUTATION OF BINOMIAL PROPORTION:
P(k = 3) = n!/[k!*(n - k)!] * p^k * (1 - p)^(n - k)
0.24 = 12!/[3!*(12 - 3)!] * 0.3^3 * (1 - 0.3)^(12 - 3)
ALTERNATIVE COMPUTATION USING EXCEL:
"Look-up" value of PROBABILITY = 0.24 =BINOMDIST ( 3 , 12 , 30/100 , FALSE )
"Using Excel function: BINOMDIST(number_s, trials, probability_s, cumulative)
Number_s is the number of successes in trials. [ 12 ]
Trials is the number of independent trials. [ 3 ]
Probability_s is the probability of success on each trial. [ 30]"
Cumulative is a logical value that determines the form of the function. If cumulative is TRUE, then BINOMDIST returns the cumulative distribution function, which is the probability that there are at most number_s successes; if FALSE, it returns the probability mass function, which is the probability that there are number_s successes.
c. ANSWER: (approx) 4 children expected to be hyperlipidemic
Why???
SAMPLE SIZE * POPULATION PROPORTION = EXPECTED [12 * 0.3 = (approx) 4]
Why???
BINOMIAL DISTRIBUTION, POPULATION PROPORTION
n = NUMBER OF TRIALS [ 12] (sample size)
k = NUMBER OF SUCCESSES [2] (from 0 up to and including k NUMBER OF SUCCESSES)
p = POPULATION PROPORTION [30%]
significant digits2
COMPUTATION OF BINOMIAL PROPORTION:
P(k => 3) = 1 - P(k ⤠2) = 1 - n!/[k!*(n - k)!] * p^k * (1 - p)^(n - k)
0.75 = 12!/[2!*(12 - 2)!] * 0.3^2 * (1 - 0.3)^(12 - 2)
ALTERNATIVE COMPUTATION USING EXCEL:
"Look-up" value of PROBABILITY = 0.75 = 1 - BINOMDIST ( 2 , 12 , 30/100 , TRUE )
"Using Excel function: BINOMDIST(number_s, trials, probability_s, cumulative)
Number_s is the number of successes in trials. [ 12 ]
Trials is the number of independent trials. [ 2 ]
Probability_s is the probability of success on each trial. [ 30]"
Cumulative is a logical value that determines the form of the function. If cumulative is TRUE, then BINOMDIST returns the cumulative distribution function, which is the probability that there are at most number_s successes; if FALSE, it returns the probability mass function, which is the probability that there are number_s successes.
b. ANSWER: PROBABILITY = 0.24 exactly 3 are hyperlipidemic
Why???
BINOMIAL DISTRIBUTION, POPULATION PROPORTION
n = NUMBER OF TRIALS [ 12] (sample size)
k = NUMBER OF SUCCESSES [3] (Exactly 3 NUMBER OF SUCCESSES)
p = POPULATION PROPORTION [30%]
significant digits2
COMPUTATION OF BINOMIAL PROPORTION:
P(k = 3) = n!/[k!*(n - k)!] * p^k * (1 - p)^(n - k)
0.24 = 12!/[3!*(12 - 3)!] * 0.3^3 * (1 - 0.3)^(12 - 3)
ALTERNATIVE COMPUTATION USING EXCEL:
"Look-up" value of PROBABILITY = 0.24 =BINOMDIST ( 3 , 12 , 30/100 , FALSE )
"Using Excel function: BINOMDIST(number_s, trials, probability_s, cumulative)
Number_s is the number of successes in trials. [ 12 ]
Trials is the number of independent trials. [ 3 ]
Probability_s is the probability of success on each trial. [ 30]"
Cumulative is a logical value that determines the form of the function. If cumulative is TRUE, then BINOMDIST returns the cumulative distribution function, which is the probability that there are at most number_s successes; if FALSE, it returns the probability mass function, which is the probability that there are number_s successes.
c. ANSWER: (approx) 4 children expected to be hyperlipidemic
Why???
SAMPLE SIZE * POPULATION PROPORTION = EXPECTED [12 * 0.3 = (approx) 4]
Hyperlipidemia is 30% in children 2-6 years of age. If 12 children are analyzed, what is the probabilty that?
Q. At least 3 are hyperlipidemic?
A. Well, four kids out of twelve should have it. But your question isn't very specific. If you have three kids, and you wanna know what their odds of getting it are, it depends.
Family history is an important factor, but if you're going by statistics alone, one of your kids probably has it.
Family history is an important factor, but if you're going by statistics alone, one of your kids probably has it.
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