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Mathematics 8 Online
OpenStudy (anonymous):

Write a problem for which the following would be used in finding the solution.a) Binomialpdf(20,0.25,12)b) Binomialcdf(20,0.25,12)

OpenStudy (anonymous):

@jim_thompson5910

jimthompson5910 (jim_thompson5910):

Binomialpdf notation is Binomialpdf(n,p,k) n = # of trials p = probability of success on 1 trial k = number of exact successes you want

jimthompson5910 (jim_thompson5910):

so Binomialpdf(20,0.25,12) means n = 20 p = 0.25 k = 12

jimthompson5910 (jim_thompson5910):

effectively allowing you to find the probability of getting exactly 12 successes (out of 20 trials total)

jimthompson5910 (jim_thompson5910):

so what ideas come to mind?

OpenStudy (anonymous):

uh maybe we can say for like an AP test? 20 tests, 25% success rate and we want 12 people to pass to make the school look good?

OpenStudy (anonymous):

@jim_thompson5910

jimthompson5910 (jim_thompson5910):

that works

OpenStudy (anonymous):

okay what about for b?

jimthompson5910 (jim_thompson5910):

the 'cdf' is very similar but it's a cumulative probability cdf = cumulative density function

jimthompson5910 (jim_thompson5910):

basically it's a bunch of pdfs added up

jimthompson5910 (jim_thompson5910):

example Binomialcdf(20,0.25,2) = Binomialpdf(20,0.25,0)+Binomialpdf(20,0.25,1)+Binomialpdf(20,0.25,2)

jimthompson5910 (jim_thompson5910):

the Binomialcdf allows you to answer questions like "what is the probability of getting at least X or at most X" stuff like that So again, this is where you're adding up a bunch of individual pdfs

OpenStudy (anonymous):

so could we do the scores for AP tests over the years?

jimthompson5910 (jim_thompson5910):

or you can ask something like "what is the probability of at most 12 succeeding" that's the same as saying "probability of 0 succeeding + probability of 1 succeeding + ... + probability of 12 succeeding"

OpenStudy (anonymous):

oh okay!

OpenStudy (anonymous):

can you help with one more?

jimthompson5910 (jim_thompson5910):

sure

OpenStudy (anonymous):

A quarterback for the Seattle Seahawks completes 54% of his passes. Let the random variable X be the number of passes completed in 20 attempts. Conduct a simulation of the 20 attempts using the following random digits. Be sure to state how you assign your digits. 98726 10983 56239 42042 76520 68276 58239 48729 84912 87491 a) What proportion of passes were completed? b) How does this compare with what "should have happened" theoretically?

jimthompson5910 (jim_thompson5910):

"A quarterback for the Seattle Seahawks completes 54% of his passes" so p = 0.54

jimthompson5910 (jim_thompson5910):

54% = 54/100 so if he threw 100 passes, then we expect him to make 54 passes (average)

OpenStudy (anonymous):

okay

jimthompson5910 (jim_thompson5910):

how do we use "98726 10983 56239 42042 76520 68276 58239 48729 84912 87491" ? well we can make this rule break up the sequence into number pairs. So the first number is 98, the second is 72, third is 61, etc etc Rule: if you get a number from 1 to 54 (inclusive), he completes the pass. If you get a number from 55 to 100 (inclusive), then he fails to complete the pass

OpenStudy (anonymous):

okay

jimthompson5910 (jim_thompson5910):

So based on that rule, the first three numbers: 98, 72, 61 means he fails his first three passes but the next number 09 tells us that on the 4th pass, he actually completes it (his first completion) make sense?

OpenStudy (anonymous):

okay give me a sec to get A

OpenStudy (anonymous):

i got 18/25 @jim_thompson5910

jimthompson5910 (jim_thompson5910):

how did you get 25? he only did 20 attempts (ie 20 trials)

OpenStudy (anonymous):

OpenStudy (anonymous):

actually it would be 7/25

jimthompson5910 (jim_thompson5910):

98726 10983 56239 42042 76520 68276 58239 48729 84912 87491 98 72 61 09 83 56 23 94 20 42 76 52 06 82 76 58 23 94 87 29 84 91 28 74 91 -------------------------------------------------------------------------- Rule: if you get a number from 1 to 54 (inclusive), he completes the pass. If you get a number from 55 to 100 (inclusive), then he fails to complete the pass 98 - fail 72 - fail 61 - fail 09 - successful pass 83 - fail 56 - fail 23 - successful pass 94 - fail 20 - successful pass 42 - successful pass 76 - fail 52 - successful pass 06 - successful pass 82 - fail 76 - fail 58 - fail 23 - successful pass 94 - fail 87 - fail 29 - successful pass There are 8 successful passes out of 20 total, so the probability for part a) is 8/20 = 2/5

OpenStudy (anonymous):

oh i iused all the numbers i dint stop after 20 my bad

OpenStudy (anonymous):

@jim_thompson5910

jimthompson5910 (jim_thompson5910):

what's your question

OpenStudy (anonymous):

is that it for A?

jimthompson5910 (jim_thompson5910):

yes 2/5 = 0.4

OpenStudy (anonymous):

and for B it would be this is less then what "should've happened" theorectially

jimthompson5910 (jim_thompson5910):

yes empirically we got 40% theoretically it should be 54%

jimthompson5910 (jim_thompson5910):

the more trials you do, the closer you should get to the theoretical probability (assuming the theoretical probability is accurate)

OpenStudy (anonymous):

okay than you again! can you help with one more question or do you not have time?

jimthompson5910 (jim_thompson5910):

post it and show me what you got so I can check

OpenStudy (anonymous):

What are the conditions necessary for using the formula for standard deviation (sigma = sqrt(p(1-p)/n) when examining a population from a sampling distribution?

jimthompson5910 (jim_thompson5910):

check out this page http://stattrek.com/estimation/confidence-interval-proportion.aspx

OpenStudy (anonymous):

are these the two conditions? the sampling method is simple random sampling. The sample is sufficiently large. As a rule of thumb, a sample is considered "sufficiently large" if it includes at least 10 successes and 10 failures.

jimthompson5910 (jim_thompson5910):

look just above the "alert" box

OpenStudy (anonymous):

When the population size at least 10 times larger than the sample size?

jimthompson5910 (jim_thompson5910):

yes

jimthompson5910 (jim_thompson5910):

N > 10n N = population size n = sample size

OpenStudy (anonymous):

okay thank you so much! you're the best!

jimthompson5910 (jim_thompson5910):

If \(\Large N \ge 10n\) is false, then \(\Large \sqrt{\frac{N-n}{N-1}}\) needs to be tacked on (as shown on the page).

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