<p>Does someone want to verify number 23 on <a href=“http://www.jonescollegeprep.org/ourpages/auto/2008/5/2/1209733393741/ap%20stats%202007%20complete%20exam.pdf[/url]”>http://www.jonescollegeprep.org/ourpages/auto/2008/5/2/1209733393741/ap%20stats%202007%20complete%20exam.pdf</a></p>
<p>Also, how do you determine sample size. I know it has something to do with error, but I forgot everything and can’t find it in Barrons.</p>
<p>I just looked in the back of the Barrons book and it said with mean Confidence Intervals and Hypothesis tests, you always use t, and not z. I always learned that you use t when n <30, and the sample is approximately normal.</p>
<p>I seem to be forgetting everything.</p>
<p>You use a T-test when you do not have the population standard deviation. </p>
<p>The conditions/assumptions for it are most favorable when n > 40, but it is also acceptable for n > 15 as long as it appears to be normally distributed (check histograms/dot plots).</p>
<p>Ok that’s right, Thank you.</p>
<p>Can someone lend me their 2002 Exam? I have every SAT qas. Quick! You have less than half an hour to PM ME!!! (the test is tomorrow so yea…only reasonable)</p>
<p>I get b for 23</p>
<p>Does someone have an answer key for the 2007 exam?</p>
<p>Oh whoops I did not read that it was the same sample.</p>
<p>One question from the sample questions (<a href=“Supporting Students from Day One to Exam Day – AP Central | College Board):%5B/url%5D”>Supporting Students from Day One to Exam Day – AP Central | College Board):</a></p>
<p>How do you do #14? How can you figure out b1 without r or n?</p>
<p>okay so youre given x(bar)=5 and y(bar)=10. so you just find the line which fits the coodinates (5,10)</p>
<p>so the answer is d</p>
<p>and the y intercept cant be negative so that rules out A</p>
<p>
</p>
<p>B is correct. The Central Limit Theorem states that normality is derived from an increase in sample size, and the smaller width of Dist. I in comparison to Dist. II indicates greater normality; more units closer to the actual population mean/parameter rather than spread out as they would be with a smaller sample size.</p>
<p>question! could someone explain this to me…i’m really confusing myself with when you use the standard error of root[p<em>(1-p)/n] VERSUS root[p cap</em>(1-p cap)/n]. will it specify population vs. statistic?? oh god, it’s bad i’m getting confused so late…D:</p>
<p>^ I can probably help if you tell me what “cap” is…</p>
<p>^he means to say “hat” lol</p>
<p>^^the p with the little cap on it…it’s used for statistics, lol.</p>
<p>^no, i didn’t. my teacher has always said ‘p-cap’. but, what have you.</p>
<p>Oh.</p>
<p>sqrt[p^(1-p^)/n] is the standard error for a 1-Prop Z-Interval</p>
<p>Your use of * is confusing too…it usually means critical value. Do you mean “o” signifying “not?”</p>
<p>If so, * (critical value) +/- sqrt[p(o)q(o)/n] is the SE for a 1 Samp Z-Test. </p>
<p>If it tells you to construct a confidence interval, do the first one. Otherwise use the second.</p>
<p>i have no idea what u mean by ‘o’ & ‘q’. i have literally never seen it done like that before D:</p>
<p>correct me if i’m wrong…but, i think that the difference between</p>
<p>root[p(1-p)/n] VERSUS root[p^(1-p^)/n]</p>
<p>is that the former is describing a population and the latter is describing a statistic. so, my question is, will it be clear on the test if i’m to use one vs. the other? because, aren’t they essentially being used in the same way?</p>
<p>my bad, q is the same thing as (1-p). It’s just an easier way to write it. o it essentially the probability of failure. so P^+P(o)=1.</p>
<p>Yeah, if you have ^'s in the second one, it’s from a population rather than an actual statistic like the first one looks like. I’m really, really bad at that chapter so I’ll shut up before I confuse you you/myself further.</p>
<p>haha, oh, got it with the q. i don’t think we ever went over probability of failure…fabulous.</p>
<p>& don’t the '^'s indicate a statistic…?</p>