STATSWeek10Notes.pdf Stats 1350
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This 5 page Class Notes was uploaded by Alyssa Leathers on Thursday March 26, 2015. The Class Notes belongs to Stats 1350 at Ohio State University taught by Ali Miller in Winter2015. Since its upload, it has received 105 views.
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Date Created: 03/26/15
STATS 1350 Week Ten 32615 128 PM March 24thMarch 26th Right Now sampling distribution we care about is sample proportion which we write as p Example 0 64 of Americans hand out candy on Halloween normal distribution sample size is 1000 mean is 64 standard deviation is 02 0 Probability of less than 59 Ap lt 59 596402 look at chart for 62 62 0 Probability of greater than 67 Ap gt 67 676202 look at chart and subtract from 100 668 Midterm Two Review Important Terms 0 The Empirical Rule 6895997 0 Ex normal distribution with a mean of 65 and standard deviation of 25 68 of women have heights between 625 6525 and 675 6525 95 of women have heights between 60 62525 and 70 67525 997 of women have heights between 575 6025 and 725 7025 What have heights lt 625 100682 16 What have heights gt 70 100952 25 What have heights lt 675 6816 84 What of the woman are lt 61 616525 16 548 from table What of the women are gt 61 100548 9452 Backwards observed mean standard deviation times 2 score 91 percentile how tall look at the table for zscore 13 65 25 x 13 0 Ex Correlation r SAT scores x and First year college grades y between 1 and 2 between 10 and 20 square root of 1 and 2 r must be between 316 and 447 o rquot2 percent of variation in y due to the linear relationship with x 0 Can t tell if r is inferenceprobably TrueFalse Examples 0 False if correlation between two lists of numbers is zero then there can be no relationship between them linear only could be some relationship just not linear 0 True correlation between height and pounds same correlation between centimeters and kilograms correlation is independent of units 0 False negatively correlated because the correlation coefficient of 141 r always has to be between 1 and 1 0 False negative correlation then both low values low in one high in the other Example 0 R 34 regression equation is blood pressure 101672333 pulse y101672333 Determine how well pulse rate helps predict blood pressure check rAZ 34 2 0 Pulse 90 beats per minute determine if regression equation would be appropriate to predict blood pressure 0 Check that we re not extrapolating check that 90 beats per minute is in range of observed heart rates Scatterplot Example dentist 0 Form linear Direction positive 0 Strength moderate Law of averages Averagesproportions are likely to be more stable when there are more trials while sums or counts are likely to be more variable Independent trials have no memory 0 Closer to the expected when large of trials 0 Farther from expected when smaller of trials TrueFalse Tossing fair coin probability that you get heads between 49 and 51 of the tosses decreases as the number of tosses increases F Flipping thumbtack two options updown 5050 F o Spinning roulette 47 chance is great with 50 than 700 when looking for majority T o Sees 12 people with heart attack next will be more likely not to have heart attack F Examples 0 Observed 50 or more 0 Expected 47 0 Standard deviation 02 0 Observed expected standard deviation 0 50 47 02 15 o zscore 9332 0 100 9332 667 Example 0 Males 75 younger than females when mating always 0 Correlation between ages of lizards 1 Ex The slope show that for each increase increases by one 32615 128 PM 32615 128 PM
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