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(a) How would the man whose case is described in the Appendix score on Eysenck's supertraits? (b) How would he score on the Big Five traits?(c) How would you s...

Question

(a) How would the man whose case is described in the Appendix score on Eysenck's supertraits? (b) How would he score on the Big Five traits?(c) How would you score on Eysenck's traits and the Big Five traits? (Remember that all traits are continuous.)

(a) How would the man whose case is described in the Appendix score on Eysenck's supertraits? (b) How would he score on the Big Five traits? (c) How would you score on Eysenck's traits and the Big Five traits? (Remember that all traits are continuous.)



Answers

As described in the third paragraph (lines 56–82), the gardener’s actions suggest that he is a man who:

A.is very alert.
B. knows all there is to know about plants.
C. loves nature.
D. resembles Adam.

Let's look at the statistics problems about percentile. But before I start I recommend students to pause the video, do the question themselves and come back to see if they've got a right or not. That is the true way of knowing if you fully understand this stuff. So let's start with what we're given. Were given a student's score on and examine the statistics class break And it is the 64th person type and recall that percentile is a value of like 100 right? It doesn't have to be because we're not given the number of students, it doesn't have to be 100 students. It could be 180 200. But if you draw a scale here, what else Let's say this is zero and this is the 100%ile then um student would be somewhere here, 64th%ile but it could be like 100 students, 180 students for example, It's just percentile is out of 100 because if you think about the work percent %,'s 100%. So and I feel like a box plot would help a lot in this situation. So let's look and act. So we have the options that his score could fall between the minimum and first court Tyler. Right? But if you look over here, so the first quartile is the uh huh. The fourth quarter is the 25th%ile. That means like there is 25% in this region. So it wouldn't make sense. And then there's another 25% between the first quartile and the median. So that adds up to 50%. Right? And then when you come from the media into the upper quartile is another 25%. So that adds up to 75%. And we can see from the image over here, it's written the Q three or the upper quartile, it's the 75%. So we can expect the student's score to be somewhere around here, right? It would be greater than the medium because the medium is the 50th%,ile, but it would be between the from the upper quartile Or the 3rd quartile and the media. So the final answer is because The 64 is between 50th%ile, of so it has to be between the third quarter out and the media. And I hope that was

This question. We're asked to explain how we would use Terry Vogel's data to find out if she drives faster in races or in practices so we can use the available data from her lap times to calculate the total times for each of her races and each other practices. Random samples of these racing practice times can be drawn and the sample averages and standard deviations calculated. And from these parameters, a test statistic can be calculated to see if there is a significant difference between the average race time and the average practice time.

Okay, So this question you want to figure out First off, what is a hierarchy for this relation? So the first primary key would be, of course, SSN, because everyone has different social security number in a night, so be unwelcome conditions would be the name and street address. I just the Commissar key. Well, this will be a commissar key if no two people with the same address has the same name. So I know you people in the saying street address address has the same names. That's pretty obvious. Why? And in practice, this is actually pretty likely. Okay, so you just good work, Kaminsky. Now our final one name street address address on DSI. So this one will be no two people in the same street address on dhe city. That's has what same names on this one will be even more likely to go because he put another condition of the city being the same. We're looking the same. So yeah,

Yeah, all right. In this question, we are looking at three different test scores with the mean and standard deviation of the, um, data sets that those test scores were taken from. And the overall question is which of the test scores is better relative to the rest of the test in that in that data set. So, um, all of these test scores are on different scales, so using a Z score to compare them gives us a way to make them on the same scale. So let's recall that our formula for the Z score is X minus X bar over s on. We're gonna use this formula three times to calculate the Z score for each of these tests. So the Z score for part a then would be 3.2 minus 4.6 over 1.5 subtracting and then dividing by 1.5 gives us a Z score of negative 0.93 Ah, that makes sense, because this is below the average and not quite one standard deviation below. We look at test be the Z score, then would be 6 30 minus 800 over 200 again we have a score that is below average. So this Z score turns out to be negative 0.85 and then our last test that we're going to calculate the Z score for 43 minus 50. Again, we're below average, divided by five. And here we get a Z score of negative 1.4. So all three of these tests were below average. But the question is, which one is the best? Even though they were all below average, which one is closest to average? So we would be looking for the Z score that is closest to zero or the largest of these negative Z scores. Not the most negative, but the largest. And this Z square right here of negative 0.85 This is the Z score that is the closest to zero. So, out of all three of these tests tests B is the one that that test was the best relative to their scores


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