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Suppose we'd likeEnoythe mean PSI for the Colts' footballs changed significantly from pregame halftime The pregame PSI forColts fcotbals 12 13Get JMP t0 p...

Question

Suppose we'd likeEnoythe mean PSI for the Colts' footballs changed significantly from pregame halftime The pregame PSI forColts fcotbals 12 13Get JMP t0 perform tesl dqainst:Ho: Hcotts PSI HalftimngTo do this in JMP start fromn lhe Analyze Distribution output yoll used Wntweastionethen click the red Acro ou 'PSI_Halftime'statistic 66 1584 -ualue 0 01b. JMP provides all the numbers Vised and repont them below-comaut che test starlsriepanted above CalculateVale Forche numerator

Suppose we'd like Enoy the mean PSI for the Colts' footballs changed significantly from pregame halftime The pregame PSI for Colts fcotbals 12 13 Get JMP t0 perform tesl dqainst: Ho: Hcotts PSI Halftimng To do this in JMP start fromn lhe Analyze Distribution output yoll used Wntwe astione then click the red Acro ou 'PSI_Halftime' statistic 66 1584 -ualue 0 01 b. JMP provides all the numbers Vised and repont them below- comaut che test starlsri epanted above Calculate Vale Forche numeratorand denominato Mumerator rest statistic: 0 996, Denominator oftest statistic: 1269



Answers

Super Bowl XXXIX Champion New England Patriots The following table gives roster information for the offense of the Super Bowl XXXIX Champion New England Patriots. (a) Find the mean, median, and mode age. (b) Find the mean, median, and mode weight. (c) Find the mean, median, and mode years of experience. (Note: Rookie $=0$ years.) (d) Find the mode college attended. (e) Obtain a simple random sample of six members of New England's offense. Compute sample mean age, weight, and years of experience. How do the sample means compare to the population means? (f) Compute the mean, median, and mode weights of the five offensive guards $(\mathrm{OG}) .$ Compute the mean, median, and mode weights of the five running backs (RB). Does there appear to be a difference in the weights? What might account for any differences? (g) Does it make sense to compute the mean player number? Why?

Hi there. This question. Give us the better off ages off different players off a Super Bowl in two, silent and 16. And we need to use the data given to draw dot plot on Let's see how to do that. Well, since you already have the data, I don't read them down here and that's a week. According to the data, we can say that the biggest value is starting ni, and the smallest value is also above touching. So let's set the horizontal lines starting from 20 to 40. That's eight your cover all of the details given in this problem. So that's first review the first line on then move on your second land and so are starting from left to right eso for the first data. It is 24. So let's draw a point here for next one is 23. The point here the next 1 20 by next one is also 25. So that's I thought, here and for the next one it is 26 for next one a 30. Okay, that's going to our next line of data. Uh, the 1st 1 There's 30. Okay for the second row, Second Colon. It is service free. And the next one is 23 draught here on top of that. And the next one is 32. Next one. This 21 and the last one of a second row is 26. That's at one point here for a servo. We start with 2 24 So let's draw two points here and x one is 27. Okay, first off myself and next one is 26. Okay, I was certain, sir. 26 and next. One days, 30 hour. Serves 30. And the last one of Acero is 24 over. This will want to this to the fourth row. The 1st 1 is 26. The 2nd 1 is 28. The 3rd 1 is 24. Okay. Or fits 24. Andi, The next one is 23. The next one is 39 while the biggest one is here. And the next one is 26. Okay, lets will want to fist, uh 50 role. It starts with 34. Okay, so therefore our first of the four and five and 24 on 26 on 24 on for the three. Okay, let's move on to our six row start. It starts with 26 utterly forget. And then 29 off first on 25. 26. 30. Plenty to Okay, we have street lines with three rows for meaning for next one starters 23 then 28. Then 25 in 24 again, a lot of 20 force and 34 and 27. Okay, for our next row with start with 29 than 28 then 23 then 25 and then 28 to 28. So right, two points here. Okay. And for the last row is five data. We start with 29. I move on to 33 2 25 bridges here again and 27 in the last data is 25 25 as well. Okay, so these concludes our thought plots. Dog barks. And it shows, actually that in 2000 and 16 the Super Bowl on the majority off the football clears, they have ages range from 23 to 30 and among them, most of the players Oh, are the biggest percentage off. The age is 24 and next is 25. And there are there are also some extreme debt. Us, for example, is a The oldest player is 39 years old. Terrorist. The youngest player is 21 years old, and that's and that concludes our dot plot. Thank you.

You're given some information in regards to a normal distribution, the mean and the standard deviation in a normal distribution are mean, is in the middle and then we have values that are one standard deviation two standard deviations three standard deviations to the right and 12 and three standard deviations to the left. So in our particular problem, if we want to know what percent would gain more than two standard deviations above the mean, so we want to know what percent does this represent? Well, recall that between two standard deviations of the mean, we have 95% of our data. So quick little calculation 100 minus 95. So that means there's 5% on either side. And since I only want the top half, I'm going to divide that by two, so that tells me 2.5% I can expect to point point 5%. Now, in our particular case, what does that mean? While taking my information and replacing you with the actual mean and then adding the standard deviation. This first one will be 759.55 and the second one is 11 to 1.95 So in the context of our particular problem, we are expecting 2.5% of the receivers to gain 1000, 120. Let's round it 22 yards or more, or we expected them, or 2% of the receivers gained 1 1000, 122 yards or more in the 2010 season.

In this video, we're going to be discussed. We're gonna be discussing road numbers and their properties in particular. We're gonna be playing the real numbers into a formula for solving the formula. So, as you see on the screen, I have the formula used by the NFL to determine the passer rating of Q. B. S. So Down here on the bottom left at Peyton, Manning Stat from 2014 When 2014, sorry, he played for Denver. His attempted passes. You have 597 total, 395 completed passes, 39 touchdown passes, 4,727 yards gained and 15 interceptions. All right. So we're gonna do is play these values directly into our formula and then solve the formula. So we're gonna write down exactly what we see in our formula and plug in our values. So we have 250 Times are completed passes, 395 over our attempted passes plus 1000 over our touchdowns, Divided by 10 passes plus 12.5 Over his total yards. 4727. Writing by his attempted passes. 597 plus 6.25 minus 12 50 divided by his interceptions. 15 divided by his attempted passes. 5 97. All right, So now, Oh sorry, all divided about three. So now you're gonna plug this directly into the calculator, using the parentheses as multiplication. Because if not, you're gonna mess up your order of operations. You have to do what's in parentheses here, Which is going to be all of these fractions over over the attempted passes. And then you're going to multiply the constants. So you're gonna want to type this directly into the calculator, how you see it, you're gonna have these are calculated because it's a lot of complex calculations and I just don't believe you can do it by hand. I mean it's possible but this is gonna take you a long time. So type this directly into the calculator. What I do is I put in this numerator first and then I divide the answer by three. But to type it all in at once you can just put parentheses around his numerator. Not only allow you to type it all this whole problem and the denominator and at once and if you do that going to get an answer We're paying man, he's passing rating in 2014 Was 101.5.

The following is a solution for number 16. And we're looking to see if the passing offense more potent now from professional football. So we looked at the passing yards per game, that's what this stands for. Previously, I think it was like five years ago we looked at 20 games and the average was 203 passing yards per game, with the standard deviation of 38. Then we looked at recently within the past year or two Passing yards per game for 11 games was 232 With a standard deviation of 33. So we have to use and we're going to find a 95% confidence interval. We need to use a T interval because these sample sizes are so small. 20 and 11, they're both less than 30 30 is kind of that magic number. Then we would be able to use the Z interval. But since there's less than 30 week we have to use the tea interval. So I'm gonna use a calculator here because it makes things a lot easier. So if you go to Staten them tests, it's going to be that zero option all the way down where it says to samp T. And so option zero and then make sure stats is highlighted. And you can see here we have the data X one, bar, S one N one X two, bar S to an end to the sea levels 20.95 for 95%. And then we're still pulled because we're assuming that the standard deviations are the same. So when I recalculate, its between negative 56 91 A negative 1.09. So this actually looks like there is a difference since they're both negative but we'll see. So negative 56.91 And -1.09. We're 95% confident that the main difference between previously and recently for passing yards per game is between these two numbers. Okay, the second part of this new one minus mu two is zero. That means that there is no difference between five years ago and today in passing yards per game and then this one saying that there are actually more passing yards per game now than there were previously. So mu one minus Me too is less than zero because we're doing you one as previously And we're testing at the 5% level of significance. So I need a t. value a statistic and I also need a P value and we're going to compare that to that point oh five in order to make our decision. So fortunately for us, I already have this set up and ready to go and you do too. So if you go to stat and then tests, it's the two sample T test instead of tea interval, it's a test of two sample T test and stats and notice you know everything is already in there. So I don't have to do anything and I don't even have to change the alternative because it's already done. So less than you two. The pool is still yes. And then I calculate And I get this test statistic here of -2.125 and AP value of about .02. Let's go and write those down negative 2125. And then a P value of 0.2 which is less than alpha. So anytime the P values less than alpha, we reject that null hypothesis, we're going to reject the null hypothesis. And for lack of a better word, except the alternative hypothesis saying that there is a difference. In fact, um the passing office offense is more potent since those passing yards per game recently is significantly larger than previously.


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