5

I will thumbs up if good and correct! Please help with this andexplain how you reached your conclusion it would be greatlyappreciated as I am a little lost!There ar...

Question

I will thumbs up if good and correct! Please help with this andexplain how you reached your conclusion it would be greatlyappreciated as I am a little lost!There are 4 different parts.This check sheet below provides the number of errorsreported for a seven day period for the events completed during theturnaround process.Use Excel and the error data to develop a histogram and Paretochart. Review the charts and draw conclusions from the data.Explain what the data are telling you. What actions woul

I will thumbs up if good and correct! Please help with this and explain how you reached your conclusion it would be greatly appreciated as I am a little lost! There are 4 different parts. This check sheet below provides the number of errors reported for a seven day period for the events completed during the turnaround process. Use Excel and the error data to develop a histogram and Pareto chart. Review the charts and draw conclusions from the data. Explain what the data are telling you. What actions would you suggest to reduce the number of errors? 3- Using the Galley Servicing Delay data and the Excel OM plugin, identify a statistical process control chart (SPC) (use the c-chart and make sure to click on the graph box). While this method is best used in manufacturing, you can apply the principles to our problem. Since the management wants to tightly control the error rate, use a standard deviation (z value) of 2. Explain the chart and indicate whether it provided you with any additional information on ways to reduce errors and improve quality. Also, in this case, is an LCL needed? If not, why not? 4- Now that you have run the data, let's look a little deeper and try to determine possible causes of the problems. Galley servicing delays showed the highest number of problems on our original check sheet, so think about possible issues with galley servicing and produce a cause-and-effect diagram (also known as a fishbone or Ishikawa diagram). Use as least 4 categories and think of several causes for each of the categories.



Answers

Please do the following. (a) Draw a scatter diagram displaying the data. (b) Verify the given sums $\Sigma x, \Sigma y, \Sigma x^{2}, \Sigma y^{2},$ and $\Sigma x y$ and the value of the sample correlation coefficient $r$ (c) Find $\bar{x}, \bar{y}, a,$ and $b .$ Then find the equation of the least-squares line $\hat{y}=a+b x$ (d) Graph the least-squares line on your scatter diagram. Be sure to use the point $(\bar{x}, \bar{y})$ as one of the points on the line. (e) Interpretation Find the value of the coefficient of determination $r^{2} .$ What percentage of the variation in $y$ can be explained by the corresponding variation in $x$ and the least-squares line? What percentage is unexplained? Answers may vary slightly due to rounding. The following data are based on information from the Harvard Business Review (Vol. 72, No. 1). Let $x$ be the number of different research programs, and let $y$ be the mean number of patents per program. As in any business, a company can spread itself too thin. For example, too many research programs might lead to a decline in overall research productivity. The following data are for a collection of pharmaceutical companies and their research programs:Complete parts (a) through (e), given $\Sigma x=90, \Sigma y=8.1, \Sigma x^{2}=1420$ $\Sigma y^{2}=11.83, \Sigma x y=113.8,$ and $r \approx-0.973$ (f) Suppose a pharmaceutical company has 15 different research programs. What does the least-squares equation forecast for $y=$ mean number of patents per program?

We are given a sample of data points X. Y. Listen to the top of this white board and we want to use this data to answer the questions A through F. As follows. And part A. On the left. We want to draw a scatter plot for these data points. I've already included a scatter plot and the data points X. Y. Are demarcated with the black crosses or exes Next in part B of the right. We want to compute the relevant some of this data as well as the Pearson correlation coefficient. R. I've already included the value of the sums as they are simply found by following these equations exactly. So some acts of some of the X values, some wise some of the Y values and so on. Next you complete. You are using the following formula which takes as input the sum to just computed as well as the sample size. And Plugged in gives r equals negative .973. Next for part C. Let's find the line of best fit. First. We have to find the X and Y means X by Y. Bar found by dividing by N. The sums for X and Y. Next we find the slope and intercept for the best fit line. Be. The slope is given by the formula here it takes its input N. And the sums computed above. So it's very similar to the correlation coefficient. R Plugging in to get equals negative .11 And plugging in b. x. bar and wine bar to a give us our intercept three producing line of best fit. Why Pat equals three minus 30.11 X. Next you were trying to scatter plot to plot. Ry hat we make sure to mark our ex me and what I mean, producing this. Next we go to the bottom right. For part E. We want to calculate the correlation coefficient or rather a court coefficient of determination. R squared, which is the square of the correlation coefficient and interpret its meaning. R Squared is simply .946. We interpret this to mean that 94.6 of variation in the data can be explained by the corresponding variation between X and the the square line, Roughly five of the data cannot be explained by this, or rather five of variation cannot be explained by this. Finally, let's protect y for x equals 15 Plugging into white hat. We obtain y equals 1.35.

Were given that delightful has a 0.2 chance of failing, and each box has ate light bulbs in it. So the first thing we're gonna do is find the probability distribution. Now, on this page, on the last page of the book, you were given a lot of notes about how to do these problems on a computer. That's because they want you to do these problems on either a computer or graphing calculator. I'm gonna be doing this and excel well, you conduce this in over programs. The steps might be a little bit different, though, So if we do this in Excel, first thing I'm gonna do is make a list of all the possible outcomes. There's eight trials, so we need the number 0 to 8. Just this select all home and dragged down. They don't want to going to be one under formulas and statistical, and I use the binomial distribution. Tual. So our trials that's eight. Cause there's ate light bulbs in the box or probability was 80.2 We don't have to convert it like we normally deal because we weren't given it as a percentage. It's already in the form we wanted to be in Cumulative is false for not working on this right now. So for this the number I'm gonna play it all my numbers from 0 to 8. So starting with B a one box colon, the A nine rocks, and we get this. So now we need to draw a hist. A gram of acsa. So for a history Graham of acts, we put everything in order, and our X values are going to be the X access. So that's just gonna be the numbers from 0 to 8. So to free 456 seven and eight. No wonder why access is gonna be all of the probabilities. However, what? Let's go back to take a look here. You notice the 1st 1 is the biggest. Then the 2nd 1 smaller, smaller, smaller and keeps getting smaller and smaller. This e means times 10 to the blank power. So, for example, on the probability of seven bull to being bad is one times 10 to the negative, a lower power. So the reason why it keeps getting smaller is because of this probability is so low that getting zero, where wine that's the most realistic outcome so we can make our hissed a gram like a descending staircase. Kind of. So zero is gonna be the highest, then wine and to than free four and eventually these ones, they're going to get so small that it's just a tiny little dash. And then we'll fill in some values with one for zero. That was a point. Eat by one one at one that was 10.139 Then we have points cereal 099 I don't put one more. The one at free. We have 10.0 for. So this is Ah, a decent history, Graham. So what is the probability of getting a box with no failing light bulbs? So let's go back to our distribution that we just made it. So no feeling like bulbs that zero. So that's right here. The 0.851 This problem is just reading the table. So 0.851 That's because the no here means zero. What is the probability of getting a box with no more than one? So what we'll do for this one is will take all the possible options. No more than one means even zero or one. So we'll take both of these two and add them together. And when you do that, you should get a point 990 We just add the 1st 2 together, find the mean and standard deviation of X. So because we have a binomial, random variable over the light bulb fails or it works. So it's binomial. These are the two equations we used to get mean and standard deviation. Your notes might say a que here instead of one minus p. That's the same thing. So N is our number of trials, that is eight and P is our probability. That's 80.2 so are mean is equal. Chill eight times 80.0 chill, which is equal 2.16 Our standard deviation is the square root of eight times 80.0 chill times one minus 10.2 or 0.98 If you're using keel, it's the same feign, and this gives us point free 96 So what proportion of the distribution is between you have these two symbols. So first, let's define them. This one is called new, and it's the mean. This one is called Sigma, and it's the standard deviation. So this is asking how much of the data is between mean minus standard deviation and mean plus standard deviation. Well, mean minus dinner deviation. That gives us a negative. Zero is our lowest option. So we have starting from zero chill. But what's 0.16 plus 0.396 Find six. Well, that's Ah, 0.5 by six. So we go here if you notice we have all whole numbers here. So 0.556 That doesn't get us toe one because this is binomial. We can't have half of a try algo ever way. We can't have a light bulb half working, so we have to round everything down and we're only gonna be in the zero box, for example. Let's say we got a mu plus Sigma was equal to free. Then we would include zero to free, but because it hasn't hit one, we're going to stay in the zero box. So we're gonna get 0.851 again. Now, what about if we multiply the standard deviation by two first? So we're still gonna have zero here? It doesn't matter what the exact value is its negative. So we're still gonna have zero, and we're gonna get 00.952 here again. It didn't hit one yet, so we're still within that 85% of data or 0.851 So how does this information relate to the empirical rule and Chevy sex? Fear out. These two rules give less guidelines for how much of the data is going to be within one standard deviation of the mean, like in part E two standard deviations of the mean in free standard deviations of the mean. And sure enough, most of the data should be off in one standard deviation last living too and less within free. However, in our problem, because the probability of a light bulb not working is so low. Almost all of the data is within one standard deviation and so and relates to this because this is what we would expect from such a low probability. Okay, if we buy 100 box isn't we're going to simulate how many of them were go bad. There are many different ways of doing random numbers simulations. The way I'm going to do it is just one way of doing it. So what? I'm gonna do is generate ah 100 random numbers ranging from 1 to 100. I'll do this by going to insert function under category all, and I'm going to scroll down to the ours and almost the aerial ran between. I'm gonna generate numbers from 1 to 100. Now, what my role is going to be is any time we see the number one or two, that means it is going to be a broken bull. That's because we have a 20.2 chance of a light bulb failing. So that's really 2%. So there's 100 boxes, 2%. So wanting to that's 2% of 100 because that's two numbers. Now, we're going to do this 100 times, so I'm going to drag this all the way down to Ah 100. I'm gonna quickly look through and see if we got any ones or two. I see it too. I see one. Okay, so we got to Obviously, your answer could realistically be 0123 or four. Now, repeat, part h in common on it. So we're gonna do this a few times now. We're gonna comment on what we see happening, Nina. So it's high, like this whole thing. This is why I'm doing it this way. So is gonna be very easy to recreate, because I just drag this to the right. I'll do free more. Okay, so starting at the 2nd 1 I see a to there's a one. A number one so free. So we got to for the 1st 1 Been free. Now let's look at this line. No. Is that looks like zero must quickly make sure Yep, zero. And then the last one. There's a one. There's an over one. So, too, to so free we got free. This time you notice we're kind of getting around the same amount each time to or free makes sense. There's a 2% chance that a bold goes bad, so the higher this number gets, we should be getting closer to 2% each time. So 12 or free

And this video will be looking at one criteria or one way that you can see if you have an outlier in your information. So what I'm gonna do is I'm going to start by entering the information into my calculator to make a box plot. So I select stat number one and I'm going to enter the information in. Now I will enter a couple of the items and then I'll stop and I'll enter it in. So you don't have to sit here and watch a magic hand enter values into the calculator. So now I'm entering the last value. I like to use the calculator when my information isn't already in order for me. So now I need to look at the the box plot so I will choose second Y equals stat plot. I see my plot is already on but if yours is not select one, press enter when your cursor is on the word on cursor down and over to select the second box plot. And it should already be default to list one. Now I want to look at my graft so I select zoom, zoom nine zoom stat and there's my box plot and then I can select the zoom oops wrong button. Sorry then I can select the trace button and the trace button automatically starts on the median And I can see my median is 65.5. Q 1 61.5. There's my minimum it for Q three at 71.5 And 80 is my high value. So I went ahead and copied the plot and put it on my screen here so that I could write on it. So this value was for Q one was 61.5. The median value 65.5. Q371.5 and the maximum value is 80. So it does appear that I have an outlier. My whisker here appears to be very, very long. But believe it or not, there's actually a formula for that. The formula is to take Q one -1.5 times the inter quartile range and Q two minus or plus 1.5 times the inter quartile range. And anything outside of these values is most likely an outlier. Or another way to look at it is if you're Whisker is 1.5 times larger than your box, you most likely have an outlier. So let's do this. The official way will take Q1 which was 61.5 and then the inter quartile range Would be 71.5 61.5. So I open up my calculator again and 61.5 minus 1.5 times the inter quartile range And I'll see that I have a value of 46 point five. So anything below 46.5 is most likely an outlier. And then let's just check the rest of the range so I'm gonna do the other value. I'll do cue too. So that was with Q one. So I'm gonna do Q two 71.5 plus. I said cute too, didn't I? Q 3? I apologize accused to. Is the median Q three is 71.5 Plus 1.5 times the inter quartile range. So I'm gonna do a little trick with my calculators. Don't have to re type all that second enter. There's the information written out for me In place of 61.5, I will type 71.5 plus And that tells me that the high end of my range is 86.5, So anything below 46.5 or above 86.5 is most likely an outlier and obviously four is way below. So yes, it does appear that there is an outlier. Now, what is the reason for this? Well, the outlier is below. Could be any number of reasons, but these this is information from a statistics class that students recorded. So chances are this might have been and an error and entry. So perhaps the student meant to type in 42 Or 49 instead of four. So it's a very good chance that that is a data entry error. Or perhaps somebody is actually that tall Because these are all heights of students in a class. So I highly doubt somebody is 4" tall.

So in this problem, we're taking a look at outliers, which are important to identify, to see if that we see if we've made a error in our data collection data entry or if we just have an unusual data value and one way to detect outliers, just use a box and whisker plot. So we're given students heights that are in the statistics plus and for party. We want to go ahead and make a box and whisker plot of the data so we can see that the low value is for the high value is 80. Yeah, and we want to find our portals. Sochi one is the 25th percentile, so 25% of the values will fall below that. So we have key 1, 61.5, and then our median or Q two is our 50th percentile. Um, we just want to order our data in order from least to greatest, so we can find our, uh, middle value, which, by doing that, we can see that our median is 65.5. And that's because we have an odd data set. So whenever you have or even data set. So when you have two values that are left in the middle. You just add them together and divide them by two to get your media. And then our Q three or the 75th percentile, um, is going to be 71.5. And so from this we can see that our inner portal range is going to be 10. So a plot looks like this. We have a four then at 61.5 60 65.5 in 71.5 in the 80. And this isn't inches. And then we find the value of the inter quartile range. So we just did that in part A. So we can make our plot. So it's just going to return. Mhm. See, we went to multiply that intercourse salary and try 1.5 to find the lowered upper limits. So the low is going to be 61.5 minus 10 times 1.5. So we get 46.5 and are high. Limit is 71.5 minus plus 10 mhm 1.5, which is equal to 86.5. So Part D asks if there is any data values below the lower limit and above the upper limit. So we want to list any suspected outliers and what might be an explanation for the outlier, So we can clearly see that are outlier is going to be that for value. Um, and this could be that they incorrectly wrote the wrong number. Or it could be in feet. Um, as an explanation for this outlier, Yeah.


Similar Solved Questions

5 answers
6* +y2 Determine and the position 28 vector aod the coeapute I [ Sketch the the curve. intersection
6* +y2 Determine and the position 28 vector aod the coeapute I [ Sketch the the curve. intersection...
5 answers
Grade: 75/230 Print Version Hide Question InformationTextbook LVideosUse Logarithmic Diflerentiation t0 findPreviewType sin(x) for sin(€) cos(x) for cos(z), and so onUse x^2 t0 square x; x^3 t0 cube X and $o on.Use sin(x) ) ^2 t0 square sin(x)Use In( ) for the natural logarithm:Do NOT simplify your answer:Points possible: 10 Unlimited attempts Message instructor about this questionLiceibe
Grade: 75/230 Print Version Hide Question Information Textbook L Videos Use Logarithmic Diflerentiation t0 find Preview Type sin(x) for sin(€) cos(x) for cos(z), and so on Use x^2 t0 square x; x^3 t0 cube X and $o on. Use sin(x) ) ^2 t0 square sin(x) Use In( ) for the natural logarithm: Do NOT...
5 answers
Let f(x) = e7za)Find Pa(c) for f(r) atc = 0b)Use your answer to part a) to approximate el.4
Let f(x) = e7z a) Find Pa(c) for f(r) atc = 0 b) Use your answer to part a) to approximate el.4...
3 answers
Show that~VBSBis an alternate symbol for Kor Kt
Show that ~VBS Bis an alternate symbol for Kor Kt...
5 answers
3.) Simplify:5 (643" y16
3.) Simplify: 5 (643" y16...
5 answers
Given the following vectors U and v, find a vector w in 23 so that {u, &, w} spans E3 and a non-zero vector z in 23 so that {u, v, 2} does not span %3.U = 852
Given the following vectors U and v, find a vector w in 23 so that {u, &, w} spans E3 and a non-zero vector z in 23 so that {u, v, 2} does not span %3. U = 8 5 2...
5 answers
Wina vaneRotorPitchHigh Speed Shaft Gear Box Controller
wina vane Rotor Pitch High Speed Shaft Gear Box Controller...
1 answers
Determine the field lines of the given polar vector fields. $$\mathbf{F}=\hat{\mathbf{r}}+r \hat{\boldsymbol{\theta}}$$
Determine the field lines of the given polar vector fields. $$\mathbf{F}=\hat{\mathbf{r}}+r \hat{\boldsymbol{\theta}}$$...
1 answers
The following problems involve addition, subtraction, and multiplication of radical expressions, as well as rationalizing the denominator. Perform the operations and simplify, if possible. All variables represent positive real numbers. $$ \frac{\sqrt{3}}{\sqrt{98 x^{2}}} $$
The following problems involve addition, subtraction, and multiplication of radical expressions, as well as rationalizing the denominator. Perform the operations and simplify, if possible. All variables represent positive real numbers. $$ \frac{\sqrt{3}}{\sqrt{98 x^{2}}} $$...
4 answers
Please explain the difference between ApproximateCounting Algorithm and Multiple Access with CollisionAvoidanceAnalyze the behavior of the algorithm when it is run onlyonce.
Please explain the difference between Approximate Counting Algorithm and Multiple Access with Collision Avoidance Analyze the behavior of the algorithm when it is run only once....
5 answers
Differentiate y =xln(2x +l) 2x a) 2x+1 2x b) 1n(2x+4) + 2x+1 c) 2xln(2x+1)Suppose energy price experienced an exponential increase and the inflation rate is 8.2%_ What will be the gas price in the next 3 years if the gas is S1.89 per gallon now? a) S2.24 b) S2.32 c) S2.42
Differentiate y =xln(2x +l) 2x a) 2x+1 2x b) 1n(2x+4) + 2x+1 c) 2xln(2x+1) Suppose energy price experienced an exponential increase and the inflation rate is 8.2%_ What will be the gas price in the next 3 years if the gas is S1.89 per gallon now? a) S2.24 b) S2.32 c) S2.42...
5 answers
Solve ax^3 + ax^2 + bx +b=0
solve ax^3 + ax^2 + bx +b=0...
5 answers
Question 9 (5 points) What is the pH of a 6.7 * 10-4 M HCI solution?03.174562.312.55Pae
Question 9 (5 points) What is the pH of a 6.7 * 10-4 M HCI solution? 03.17 456 2.31 2.55 Pae...
5 answers
41 02 -etescn +0 I[4 PointsMexanunni Ts 6fA)dy IQ) eryldrYWEanuclWhara C is constant 0f integration,Hankion Revie"Ahali
41 02 - etescn +0 I[ 4 Points Mexanunni Ts 6f A)dy IQ) eryldr YWEanu cl Whara C is constant 0f integration, Hankion Revie"Ahali...

-- 0.018646--