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4190 employees judge Iheir peers by the cleanEness their workspaces You randomly select emplovees and ask them whether they judge their peers by the cleanliness the...

Question

4190 employees judge Iheir peers by the cleanEness their workspaces You randomly select emplovees and ask them whether they judge their peers by the cleanliness their workspaces The random variable represents the numbet ernployees who judge teir peers by the cleanliness their work spaces Complete par through helouConstnuctbinomtal distribution using PLLand p =OuG de Cime blace=nutatded

4190 employees judge Iheir peers by the cleanEness their workspaces You randomly select emplovees and ask them whether they judge their peers by the cleanliness their workspaces The random variable represents the numbet ernployees who judge teir peers by the cleanliness their work spaces Complete par through helou Constnuct binomtal distribution using PLL and p = OuG de Cime blace= nutatded



Answers

Use the bar graph at the left, which shows the highest level of education received by employees of a company. Find the probability that the highest level of education for an employee chosen at random is a master's degree.

Okay. The total number off people 91 the people who have an associate is the number of it is Chinese three. So the probability would be number of associate over the number off total which is Yuko Thio Ministry over 91. So this is 0.253 This will be our answer.

Yeah, the number of total people is 91 the number off people who have high school degrees for, so the probability would be for over 91 which is security 910.44

So this will calculate the total number in this simple space, which is three plus 25 plus 34 10 3 a school. That's too okay. And this is a good to 91 and the school is PhD. Gray is three over 91 which is 1233 But this is the probability.

All right, so in this problem, you're asked to construct a binomial distribution, and any time you're working with binomial distributions, you have four variables that you are looking for and the first variable is your N, which is your number of trials X, which is counting the number of successes p, which is your probability of success, and Q, which is your probability of failure. And once you have identified all of those variables, then you're going to apply the formula to find those probabilities. And that's gonna be P of X equals N C X multiplied by P, raised to the X power multiplied by Q raised to the n minus X power. So let's read through this problem and let's identify the values of each of these variables. So we are talking about a messy desk, and 38% of hiring managers have a negative view of workers that have a messy desk. So that's our value for P. So we've got 38% of hiring managers having a negative view. So if 38% have a negative view, that means there's 62% of hiring managers that don't have a negative view and we're going to randomly select 10 hiring managers. So that means our N value is going to be 10. And if we ask those 10, how many have a negative view? Could be that zero of the 10 have a negative view, or one or two or three all the way up to and including all 10 may have a negative view of their workers because of a messy desk. So what is a probability distribution? So we're going to take thes values, and we're going to organize them into a chart. So our probability distribution is going to be a two column chart listing all the possible outcomes of the experiment and their associative probabilities. So in our chart, we're going to put the numbers zero through 10. Now we can apply that formula 11 different times, replacing all the exes with a zero and then going back and replacing all the exes with the one and then going back and replacing all the exes with the two and so forth. Or we can be a little bit more efficient by using our graphing calculator and in using our graphing calculator. What we're going to do is we're going to apply the formula. So in place of N in that formula, we're gonna put a 10 see x, and that X is going to continue to change. So I'm gonna leave it as an ex for the moment. And we're multiplying that by the P value, which is 0.38 raised to the X power multiplied by the 62 raised to the 10 minus X power. And I'm gonna bring in my graphing calculator and we're going to access the lists by hitting the stat button and edit and enlist one. We're going to put all of the possible X values, so we're gonna type in zero through 10, and then we're gonna go sit on top of list, too. And as we type in, since we've put all of our X values enlist to, then everywhere we see an ex, we're gonna type list to instead of an X. So we're going to have 10. We're going to access our combination, which is under the math key, and over under the probability. And instead of X, we're gonna type list one in because we've housed all of our exes in that list. One column. We're gonna multiply it by the p value 0.38 raised to the list. One power and we're gonna multiply that by the Q Value 62 Raised to the 10 minus list. One. Power. When we hit Enter, it's going to give us all of the probabilities that we need to just need to copy into our distribution table. So there they are, so we're just going to copy them down. So the probability out of 10 getting zero hiring managers with a negative view of their worker would be 00.8393 And then we're going to do the probability of 1.514409 and just keep copying for two. It's 20.1418774 for 3.231 8856 for 4.248 7161 five is 50.18 to 9. 266 6934 303 seven is 03 to 7 2 to 1 probability that eight out of 10 have a negative view. Would be 007 5208 probability of nine Would be 001 0243 and 10. Notice it's in scientific notation. The e negative five is telling you to move the decimal 50.5 places to the left, resulting in 0.6 to 7 82 And that is the answer for part A. This is your probability distribution for selecting 10 hiring managers and asking whether they have a negative view of workers with a messy death. Alright, in part B, we want to take that information and we want to draw a binomial distribution graph and we want to use a hist a gram. So when it comes time to do the hissed a gram, we're gonna need a vertical axis and a horizontal axis. And when you look at these probabilities, the highest one is pretty close to point 25 So that means our vertical access has to get close to 0.25 So what if I count by 0.5 so this would be 0.5 points 10.15 20.25. So now we're ready to draw our hissed a gram in our history. Graham is going to be towers so the first tower is less than 1%. So it's gonna be really, really small. And actually, that's probably even too high, really, really small. And we wanna make sure towers aren't too wide either, because we've got to get 10 towers. So that's your probability for zero. One is slightly bigger than five two is at about 14% so it's just under the 15. Three is at 23%. It's probably right around there. Four is at almost 25% so there's four. Then they start coming back down. Five is at 18% so somewhere right there and six is at about a little over 9% and seven is at about 3% and eight is under 1% and nine ISS smaller yet and 10 is even smaller yet, so there is a picture of our probability distribution, and that is your answer for Part B. And then finally, part C Part C is asking you identify any values of the random variable X that you would consider unusual. So unusual is going to be anything that has a probability that is less than 0.5 So the X values that result in probabilities that are less than 0.5 would be here. So ex being zero is unusual, right here is less than five. So X, being seven or eight or nine or 10 would all be unusual. So in the context of this problem, if we were asking 10 hiring managers finding zero that have a negative view of workers out of those 10 would be unusual finding 789 or 10 to say in any sample of 10. To say they have a negative view would also be unusual.


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