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Trust is primarily associated with two things cooperation andassistance and it is a key component to streamline group activitiesand participative decision making. I...

Question

Trust is primarily associated with two things cooperation andassistance and it is a key component to streamline group activitiesand participative decision making. It helps in creating a positiveattitude towards work. Organizations now are taking a strategicshift towards the implementation of management by objectives andtrust is a key component in its implementation. Research conductedbefore the implementation of management by objectives suggests thatmore than 69% of asian front line managers do

Trust is primarily associated with two things cooperation and assistance and it is a key component to streamline group activities and participative decision making. It helps in creating a positive attitude towards work. Organizations now are taking a strategic shift towards the implementation of management by objectives and trust is a key component in its implementation. Research conducted before the implementation of management by objectives suggests that more than 69% of asian front line managers do not trust their top level executives and same is the case with US workers that they do not trust their supervisors. What problem can be studied here? State the problem



Answers

Please provide the following information. (a) What is the level of significance? State the null and alternate hypotheses. (b) Find the value of the chi-square statistic for the sample. What are the degrees of freedom? What assumptions are you making about the original distribution? (c) Find or estimate the $P$ -value of the sample test statistic. (d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis of independence? (e) Interpret your conclusion in the context of the application. (f) Find the requested confidence interval for the population variance or population standard deviation. Interpret the results in the context of the application. Engineering: Jet Engines The fan blades on commercial jet engines must be replaced when wear on these parts indicates too much variability to pass inspection. If a single fan blade broke during operation, it could severely endanger a flight. A large engine contains thousands of fan blades, and safety regulations require that variability measurements on the population of all blades not exceed $\sigma^{2}=0.18 \mathrm{~mm}^{2}$. An engine inspector took a random sample of 61 fan blades from an engine. She measured each blade and found a sample variance of $0.27 \mathrm{~mm}^{2}$. Using a $0.01$ level of significance, is the inspector justified in claiming that all the engine fan blades must be replaced? Find a $90 \%$ confidence interval for the population standard deviation.

Starting with part a. For this question, we can see that our level of significance is 0.01 is given to us in the question are null hypothesis is going to be that muse equal to 11% that was given to us as well. We can form our ultimate hypothesis by seeing what the question is asking us to test for is asking us to simply test if the Data indicates that it is not equivalent to 11%. So it could be either way, it could be greater than or less than so, since it is just not equals, it is a two tailed test. Moving on to part B. We can see we have a normal distribution because it has given to us in the question. And since we have a normal distribution, we use this formula to calculate our Z score. We have all of these values given to us in our question. So our average or mean is 12.5% -11%, about about 5% over the square root of our sample size. Doing this math and making sure that we convert our percentages to decimals. Doing this math, we find that our Z score is 1.2. Now using our Z score and the normal CDF function on our calculator we can find an R. P value is equal to 0.23 For a two tailed test. Now comparing RP value of 0.23 with our level of significance. We see that it is greater than our level of significance of 0.1. So we do not reject. Are no hypothesis. Since we are not rejecting on Ohio hypothesis, this does not indicate crop loss in this county differs yeah from the average 11%.

Brooklyn 25 order the data values from the smallest to the largest, just 12 and 14. And 14, 15 and 16 on 17 and 18. And 19, 19 and 21 23 25 27 32 33 35 39 41 42 47. So determined The critical values Imperial and J, using up as equal to 0.5 and then is able to train. So the critical values is even toe find. So K is equal to the critical values plus one. So five plus one, she's six and the boundaries off the confidence in terms for the meeting or then the fix. Smallest value and the sixth largest value. Eso 123456 So the median inbounded between 17 and 33.

Problem 22 or with the data values from the smallest to the largest, which is hundreds, hundreds on one 1/6. Then 115 115 141 one or two and one for three and 14 green and one for five and one for seven and one for seven and 1 15 and 1 52 on 1. 53 and 1 55 and 1 57 and 1 61 63 and 1 64. So to remind the critical value using Table and J, who's offer is equal to opening one and then is equal to 20 so the critical value is equal to find, so add one toe critical. Various okay is equal to five plus one, which is six to the boundaries, off the confidence interval for the million or then six smallest and the sixth largest value insulting data list, which is 1 41 and 1 53

So what we want to do is create a categorical column. Essentially. So we're gonna make a table. So in this table, we will have our class, the tally, the frequency and the percent. So our class will have a M. H s. Then we tally the data in the telecom. Then we'll count the tally and replace the results in the frequency calm and then to do percent. We do frequency divided by total times 100. And then that will be our new percent. So we count what we have. Um, and we'll separate these, so we count. But we have we have 1234 So it's our frequency. Um, so here we have. 12345 12345 12345 12345 Um, we have 25. 1234 45 And then we have three more. So 28 then for each, we have 12345 six. And then as we just have to So we look at the percentages we see 10% or a 70% are, um, 5% are actually 15% our age 5% or s, and then we have our total, which is 40. So that means that's our 100%. So that's where the total came from. That's how he got our percentage. And this is our final categorical chart.


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