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1. Summarize a business problem and describe both the sampling technique and the sample size that you would require to set up a research project to solve this problem.
2. A situation occurs at your company where you are trying out a new process improvement for invoice processing. Data are collected for a week before the implementation and it takes the department 5.3 hours to process the invoice with a sd of 7.6. Afterwards, the department can process the invoice in 4.7 hours with a sd of 8.3. The project manager declares this test a success and wants to implement this new process in the rest of the company. After doing a t-test, you do not find significance, as there is too much variability in the data both before and after. What would you do in this situation?
3. Describe a business situation that you have had or might face that will benefit from the use of confidence intervals?
Compute the probability of seven consecutive points falling above the centerline given a stable process. Is this probability associated with type I or type II error?
Their resting heart rates were measured. A partial ANOVA table is given.
Give a mathematical expression for the probability density function of driving distance.
Using Analysis of Variance (ANOVA) test at 5% level if there are important differences in mean sales calls made across the three branches.
Using the probabilities above what is the expected size of family you draw?
A certain airplane has 2 independent alternators to provide electrical power. The probability that a given alternator will fail on a 1 hour flight is 0.02. What is the probability that (a) both will fail? (b) Neither will fail? (c) One or the othe..
In a survey conducted to see how long Americans keep their cars, 2000 automobile owners were asked how long they plan to keep their present cars. The results of the survey follow. Find out the probability distribution associated with these data.
The reason why we finish our calculation by dividing range by 4 is that in most data sets 95% of the data values fall within two standard deviations of the mean.
Construct a 90 percent confidence interval for the proportion of all kernels that would not pop.
The mean of a sample is 22.5. The mean of 1000 bootstrapped samples is 22.491. The bias of the bootstrap mean is
Mention your decision regarding the null hypothesis. If H 0 rejected can we conclude that treatment 2 and treatment 3 differ? Use 95 percent level of confidence.
What is your conclusion? Are the two variables independent?
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