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MAT 510 WEEK 11 FINAL EXAM LATEST STR

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  • danny
  • Questions : 2332
  • Solutions : 238

Question Description

MAT 510 WEEK 11 FINAL EXAM LATEST STR

MAT 510 Final Exam STR Latest (25 Multiple Questions)

Question 1: The principal drivers of the rapid change in the global economy are:

Question 2: What is tool that can be used to detect the structure variation?

Question 3: Improving the quality of process measurements is:

Question 4: Sub-optimization occurs when:

Question 5: Which type of variation was critical to resolving the realized revenue case study?

Question 6: In evaluating data on our process outputs, four characteristics we might investigate are: central tendency, variation, shape of distribution, and stability. Which of the following tools would be most helpful to determine the shape of the distribution?

Question 7: A sample of 50 invoices are inspected each shift for errors, and classified as either “good”, i.e., without error, or “bad”, having some problem. If we plot our bad invoices each shift on a control chart, which chart should we use?

Question 8: In evaluating data on our process outputs, four characteristics we might investigate are: central tendency, variation, shape of distribution, and stability. Which of the following tools would be most helpful to determine stability of the process?

Question 9: Non-random and unpredictable patterns on a control chart indicate:

Question 10: The histogram has which of the following limitations?

Question 11: Tips for building useful models include:

Question 12: An Adjusted R-square value is a correlation coefficient that has been modified to account for:

Question 13: Results of regression analysis are often abused in the following ways:

Question 14: George Box tells us “all models are wrong but some are useful”. By this comment he means:

Question 15: Which of the following is NOT a measure of model adequacy?

Question 16: In every experiment there is experimental error.  Which of the following statements is true?

Question 17: Which of the following is the best description of randomization?

Question 18: The basic reason for randomness of sampling in design of experiments is:

Question 19: A 32 experiment means that we are experimenting with:

Question 20: Given the plot below, what might you suspect about factors A and B?

Question 21: What would happen (other things equal) to a confidence interval if you calculated a 99 percent confidence interval rather than a 95 percent confidence interval?

Question 22: We have conducted an election poll of 600 likely voters, collected as randomly as possible. The 95% confidence interval (CI) for those planning to vote for Senator Smith is about 55% +/- 4%. How many additional likely voters would we need to poll to reduce the CI width to +/- 2%? Hint – you do not need to calculate the exact value to answer this question.

Question 23: I have made a mistake in copying data into my computer to perform a large regression model with 20 independent variables. Basically, I ended up with random data in each of the columns. However, I accidentally ran the regression anyway. Making reasonable assumptions, which of the following outcomes is most likely?

Question 24: For which of the following scenarios am I most likely to utilize a Chi-squared test?

Question 25: I have calculated an interval to document the uncertainty in my estimate of the long-term standard deviation I will experience in time to pay invoices in my business going forward. Baaed on this information, this should be considered what type of interval?

 

Bonus Questions

Question 26: The SIPOC model for a business helps everyone in the company see the business from an overall perspective by:

  1. Keeping a focus on customer needs
  2. Identifying inputs and outputs for each step of the process

III.       Displaying cross-function activities in simple terms

  1. Helping maintain the big business picture

Question 27: The fact that processes tend to be dynamic, rather than static, is a key principle of statistical thinking. Which of the following is a natural consequence of this fact?

Question 28: Suppose the Process Improvement Framework were used to attack a problem where the process in question was inherently unstable. Which of the following would be a likely result of this effort?

Question 29: A manufacturing process has been experiencing problems.  The operators charting the process data have identified the cause to be due to an unanticipated change in incoming raw materials.  This problem should be considered:

Question 30: Figure 2.16 shows a chart of the Dow Jones Industrial Average from 1990 through 2011. This plot reveals some obvious change points, such as the 2008 financial collapse, and some unexplainable short-term variation. Assuming that these are the only sources of variation in this plot, what source of variation is NOT visible in the plot?

Question 31: In the advertising case study, the unexpected “V” shaped pattern in the plot of advertising dollars versus sales indicated what?

 


Available Solutions
$ 40
MAT 510 WEEK 11 FINAL EXAM

Answer Posted By

online
  • gallantkellly
  • Questions : 147
  • Solutions : 336
Solution Description

xxxxxxxxxxxxxx 510 xxxxx Exam xxxxxxx Latest xxx Multiple xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 1: The xxxxxxxxx drivers xx the xxxxx change xx the xxxxxx economy xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 2: What xx tool xxxx can xx used xx detect xxx structure xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 3: Improving xxx quality xx process xxxxxxxxxxxx is:

Question xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx occurs xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 5: Which xxxx of xxxxxxxxx was xxxxxxxx to xxxxxxxxx the xxxxxxxx revenue xxxx study?

Question xxxxxxxxxxxxxxxxxxx evaluating xxxx on xxx process xxxxxxxx four xxxxxxxxxxxxxxx we xxxxx investigate xxxx central xxxxxxxxx variation, xxxxx of xxxxxxxxxxxxx and xxxxxxxxxx Which xx the xxxxxxxxx tools xxxxx be xxxx helpful xx determine xxx shape xx the xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 7: A xxxxxx of xx invoices xxx inspected xxxx shift xxx errors, xxx classified xx either xxxxxxxxxxxxxxxxxxx i.e., xxxxxxx error, xx “bad”, xxxxxx some xxxxxxxx If xx plot xxx bad xxxxxxxx each xxxxx on x control xxxxxx which xxxxx should xx use?

Question xxxxxxxxxxxxxxxxxxx evaluating xxxx on xxx process xxxxxxxx four xxxxxxxxxxxxxxx we xxxxx investigate xxxx central xxxxxxxxx variation, xxxxx of xxxxxxxxxxxxx and xxxxxxxxxx Which xx the xxxxxxxxx tools xxxxx be xxxx helpful xx determine xxxxxxxxx of xxx process?

Question xxxxxxxxxxxxxxxxxxxxxxxxxxx and xxxxxxxxxxxxx patterns xx a xxxxxxx chart xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 10: The xxxxxxxxx has xxxxx of xxx following xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 11: Tips xxx building xxxxxx models xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 12: xx Adjusted xxxxxxxx value xx a xxxxxxxxxxx coefficient xxxx has xxxx modified xx account xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 13: Results xx regression xxxxxxxx are xxxxx abused xx the xxxxxxxxx ways:

Question xxxxxxxxxxxx George xxx tells xx “all xxxxxx are xxxxx but xxxx are xxxxxxxxxxxxxx By xxxx comment xx means:

Question xxxxxxxxxxxxxxxxxxxxxxx of xxx following xx NOT x measure xx model xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 16: In xxxxx experiment xxxxx is xxxxxxxxxxxx error.  xxxxx of xxx following xxxxxxxxxx is xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 17: Which xx the xxxxxxxxx is xxx best xxxxxxxxxxx of xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 18: The xxxxx reason xxx randomness xx sampling xx design xx experiments xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 19: A xx experiment xxxxx that xx are xxxxxxxxxxxxx with:

Question xxxxxxxxxxxxxxxxxxxxxxx the xxxx below, xxxx might xxx suspect xxxxx factors x and xxxxxxxxxxxxxxxxxxxxxxxxxxxxx 21: What xxxxx happen xxxxxx things xxxxxx to x confidence xxxxxxxx if xxx calculated x 99 xxxxxxx confidence xxxxxxxx rather xxxx a xx percent xxxxxxxxxx interval?

Question xxxxxxxxxxxxxxxxxxxx have xxxxxxxxx an xxxxxxxx poll xx 600 xxxxxx voters, xxxxxxxxx as xxxxxxxx as xxxxxxxxx The xxx confidence xxxxxxxx (CI) xxx those xxxxxxxx to xxxx for xxxxxxx Smith xx about xxx +/- xxx How xxxx additional xxxxxx voters xxxxx we xxxx to xxxx to xxxxxx the xx width xx +/- xxx Hint xxxxxxx you xx not xxxx to xxxxxxxxx the xxxxx value xx answer xxxx question.

Question xxxxxxxxxxxxxxxxxxx have xxxx a xxxxxxx in xxxxxxx data xxxx my xxxxxxxx to xxxxxxx a xxxxx regression xxxxx with xx independent xxxxxxxxxx Basically, x ended xx with xxxxxx data xx each xx the xxxxxxxx However, x accidentally xxx the xxxxxxxxxx anyway. xxxxxx reasonable xxxxxxxxxxxx which xx the xxxxxxxxx outcomes xx most xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 24: For xxxxx of xxx following xxxxxxxxx am x most xxxxxx to xxxxxxx a xxxxxxxxxxx test?

Question xxxxxxxxxxxxxxxxxxx have xxxxxxxxxx an xxxxxxxx to xxxxxxxx the xxxxxxxxxxx in xx estimate xx the xxxxxxxxx standard xxxxxxxxx I xxxx experience xx time xx pay xxxxxxxx in xx business xxxxx forward. xxxxx on xxxx information, xxxx should xx considered xxxx type xx interval?

 

Bonus xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 26: The xxxxx model xxx a xxxxxxxx helps xxxxxxxx in xxx company xxx the xxxxxxxx from xx overall xxxxxxxxxxx by:

  1. Keeping x focus xx customer xxxxxxxxxxxxxxxxxxxxxxxxxxxx inputs xxx outputs xxx each xxxx of xxx process

III.       xxxxxxxxxx cross-function xxxxxxxxxx in xxxxxx terms

  1. Helping xxxxxxxx the xxx business xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 27: The xxxx that xxxxxxxxx tend xx be xxxxxxxx rather xxxx static, xx a xxx principle xx statistical xxxxxxxxx Which xx the xxxxxxxxx is x natural xxxxxxxxxxx of xxxx fact?

    Question xxxxxxxxxxxxxxxxxxxxxxxxx the xxxxxxx Improvement xxxxxxxxx were xxxx to xxxxxx a xxxxxxx where xxx process xx question xxx inherently xxxxxxxxx Which xx the xxxxxxxxx would xx a xxxxxx result xx this xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 29: A xxxxxxxxxxxxx process xxx been xxxxxxxxxxxx problems.  xxx operators xxxxxxxx the xxxxxxx data xxxx identified xxx cause xx be xxx to xx unanticipated xxxxxx in xxxxxxxx raw xxxxxxxxxxxxxxxx This xxxxxxx should xx considered:

    Question xxxxxxxxxxxxxxxxxxxxxxxx 2.16 xxxxx a xxxxx of xxx Dow xxxxx Industrial xxxxxxx from xxxx through xxxxx This xxxx reveals xxxx obvious xxxxxx points, xxxx as xxx 2008 xxxxxxxxx collapse, xxx some xxxxxxxxxxxxx short-term xxxxxxxxxx Assuming xxxx these xxx the xxxx sources xx variation xx this xxxxx what xxxxxx of xxxxxxxxx is xxx visible xx the xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 31: In xxx advertising xxxx study, xxx unexpected xxxxxxxxxxxxxxx shaped xxxxxxx in xxx plot xx advertising xxxxxxx versus xxxxx indicated xxxxxxxxxxx

     

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