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Two makes of electric bulbs A and B are tested

/in /by

Get college assignment help at Smashing Essays Question Two makes of electric bulbs A and B are tested and observed. Bulbs of make A exhibit mean life of 900 hrs. and standard deviation of 30 hrs. Those of make B show mean life of 860 hrs. and standard deviation of 20 hrs. Find the probability that the mean life based on a random sample of 40 bulbs of make A being, say, 28 hours less than the mean life of bulbs of make B based on a random sample of 30 bulbs

The mean length of imprisonment for​ motor-vehicle theft offenders in

Question The mean length of imprisonment for​ motor-vehicle theft offenders in this country is 18.7 months. A hypothesis test is to be performed to decide whether the mean length of imprisonment in this city differs from the national mean. The null and alternative hypotheses are Upper H 0H0​: muμequals=18.718.7 ​months,  Upper H Subscript aHa​: muμnot equals≠18.718.7 months.

A data analytics firm hired by a Republican candidate running

Question A data analytics firm hired by a Republican candidate running for political office wants to test whether its practices were successful in increasing voter turnout among registered Republicans. Suppose that data were collected for a random set of 10 cities, where each difference is calculated by subtracting the percent voter turnout before the candidate ran for office from the percent voter turnout from after the election. Assume that the populations are normally distributed. The firm uses the alternative hypothesis Ha:μd>0. Suppose the test statistic t is computed as t≈5.41, which has 9 degrees of freedom. What is the p-value for the hypothesis test, rounded to three decimal places?

A scientist claims 6% of viruses are airborne. If the

Question A scientist claims 6% of viruses are airborne. If the scientist is accurate, what is the probability that the proportion of airborne viruses in a sample of 403 viruses would differ from the population proportion by greater than 3%. Round your answer to four decimal places.

How do you calculate a Z score?

Question How do you calculate a Z score?

A scientist claims that 6% of viruses are airborne. If

Question A scientist claims that 6% of viruses are airborne. If the scientist is accurate, what is the probability that the proportion of airborne viruses in a sample of 403 viruses would differ from the population greater than 3 %

What is the minimal sample size needed for a 95%

Question What is the minimal sample size needed for a 95% confidence to have a maximal margin of error 0.1 in the following in the following scenarios (round to the nearest whole.):a) a preliminary estimate for p is 0.13b) there is no preliminary

· General Psychology: o Clinicians at a small clinic have

Question ·        General Psychology: o   Clinicians at a small clinic have been introduced to a new method to treat post-traumatic stress disorder (PTSD) in their clients for veterans. Research indicates that virtual reality (VR) is a highly effective treatment option for patients with PTSD. Currently, the clinic uses only cognitive processing therapy (CPT) with their patients suffering from PTSD. The clinicians would like to find out whether VR therapy has different results from CPT therapy. The measure used by the clinic to measure PTSD symptoms is the Combat Exposure Scale. Both therapies need to be applied for a minimum of 12 weeks to be effective.Write a 525- to 750-word paper that addresses the following for your chosen scenario:·        Clearly define the problem or issue you are addressing. Provide a brief background of any research you have found that might affect your research hypothesis. ·        Create a research hypothesis based on the information provided in each scenario. You have been given a data set (Microsoft® Excel® document) with two sets of interval data (just the numbers, as you must decide what they represent, such as method A results or method B results). This means you are going to test one thing against another, such as which method works best (step 1 of the steps to hypothesis testing). State the null and research hypotheses. Explain whether these hypotheses require a one-tailed test or two-tailed test, and explain your rationale. ·        Describe the sample you will use. Sample size will be 30 for each group, which are provided in your data set. Explain what type of sampling you selected. ·        Do you think you would also collect some descriptive data, such as gender, age, or shift? Why do you think it makes sense to collect descriptive data? 

Can you provide an example of what type of research

Question Can you provide an example of what type of research question would best be answered by an independent sample t-test?

Hi I am trying to get a curve to fit

Question Hi I am trying to get a curve to fit my data using MS excel solver. The data is job duration data and there are n = 58 data points. The jobs are arranged in bins that are spread out in 5 minute intervals. See below. Bin Frequency5 010 015 120 425 330 835 1140 945 250 755 660 3 65 370 1I am pretty certain that the data is log normal in its distribution. I am trying to learn home to fit a curve to thre data distribution to deliver the probability density function (PDF). The PDF will be very usuful to more accurately predict the length on the job in the future. I am trying to learn this on MS Excel solver. I have tried everything. SimonAny help that you can give me would be very much appreciated.

a Presentation on Healthcare Innovation Strategies, Technology Improvement, Quality, and Cost in the 21st-Century

Get college assignment help at Smashing Essays CompetencyApply principles of organizational learning, innovation, and change in healthcare organizations.InstructionsAs the leader of this healthcare organization, you have been invited to a healthcare symposium to discuss organizational learning, innovation, and change in healthcare organizations. You are requested to give a presentation on your organization’s changes for improvement, learning methods employed in the change process, and what innovations your organization used for the improvements.You are presented with the following details to complete your presentation.On a separate slide, provide references in APA format.

What is the difference between simple random sample, cluster sample

Question What is the difference between simple random sample, cluster sample and stratified random sample?

Major League Baseball (MLB) consists of teams that play in

Question Major League Baseball (MLB) consists of teams that play in the American League and the National League. MLB collects a wide variety of team and player statistics. Some of the statistics often used to evaluate pitching performance are as follows:ERA: The average number of earned runs given up by the pitcher per nine innings. An earned run is any run that the opponent scores off a particular pitcher except for runs scored as a result of errors.SO/IP: The average number of strikeouts per inning pitched.HR/IP: The average number of home runs per inning pitched.R/IP: The number of runs given up per inning pitched. Attachment 1 Attachment 2 ATTACHMENT PREVIEW Download attachment 1.PNG ATTACHMENT PREVIEW Download attachment 2.PNG

Homework Problem 6You work for All-Care Medical Supply Company which

Question Homework Problem 6You work for All-Care Medical Supply Company which provides medical supplies to pharmacies, hospitals, clinics, and independent physicians throughout Central Florida. As part of your new duties you need to purchase exam gloves for resale. Your predecessor in this position just ordered 1,200 cases of gloves a week. This ordering system sometimes leads to back orders (orders that can not be immediately filled) and times when you have too many gloves on hand. You have decided that it is time to figure how many cases of exam gloves you actually sell per week and to adjust your orders to meet the expected sales. The numbers of cases of exam gloves sold per week for the past 24 weeks is given below. 1) Determine your projected number of exam glove sales using 3 and 4 week moving averages. Which time period provides the best forecast and why?2) Determine your projected number of exam glove sales using a 4 week weighted moving average. You have decided to place more weight on later sales than earlier sales. You decide to try weights of 1, 2, 3, and 4 (for weeks 1 to 4) respectively and weights of 1, 2, 4, and 6 (for weeks 1 to 4). Which method provides the best forecast and why?3) Determine your projected number of exam glove sales using exponential smoothing. You have decided to use the following alphas: 0.2, 0.3, 0.4, and 0.5. Which alpha provides the best forecast and why?4) Determine your projected number of exam glove sales using exponential smoothing with trend. Using an alpha of 0.3 and beta’s of 0.3, 0.4, and 0.5 which provides the best forecast and why?5) Determine your projected number of exam glove sales using linear trend. What is the forecasted amount of sales and how good is the forecast?6) Using the answers to 1 -5 above, which method should you use for future forecasting and how many cases of exam gloves should you order? Explain your answer.PLEASE HELP ME WITH THIS ASSIGNMENT! ATTACHMENT PREVIEW Download attachment Screen Shot 2019-08-06 at 12.44.34 AM.png

Use the SPSS Frequencies command to produce a frequency table

Question Use the SPSS Frequencies command to produce a frequency table for the variable HEALTH. Answer the following questions in your table:What is the number of valid respondents?Based on the valid number of respondents, what percentage of the sample reported being in excellent health?What portion of the sample is in poor health?What is the best way to graphically display these data? Explain.The data set included answers to a series of questions on attitudes about immigrants. In the chapter, we examined the relationship between race and attitudes about immigrants and jobs (IMMJOBS). There are two additional variables to consider—IMMCULT (Immigrants undermine American culture) and IMMEDUC (Legal immigrants should have the same education as Americans).Complete the following steps:

Please help me formulate a hypothesis for the following scenario

Question Please help me formulate a hypothesis for the following scenario and sets of numbers provides? ·        A large medical facility is experiencing too many missedappointments in its primary and specialty care clinics. The facility hasnoticed that not all patients respond well to reminder calls regardingfollow-up appointments. Some patients do not answer calls and do not seem torespond to voice mail requesting they call the facility. The result is thatmany follow-up appointments are missed. Facility management have read articlesthat indicate people respond very well to text messages and would like to see whichmethod provides the least amount of missed appointments. Missed appointmentsare tracked in the facility database on a monthly basis. ·         research hypothesis based on the information providedin each scenario. You have been given a data set (Microsoft® Excel®document) with two sets of interval data (just the numbers, as you must decidewhat they represent, such as method A results or method B results). This meansyou are going to test one thing against another, such as which method worksbest (step 1 of the steps to hypothesis testing). State the null and researchhypotheses. Explain whether these hypotheses require a one-tailed test ortwo-tailed test, and explain your rationale. GROUP 1 1.3 2.5 2.3 8.1 5 7 7.5 5.2 4.4 7.6 9 7.6 4.5 1.1 5.6 6.2 7 6.9 5.6 5.2 9 7.6 4.5 1.1 5.6 6.2 7 6.9 5.6 5.2 GROUP 2 6.5 8.7 9.8 10.2 7.9 6.5 8.7 7.9 8.7 9.1 8.4 6.4 7.2 5.8 6.9 5.9 7.6 7.8 7.3 4.6 8.4 6.4 7.2 5.8 6.9 5.9 7.6 7.8 7.3 4.6

a Presentation on Healthcare Innovation Strategies, Technology Improvement, Quality, and Cost in the 21st-Century

CompetencyApply principles of organizational learning, innovation, and change in healthcare organizations.InstructionsAs the leader of this healthcare organization, you have been invited to a healthcare symposium to discuss organizational learning, innovation, and change in healthcare organizations. You are requested to give a presentation on your organization’s changes for improvement, learning methods employed in the change process, and what innovations your organization used for the improvements.You are presented with the following details to complete your presentation.On a separate slide, provide references in APA format.

Hello, I’m looking forward for the answers and with its

Question Hello, I’m looking forward for the answers and with its formula. /> Attachment 1 Attachment 2 Attachment 3 Attachment 4 ATTACHMENT PREVIEW Download attachment AA1.JPG ATTACHMENT PREVIEW Download attachment AA2.JPG ATTACHMENT PREVIEW Download attachment AA3.JPG ATTACHMENT PREVIEW Download attachment AA4.JPG

The University Health Care System (UHCS) is an academic medical center with over

The University Health Care System (UHCS) is an academic medical center with over 1,200 licensed beds and over 9,000 employees. The system comprises the University Hospital, Winston Geriatric Hospital, Jefferson Rehabilitation Hospital and two outpatient centers in the metropolitan area. UHCS has a history of being a patriarchal, physician-driven organization. When University Health Care first started taking patients, it was viewed as a mecca to which community physicians throughout the South referred difficult-to-treat patients. That referral mentality persisted for decades, so physicians within the system had a difficult time making the transition to an organization that had to compete for patients with other healthcare entities in that region.In recent years, University Health Care System has evolved and given physicians proportionately more clout in decision making, in part because the healthcare leadership team has not stepped forward. Creating a balance between clinician providers and administrative leadership is a real issue. In the midst of the difficulty, both groups have agreed to embark on the electronic health record (EHR) journey. Currently about 55 percent of the system’s patient record is electronic; the remainder is on paper. The physicians as a whole, however, have embraced technology and view the EHR as the “right road” to take in achieving the organization’s goal of providing high-quality, safe, cost-effective patient care.Currently, UHCS is in the midst of rolling out the CPOE portion of the EHR project. A multidisciplinary decision-making project was established before beginning the initiative, and leaders and clinicians tried to educate themselves on what the CPOE project would entail. They were familiar with cases such as one at Cedars-Sinai where CPOE was halted after a physician uproar over the time it took to use and patient safety concerns. To help ensure this did not happen at the University Health Care System, the leadership team decided to take a slower, phased-in approach. Team members visited similar organizations that had implemented CPOE, attended vendor user-group conferences, consulted with colleagues from across the nation, and articulated the following project goals:The board has made it very clear that it wants regular updates on the progress of the project and expects to see what the return on the investment has been.Questions:1. How might you evaluate the CPOE implementation process at University Health Care System? Give examples of different methods or strategies you might employ.2. How would you respond to the board’s desire for a “return on investment” from this initiative? Is it a reasonable request? Why or why not?3. Assume you are to lead the evaluation component of this project. You have reviewed the goals for this project. What process would you use to develop a plan for assessing the value of CPOE? Who would be involved? What roles would they play? How would you decide on the best metrics to use? What baseline data would you want to collect or review?Must have a Title page, Abstract, use of Level I and II headings, a Conclusion section, and a References page. Use the template provided. Length 2-5pgs excluding Title, abstract, and reference pages. Additional Resources:http://www.himss.org/valuesuite/value-stepshttp://www.healthcareitnews.com/news/how-measure-value-health-ithttps://healthit.ahrq.gov/key-topics/computerized-provider-order-entryCPOE ROI.pdfCPOE Benefits.pdfCITL ACPOE Executive Preview_0.pdf2015 National University Research Paper Template.doc

Compute C7,2. (Enter an exact number.)

Question Compute C7,2. (Enter an exact number.)    

Dataset with nothing missing- nest nest_size sex weight brightness noise

Question Dataset with nothing missing- nest nest_size sex weight brightness noise bravery 1 10 F 152 15.9 295.8 176.1 1 10 M 149 12.8 398.2 128.5 1 10 F 158 10.3 331.5 171.8 1 10 M 152 11.7 208.9 161.8 1 10 M 132 12.4 78.8 143.9 1 10 M 133 19 313.7 148.6 1 10 M 135 20.6 327.4 132 1 10 M 149 15.4 367.2 188.9 1 10 F 155 12 264.8 159.7 1 10 F 138 12.4 342.2 159.6 2 3 F 220 19.4 141.6 76.6 2 3 F 188 23.1 301.7 40 2 3 M 191 35.8 269.2 33.9 3 6 M 253 25.1 478.2 145.3 3 6 M 232 25.8 240.2 140.5 3 6 M 226 27.4 364.5 115.3 3 6 M 255 33.5 271.4 128.8 3 6 M 236 27.8 434.1 132.2 3 6 M 243 25.9 308.6 191.7 4 4 M 129 19.7 332.8 31.5 4 4 F 107 11.7 184.3 30.7 4 4 F 134 7.3 212.8 42.5 4 4 F 122 7.3 312 -4.2 5 5 M 76 10 375.2 52.3 5 5 F 70 8.6 33.9 40.4 5 5 M 62 12.3 220.6 27.8 5 5 M 63 12.3 260.6 19.4 5 5 M 61 11.6 204.8 41.7 6 8 F 78 3.9 406.9 46.6 6 8 F 87 5.5 213.7 71.4 6 8 F 96 13.9 72.7 60.6 6 8 F 79 3.8 196.5 44.7 6 8 M 91 14.1 326.3 66.6 6 8 M 89 13.1 353 54.6 6 8 F 79 4 394.6 58 6 8 M 85 15.8 365.4 44.2 7 9 F 104 7.8 215.8 73.5 7 9 F 107 8.1 364.8 69.3 7 9 M 105 20 14.7 51.3 7 9 M 106 23.6 300.6 59.3 7 9 F 105 15.2 338 28.1 7 9 F 93 12.9 295.2 41.4 7 9 M 93 23.6 478.8 67.1 7 9 M 100 23.7 257.3 58.8 7 9 F 104 8.6 170.4 52.8 8 4 M 209 11.4 296.3 67.3 8 4 F 208 3.1 169.5 62 8 4 F 196 0.6 218.2 85 8 4 M 181 10.5 524.3 87.3 9 4 F 236 6.8 446.5 106 9 4 F 275 7 485 92.6 9 4 F 254 6.4 433 93.4 9 4 F 266 7.4 305.9 82.6 10 10 F 80 6.1 436.1 57.4 10 10 M 86 22.4 247.3 51.1 10 10 M 83 22 249.1 41.4 10 10 M 80 24.4 223 52.5 10 10 M 82 23.5 284 37 10 10 M 90 19.5 282 93 10 10 F 93 11.8 342.5 79 10 10 M 94 24.3 334.4 75.8 10 10 F 95 7.4 283.7 110.8 10 10 F 91 12.7 258.3 77.4 11 5 M 158 9.7 276.2 71.5 11 5 M 160 12.6 373 74.5 11 5 M 151 9.7 187.4 71.8 11 5 F 142 7.6 201.6 88 11 5 F 161 2.6 307.3 74.2 12 5 F 102 6.7 159.5 40.2 12 5 M 100 6.4 233.7 41 12 5 M 103 10.2 300 49.2 12 5 F 95 9.5 499.6 40.5 12 5 F 100 6.2 122.7 40.1 13 9 F 133 14.5 252.9 106.6 13 9 M 114 26.7 358.3 79.9 13 9 F 132 18.1 441.2 116.9 13 9 M 123 25.5 310.7 101.1 13 9 F 119 17.3 260.4 125.2 13 9 M 116 27 345.8 96.6 13 9 F 134 17.7 261.8 94.4 13 9 M 128 29.7 181.5 93 13 9 M 128 29.9 307.9 90.8 14 13 M 56 9.6 155.8 58.2 14 13 M 57 8.6 277.8 55.7 14 13 F 63 7.7 282.3 79.2 14 13 F 53 4.2 219.5 79.8 14 13 M 65 12.1 417.7 71.1 14 13 F 52 0.9 280 72.1 14 13 F 64 5.5 349.4 100.7 14 13 F 55 3.6 321.7 54.4 14 13 M 64 6.2 359.3 90.8 14 13 M 54 10.3 187.4 50.5 14 13 F 63 -0.2 257.8 70.3 14 13 M 59 5.9 388 77.1 14 13 F 62 6.9 374.5 45.4 15 4 M 300 30.4 494.1 85.4 15 4 M 318 26.9 333 144.4 15 4 F 327 16.6 268 135.4 15 4 F 259 8.2 353.9 129.2 16 7 M 168 24.6 168 126.4 16 7 M 170 19.5 392.8 132.6 16 7 M 160 25.4 364.8 101.7 16 7 M 178 24.9 366.1 129.9 16 7 F 184 8.2 256.8 149.1 16 7 F 160 14.9 446.5 108.7 16 7 F 159 11.9 263.2 85.8 17 7 F 75 6.9 228.3 37.5 17 7 M 84 18.5 369.5 32.9 17 7 M 93 10.1 337.7 20.4 17 7 M 80 12.7 313.8 43.9 17 7 M 83 16.5 258 66.1 17 7 M 85 18 262.5 33.4 17 7 F 93 8.4 200.3 13.1 18 6 M 93 7 236 17.3 18 6 M 103 13 274.9 37.3 18 6 F 85 5.2 235.1 10.6 18 6 M 90 12.5 323.6 14.8 18 6 F 89 -0.5 287.5 46.9 18 6 M 82 8.2 147.3 -3.6 19 6 F 142 9.2 308.9 61 19 6 M 148 26.5 299.1 75.2 19 6 M 133 24.4 359.2 50.6 19 6 M 140 18 256.9 96.1 19 6 F 137 7.5 647.3 50.7 19 6 M 162 23.9 328.6 66.4 20 3 M 206 9.3 466 81.1 20 3 M 234 11 269.9 82.9 20 3 M 228 11.6 405.3 63.3 21 4 F 164 10.3 308.2 60 21 4 M 179 17.8 114.8 18 21 4 M 165 26 159.2 70.6 21 4 F 201 13.2 370 37 22 8 F 172 15.4 366.2 151.6 22 8 F 151 14.3 196.8 104.3 22 8 M 141 32.3 191.6 106.9 22 8 F 143 15.4 246.3 173.3 22 8 F 142 19.7 351.8 138.6 22 8 M 138 28.1 345.5 61.8 22 8 F 167 15.8 198.5 82.1 22 8 F 171 20.5 308 86 23 11 M 133 9.6 427.6 160.3 23 11 F 113 7.6 352.2 141.1 23 11 F 128 1.6 364.5 150.5 23 11 F 137 0.1 339.1 172.6 23 11 M 118 8.8 315.8 167 23 11 F 138 5.7 540.2 154.4 23 11 F 125 4 401.7 138.7 23 11 M 107 10.9 348.2 87.9 23 11 M 131 8.1 433.3 128.2 23 11 M 118 8.5 302.7 125.2 23 11 M 108 14.2 469.1 128.2 24 7 M 214 35.3 428.4 83.5 24 7 M 207 37 314.2 79.7 24 7 M 177 34.6 298.8 77.4 24 7 M 204 37.6 364.8 99.2 24 7 M 190 30.3 224.5 101.9 24 7 M 204 34.1 393.3 72.7 24 7 M 214 34.5 261.7 80.1 25 2 F 193 17.8 325.6 6.5 25 2 M 202 28 288.3 26.1 DATASET with missing values-nest nest_size sex weight brightness noise bravery 1 10 F 152 15.9 295.8 176.1 1 10 M 149 12.8 398.2 128.5 1 10 F 158 10.3 331.5 171.8 1 10 M NA 11.7 208.9 NA 1 10 M 132 12.4 78.8 143.9 1 10 M 133 19 313.7 148.6 1 10 M 135 20.6 NA 132 1 10 M 149 15.4 367.2 188.9 1 10 F 155 12 264.8 159.7 1 10 F NA 12.4 342.2 159.6 2 3 F 220 19.4 141.6 76.6 2 3 F 188 NA 301.7 40 2 3 M 191 35.8 269.2 33.9 3 6 M 253 NA 478.2 145.3 3 6 M NA 25.8 NA 140.5 3 6 M 226 27.4 364.5 115.3 3 6 M 255 33.5 271.4 128.8 3 6 M 236 27.8 434.1 132.2 3 6 M 243 25.9 NA 191.7 4 4 M 129 NA 332.8 31.5 4 4 F 107 11.7 184.3 30.7 4 4 F 134 7.3 NA 42.5 4 4 F 122 7.3 312 -4.2 5 5 M NA NA 375.2 52.3 5 5 F 70 8.6 33.9 40.4 5 5 M 62 12.3 220.6 27.8 5 5 M 63 NA NA 19.4 5 5 M 61 11.6 204.8 41.7 6 8 F 78 3.9 406.9 46.6 6 8 F 87 5.5 213.7 71.4 6 8 F 96 13.9 72.7 NA 6 8 F 79 3.8 196.5 44.7 6 8 M 91 14.1 326.3 NA 6 8 M 89 13.1 353 54.6 6 8 F 79 4 394.6 58 6 8 M 85 15.8 365.4 44.2 7 9 F 104 7.8 215.8 73.5 7 9 F 107 8.1 364.8 69.3 7 9 M 105 NA 14.7 51.3 7 9 M 106 23.6 300.6 59.3 7 9 F 105 15.2 338 28.1 7 9 F 93 12.9 295.2 41.4 7 9 M 93 23.6 478.8 67.1 7 9 M 100 23.7 257.3 58.8 7 9 F 104 8.6 170.4 52.8 8 4 M 209 11.4 NA 67.3 8 4 F 208 3.1 169.5 NA 8 4 F 196 0.6 218.2 85 8 4 M 181 10.5 524.3 87.3 9 4 F 236 6.8 NA 106 9 4 F 275 7 485 92.6 9 4 F 254 6.4 433 NA 9 4 F 266 7.4 NA NA 10 10 F 80 6.1 436.1 57.4 10 10 M 86 22.4 247.3 51.1 10 10 M 83 22 249.1 41.4 10 10 M 80 24.4 223 NA 10 10 M 82 23.5 284 NA 10 10 M 90 19.5 282 93 10 10 F 93 11.8 342.5 79 10 10 M 94 24.3 334.4 75.8 10 10 F 95 7.4 283.7 110.8 10 10 F NA 12.7 258.3 77.4 11 5 M 158 9.7 276.2 71.5 11 5 M NA 12.6 NA 74.5 11 5 M 151 9.7 NA NA 11 5 F 142 7.6 201.6 88 11 5 F 161 2.6 307.3 NA 12 5 F 102 6.7 159.5 40.2 12 5 M 100 6.4 233.7 41 12 5 M 103 10.2 300 49.2 12 5 F 95 9.5 499.6 40.5 12 5 F 100 6.2 122.7 40.1 13 9 F 133 14.5 252.9 106.6 13 9 M 114 26.7 358.3 79.9 13 9 F 132 18.1 441.2 116.9 13 9 M 123 25.5 310.7 101.1 13 9 F 119 17.3 260.4 125.2 13 9 M 116 27 345.8 96.6 13 9 F 134 17.7 261.8 NA 13 9 M NA 29.7 181.5 93 13 9 M 128 29.9 307.9 90.8 14 13 M 56 9.6 155.8 58.2 14 13 M 57 8.6 NA 55.7 14 13 F 63 7.7 282.3 79.2 14 13 F 53 4.2 219.5 79.8 14 13 M 65 NA 417.7 71.1 14 13 F 52 0.9 280 72.1 14 13 F 64 5.5 349.4 100.7 14 13 F NA 3.6 321.7 54.4 14 13 M NA 6.2 359.3 90.8 14 13 M 54 10.3 187.4 50.5 14 13 F 63 -0.2 257.8 NA 14 13 M NA 5.9 388 77.1 14 13 F 62 6.9 374.5 45.4 15 4 M 300 NA 494.1 85.4 15 4 M 318 NA 333 144.4 15 4 F 327 16.6 268 135.4 15 4 F 259 8.2 353.9 NA 16 7 M NA 24.6 168 NA 16 7 M 170 NA 392.8 132.6 16 7 M 160 25.4 364.8 101.7 16 7 M NA 24.9 366.1 129.9 16 7 F 184 8.2 256.8 149.1 16 7 F 160 14.9 446.5 108.7 16 7 F 159 11.9 263.2 85.8 17 7 F 75 6.9 228.3 37.5 17 7 M 84 NA 369.5 32.9 17 7 M NA 10.1 337.7 20.4 17 7 M 80 12.7 313.8 43.9 17 7 M 83 16.5 258 66.1 17 7 M 85 18 262.5 33.4 17 7 F 93 8.4 200.3 13.1 18 6 M 93 7 236 17.3 18 6 M 103 13 274.9 37.3 18 6 F 85 5.2 235.1 10.6 18 6 M 90 12.5 323.6 14.8 18 6 F 89 -0.5 287.5 46.9 18 6 M 82 8.2 147.3 -3.6 19 6 F 142 9.2 308.9 61 19 6 M 148 26.5 299.1 75.2 19 6 M 133 24.4 359.2 50.6 19 6 M 140 18 256.9 96.1 19 6 F 137 7.5 647.3 50.7 19 6 M 162 23.9 328.6 66.4 20 3 M 206 9.3 NA 81.1 20 3 M 234 NA 269.9 82.9 20 3 M NA 11.6 405.3 63.3 21 4 F 164 10.3 308.2 60 21 4 M 179 17.8 114.8 18 21 4 M 165 NA 159.2 NA 21 4 F 201 13.2 370 37 22 8 F NA 15.4 NA 151.6 22 8 F 151 14.3 196.8 104.3 22 8 M 141 NA 191.6 106.9 22 8 F 143 15.4 246.3 173.3 22 8 F 142 19.7 351.8 138.6 22 8 M 138 28.1 345.5 61.8 22 8 F 167 NA 198.5 82.1 22 8 F 171 20.5 308 86 23 11 M 133 9.6 427.6 160.3 23 11 F 113 7.6 352.2 141.1 23 11 F 128 1.6 364.5 150.5 23 11 F 137 0.1 339.1 172.6 23 11 M 118 8.8 315.8 167 23 11 F 138 5.7 540.2 154.4 23 11 F 125 4 401.7 138.7 23 11 M 107 10.9 348.2 87.9 23 11 M 131 8.1 433.3 128.2 23 11 M 118 8.5 302.7 125.2 23 11 M 108 14.2 NA 128.2 24 7 M NA 35.3 428.4 NA 24 7 M 207 37 314.2 79.7 24 7 M 177 34.6 298.8 77.4 24 7 M 204 NA 364.8 99.2 24 7 M 190 30.3 224.5 101.9 24 7 M 204 34.1 NA 72.7 24 7 M 214 34.5 261.7 80.1 25 2 F 193 17.8 NA 6.5 25 2 M 202 28 288.3 26.1 For this assignment, use the two Ducks.csv datasets. Main goal: Predict the variables behind   Assignment parts:D1) Using the dataset with nothing missing, build a logistic model of bravery as a function of the other variables (nest size, sex, weight, noise, and brightness). Describe each variable in your model, and the effect they have on bravery score.D2) Use this same model on the MCAR dataset as is (using complete cases only, by default). What, if anything changes between the different summaries?D3) Use the mice() command as found in the “practical imputation” code, and get a pooled estimate model, using the same model as in parts D1 and D2. What, if anything changes between the different summaries?R code that will be used#### DUCKS## Load the .csv files into R.ducks_all = read.csv(“Ducks No Missing.csv”)ducks_mcar = read.csv(“Ducks MCAR.csv”)ducks_all$brave = 1*(ducks_all$bravery > 100)ducks_mcar$brave = 1*(ducks_mcar$bravery > 100)### Build a logistic model of brave or not.mod_all = glm(brave ~ nest_size sex weight brightness noise, data=ducks_all, family=”binomial”)summary(mod_all)mod_mcar = glm(brave ~ nest_size sex weight brightness noise, data=ducks_mcar, family=”binomial”)summary(mod_mcar)#### With imputationlibrary(mice)full_impute = mice(ducks_mcar,m=5,maxit=50,meth=’pmm’,seed=500)ducks_imputed = complete(full_impute,1)mod_imputed = glm(brave ~ nest_size sex weight brightness noise, data=ducks_imputed, family=”binomial”)summary(mod_imputed)mod_pooled = with(full_impute, glm(brave ~ nest_size sex weight brightness noise, family=”binomial”))summary(pool(mod_pooled))

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