Get college assignment help at uniessay writers The thickness of a wood paneling (in inches) that a customer orders is a random variable with the following cumulative distribution function:
The playing time X of classical CDs has the normal distribution with a mean of 54 and a standard deviation of 5; the N(54, 5) distribution. What is the relative frequency of classical CDs with a playing time of X less than 49 minutes? That is, find the relative frequency of the event X < 49. (2 points)
The proportion of parents with children under the age of 6 who put their children in car seats is 0.42. Suppose 49 parents with children under the age of 6 are randomly selected. What is the probability that the majority of the selected parents put their children who are under the age of 6 in car seats?
True or False, Fixed alternative questions may tempt respondents to check an answer that is untrue.
The waiting time for an individual to be served in a cafeteria is a random variable haiving an exponential distribution witha a mean value of 4 minutes. What is the probability that you will be served in less than three minutes on 4 of the next 6 days
Calculate the profit earned/loss incurred on; a high performance tire that exceeds 40,000 miles, a high performance tire that does not exceed 40,000 miles, an all weather tire that exceeds 40,000 miles, and an all weather tire that fails to last 40,000 miles.
According to a study by Decision Analyst, 21% of the people who have credit cards are very close to the total limit on the card(s). Suppose a random sample of 600 credit card users is taken. What is the probability that more than 150 credit card users are very close to the total limit on the card(s)
n the Happy Hilltop Health Home, 55% of the residents play shuffleboard, 55% of the residents play poker, and 80% of the residents garden. If 35% of the residents play poker and garden and 45% of the residents play both shuffleboard and poker, then find the probability that a resident plays poker, given that they garden.
The topic cannot be similar to the exmple given below. Research statistical data in a business context that requires a decision. Use probability concepts to formulate a decision. ??Write a 700- to 1,050-word paper, explaining your research methods and process for limiting the uncertainty in the decision. ??Address the following in your paper: o Include how you applied concepts to formulate your decision. o Include appropriate probability concepts and your application to find resulting data to limit uncertainty in this decision. o Identify each outcome from your statistical analysis, providing rationale for each. o Identify tradeoffs between accuracy and precision required by various probability concepts and the effect on your data. o Include the decision you made based on statistical data. ??Format your paper consistent with APA guidelines. I need references and citations and I need it by 4/27 at 5pm. Thanks. Example question: Student road map This Road Map will help you become familiar with the expectations of this assignment and provide some direction on how to structure it. This material is an example only, as you must research statistical data to help make a business decision. The concepts that follow focus on a personal decision of uncertainty. Use these probability concepts to help guide you in structuring your assignment. Remember to present your paper as a narrative. Assignment: A Decision of Uncertainty Research statistical data within a business context that requires a decision to be made. Then, use probability on your researched data to formulate a decision. Write a 700- to 1,050-word paper in APA format explaining your research methods and process for limiting the uncertainty within the decision. Discuss your results in an in-depth narrative. Be sure to explain the following in your paper: o How you applied the concepts from the example scenario to formulate your business decision of uncertainty. o The appropriate probability concepts and your application of them to find resulting data to limit the uncertainty within this business decision. o Identification of each discrete outcome from your statistical analysis, providing statistical rationale for each. o The trade-offs between accuracy and precision required by the use of various probability concepts, and the effect on your data. Example Scenario Decision: To buy or not to buy cruise insurance I decided to take a cruise this year. However, due to money and work constraints, the cruise was to be taken during the month of October. Through my research and compliance with my constraints, the most opportune time to travel on a cruise was during the week of October 8 – 14. However, according to the weather bureau, this particular week was the height of hurricane season. According to the cruise line, if a cruise is cancelled due to a hurricane there is no refund. However, for a 30% fee hurricane insurance can be purchased to ensure one can expect their money back if the cruise is cancelled, except for the fee of course. I have to decide whether to book the cruise and not worry about hurricanes; thus risk losing my vacation fund, or book the cruise and pay extra for the hurricane insurance, which subsequently adds more to my spending and stresses the allocated budget for this vacation. Research To make an accurate decision, I researched my trip. My researched data set was from the National Oceanographic and Atmospheric Administration (NOAA) and consisted of weather condition statistics over the past 10 years. More importantly, my research specified the date and duration of hurricanes. Since my trip was to take place during the week of October 8 – 14, my research primarily concentrated on this time frame. Once the research was gathered, I focused on accurately interpreting my data to make an accurate decision. Interpretation of Data (using Bayes’ Theorem) To interpret my data, I chose to use Bayes’ theorem as the probability model that was the most applicable to my vacation decision. Bayes’ theorem emulates the process of logical inference by determining the degree of confidence in possible conclusions based on the available evidence. This evidence is best stated in terms of subjective probability, where the probability is based on evaluating opinions and information, then estimating this data and finally assigning probability to the outcomes. Therefore, Bayes’ theorem is best used for the purposes of predicting confidence levels for purchasing hurricane insurance, predicting the occurrence of a hurricane, and or predicting a captain’s cancellation notice if there is said hurricane. While there are other effective analytical tools used to derive the probability of data, i.e. hypothesis testing, Bayes’ theorem is more appropriate for this situation based on the subjective nature of the evidence. Part of statistical modeling is using the right analytical tool for the appropriate situation. Hypothesis testing is more effective for a scenario with an observed difference. In other words, hypothesis testing is used to determine the probability when a given hypothesis is true. In our cruise scenario, for example, hypothesis testing could be used if one professional body said the probability of a hurricane being present is .5, while another body stated that the probability of a hurricane being present is .35. Since our variables are not defined, it is more effective to use Bayes’ theorem. With the appropriate theorem chosen, I continued to gather my data. After contacting the cruise line, I found out that 5 % of Caribbean cruises during hurricane season are cancelled by harsh weather conditions. I then set up the variables to examine the probability of. Cruise 1 = C1 = cancelled by hurricane Cruise 2 = C2 = not cancelled by hurricane In turn, this helped me decide whether I should buy the hurricane insurance. This is what I knew: the dates of the cruise are already determined (October 8 – 14) the probability of our cruise being canceled by a hurricane is 5%; (P(C1) = cancelled by hurricane = .05). So, prior probability of a cruise not being affected is P(C2) = .95 The weather bureau’s historical evidence cross-referenced with the cruise line’s schedule (October 8 – 14) showed that if there is a hurricane in the area there was a 90% chance the cruise would be cancelled. In other words, B = hurricane is present (as indicated by the weather bureau). This is written as P(B|C1) = .90. The cruise line additionally stated that even though a hurricane may surface, cancellation is not always imminent. Cancellation also depends on the subjective nature of the captain’s opinion. The probability of the cruise being not being cancelled due to bad weather is .15, or written as P(B|C2) is .15. Posterior probability according to Bayes’ shows us: P(C1/B) = P(C1)P(B|C1) _________________________ P(C1)P(B|C1) P(C2)P(B|C2) = (.5)(.90) = .0450 = .24 ________________ _______ (.5)(.90) (.95)(.15) .1875 Based on the calculations, the data illustrates the probability that the cruise will be cancelled at .24, provided that the weather bureau positively identifies a hurricane in the area. The cruise line stated that if a cruise is selected at random during hurricane season, the probability that it will be cancelled is .05. Now, if the weather service states a hurricane is in the area, the probability for cancellation rises from .05 to .24 It is important to the data into a table to check for accuracy and help determine what decision to make. Event Prior Probability P(Ci) Conditional Probability P(B|Ci) Joint Probability P(Ai and B) Posterior Probability P(Ai|B) Cruise Cancelled .05 .90 .0450 .0450/.1875 = .24 Cruise not Cancelled .95 .15 .1425 .1425/.1875 = .76 P(B) = .1875 = 1.00 Based on the above calculations, there is a .24 probability that the cruise will be cancelled and a .76 probability that the cruise will go as planned. Decision All of our decisions involve risk and our own personal tolerance for risk. Statistical tools for analyzing data give us a means of minimizing that risk. Based on the above analysis of available data, what would you do? Would you book the cruise, not worry about hurricanes, and thus risk losing your vacation fund? Or, would you book the cruise and pay extra for the hurricane insurance, which subsequently adds more to your spending and stresses the allocated budget for this vacation?
X and Y are discrete random variables each taking only two distinct values. Suppose X and Y are uncorrelated. Are they independent?
Get college assignment help at uniessay writers You roll a fair six sided die, and then you flip a fair coin the number of times shown by the die. Find the expected value of the number of heads obtained.
Suppose X and Y are independent discrete random variables having the Poisson distribution with parameters lambda1 and lambda2 respectively. Let Z=X Y. Calculate E[X׀Z].
After a one hour stand off, what is the likelihood(precentage) that the negotiation will end successfully? After 4 hours? After 8 hours? How does the precentage likelihood of a successful negotiation change over the course of time?
a random sample of 200 married men,all retired,were classified according to education and number of children
The following data represent the actual amount of soda in a sample of fifty 2-liter bottles. You are in charge of production and must assure that the bottles don’t have too much or too little in them. At the 0.05 level of significance, is there evidence to suggest that the mean amount of soda filled is different from 2.0 liters? Q-1a: State the null hypothesis. Q-1b: State the alternate hypothesis. Q-1c: Perform the hypothesis test and state your conclusions and evidence. Suppose you didn’t care if the bottles had too much, you only cared if the quantity in the bottles was less than 2.0 liters. Q-1d: State the new null hypothesis. Q-1e: State the new alternative hypothesis. Q-1f: Perform the hypothesis test and state your conclusions and evidence. Amount 1.973 1.996 2.109 1.957 1.941 1.981 2.012 1.894 1.969 2.086 1.999 2.014 2.029 1.966 2.052 1.938 1.963 1.992 2.010 2.015 2.005 2.031 1.951 1.951 2.023 2.038 2.075 1.967 2.003 1.971 1.997 2.012 2.065 1.941 2.012 2.057 1.908 2.025 1.994 2.036 2.066 1.984 1.986 2.020 2.044 2.013 2.014 1.975 1.947 2.029 Late payment of medical claims can add to the cost of health care. The auditing firm of Dewey, Cheatham, and Howe has discovered that for one insurance company, 85.1% of the claims were paid in full when first submitted based on a sample of 200 claims. Suppose that the insurance company developed a new payment system in an effort to increase this percentage. A sample of 200 claims processed under this new system revealed that 180 of the claims were paid in full when first submitted. At the 5% level of significance, is there evidence that the population proportion of claims paid in full under this new system is higher than the proportion of claims paid in full under the old system? Q-2a: State the null hypothesis Q-2b: State the alternative hypothesis. Q-2c: Perform the hypothesis test and state your conclusions and evidence.
A social service agency plans to conduct a survey to determine the mean income of its clients. The director of the agency prefers that you measure the mean income very accurately, to within plus or minus $500. From a sample taken two years ago, you estimate that the standard deviation of income for this populatation is about $5,000. You job is to figure out the necessary sample size to reduce sampling error to plus or minus $500. a. do you need to have an estimate of the current mean income to answer this question? why or why not?
A random sample of 64 households was selected in Corona, California and it was found that the mean expenditure per week on toothpaste was $6.15. The standard deviation of the sample was $1.30. Calculate: a. The 95 percent Confidence Interval for the mean household expenditure on toothpaste for the entire ‘population’ of households in Corona; and b. The 99 percent Confidence Interval for the mean household expenditure on toothpaste for the entire ‘population’ of households in Corona.
A recent study focused on the number of times men and women who live alone buy take-out dinner in a month. The information is summarized below. Statistic Men Women Sample mean 24.51 22.69 Population standard deviation 4.48 3.86 Sample size 35 40 At the .01 significance level, is there a difference in the mean number of times men and women order take-out dinners in a month? What is the p-value?
What is the most appropriate situation for the z-test?
To do so you randomly surveyed 1000 men and 1200 women. 100 men responded that they were members of the Tea Party. 95 women responded that they were members of the Tea Party. What is the p-value for this test? (round to 4 decimal places when possible
a literature professor decides to give a 20-question true-false quiz to determine who has read an assigned novel. she wants to choose the passing grade such that the probability of passing a student ho guesses on every question is less than .05. what score shoud she set as the lowest passing grade?
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