What is the likelihood, based on historical data and current trends, that a randomly selected individual, born in the last decade, will live to be at least 100 years old, given advancements in healthcare, improved quality of life, and an overall increase in life expectancy across various regions and demographics?
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- The index of leading economic indicators, compiled and published by the U.S. National Bureau of Economic Research, is composed of 12 time series, such as the average work hours of production in manufacturing, manufacturers’ new orders, and money supply. This index and similar indexes are designed to move up or down before the economy begins to move the same way. Thus, an economist has statistical evidence to forecast future trends.You want to construct a leading indicator for Erie County in upstate New York. The index is to be based on 2000 data. Because of the time and work involved, you decide to use only four time series. As an experiment, you select these four series: unemployment in the county, a composite index of county stock prices, the County Price Index, and retail sales. Here are the figures for 2000 and 2018. The weights you assign are unemployment rate 20%, stock prices 40%, County Price Index 25%, and retail sales 15%. (Round your answers to 1 decimal place.) a. Using….A new, miracle diabetes drug that diminishes major symptoms of diabetes has been approved by the FDA. Health care professionals and researchers believe that the new drug will prolong lifespan of diabetes patients. If the population is in steady state and the incidence is constant, what will the effect of this new drug be on the prevalence of diabetes in the population? Explain.Product failure behavior. An article in Hotwire (Dec. 2002) discussed the length of time till failure of a product pro- duced at Hewlett-Packard. At the end of the product’s life- time, the time till failure is modeled using an exponential distribution with mean 500 thousand hours. In reliability jargon, this is known as the “wear-out” distribution for the product. During its normal (useful) life, assume the prod- uct’s time till failure is uniformly distributed over the range 100 thousand to 1 million hours. a. At the end of the product’s lifetime, find the probability that the product fails before 700 thousand hours. b. During its normal (useful) life, find the probability that the product fails before 700 thousand hours. c. Show that the probability of the product failing before 830 thousand hours is approximately the same for both the normal (useful) life distribution and the wear-out distribution
- We state that the battery of a type of pos device shows an exponential distribution with an average life span of five years in standard use. What is the probability that a user who uses the POS device for three years without battery problem will encounter a battery problem within the next year?Errors in age reporting, particularly under reporting of children aged less than one is a serious error with far reaching implications. Evaluate any three major ways in which statistical agencies can contribute to and worsen this problem.Read the following passage and observe the word length of each word. Make a frequency distribution of word length. Pargraph: “Statistics play an intrinsic role in computer science and vice versa. Statistics is used for data mining, speech recognition, vision and image analysis, data compression, artificial intelligence, and network and traffic modeling. A statistical background is essential for understanding algorithms and statistical properties that form the backbone of computer science. Typically, statistical approach to models tends to involve stochastic (random) models with prior knowledge of the data. The computer science approach, on the other hand, leans more to algorithmic models without prior knowledge of the data. Ultimately, these come together in attempts to solve problems.” Note table should neat and clean
- In a population-based cohort study, an entire community was interviewed regarding smoking habits and then followed for one year. Upon ascertainment of all lung cancer deaths, the investigator obtained the following data: Number of Individuals Lung Cancer Deaths Smokers 24,500 15 Nonsmokers 10,500 2 Calculate the risk difference per 100,000 per year. Round to the tenth decimaThe National Center for Health Statistics (NICH) published a report entitled Health, Pakistan, containing extensive information on major trends in the health of Pakistanis. Data are provided for the Pak population as a whole and for specific ages, sexes and races. The NICH report indicated that in 2012 Pakistanis paid an average of Rs.3,302 per month on health care and prescription drugs. An investigator hypothesizes that in 2015 expenditures have increases primarily due to the availability of generic drugs. To test the hypothesis, samples of 100 Pakistanis are selected and their expenditures on health care and prescription drugs in 2015 are measured. The sample data are summarized as follows: n=100, R =Rs3,390 and s=Rs890. Is there statistical evidence of increased in expenditures on health care and prescription drugs in 2015? Is the sample mean of Rs.3,390 evidence of a true increase in the mean or is it within chance fluctuation?If arrivals occur at a mean rate of 2.6 events per minute the exponential probability of waiting more than 1.5 minutes for the next arrival is is a .0202 or .0122 or .0535 or .2564
- Q.No.1. Read the following passage and observe the word length of each word. Make a frequency distribution of word length. "Statistics play an intrinsic role in computer science and vice versa. Statistics is used for data mining, speech recognition, vision and image analysis, data compression, artificial intelligence, and network and traffic modeling. A statistical background is essential for understanding algorithms and statistical properties that form the backbone of computer science. Typically, statistical approach to models tends to involve stochastic (random) models with prior knowledge of the data. The computer science approach, on the other hand, leans more to algorithmic models without prior knowledge of the data. Ultimately, these come together in attempts to solve problems."c and d pleaseSuppose that, for one semester, you can collect the following data on a random sample of college juniors and seniors for each class taken: a standardised final exam score, percentage of lectures attended, a dummy variable indicating whether the class is within the student’s major, cumulative grade point average prior to the start of the semester, and SAT score. If you pool all of the data and use OLS, what are you assuming about unobserved student characteristics that affect performance and attendance rate and What roles do SAT score and prior GPA play in this regard?