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- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?What is the appropriate statistical test to assess whether there is an association between obesity status (normal weight, overweight, obese) and 5-year incident cardiovascular disease (CVD)? Suppose each participant’s obesity status (category) is known along with whether they develop CVD over the next 5 years or not. I see two answers to this question - log rank test and chi-square test of independence. Which is correct?The level of nitrogen oxides (NOX) and nonmethane organic gas (NMOG) in thedusLove uo useful life (150,000 miles of driving) of cars of a particular model varies Normall/ih nean 80 mg/mi and standard deviation 4 mg/mi. A company has 25 cars of this model in its et find the level L such that the probability that the average NOX+NMOG level 7 for the fleet is greater than L is only 0.01. Give your answer to three decimal places.
- Heat flow is the passage of thermal energy from a hot to a cold body. This phenomenon is of particular interest to engineers, who attempt to understand and control the flow of heat through the use of thermal insulation and other devices. The data below were taken from heat flow gauge readings for an industrial process over 10 equally spaced time intervals. A concern is that the process may be cooling down as time progresses. One way to check this statistically is to compare the measurements for the first 5 time periods to the measurements for the last 5 time periods. You may assume that heat flow is approximately normal for each group. Time period 1 (Group 1): 9.273, 9.262, 9.243, 9.283, 9.270Time period 2 (Group 2): 9.240, 9.292, 9.284, 9.279, 9.258 Unless otherwise stated, give your answers to three decimal places. Construct a 95% confidence interval for the difference in mean heat flow. Give your answers to three decimal places. Use t∗=2.352t∗=2.352.( , ) Conduct a hypothesis…The life of an electronic device is known to have the exponential distributionwith parameter lamda=1/1000 .(i) What is the probability that the device lasts more than 1000 hours?(ii) What is the probability it will last less than 1200 hours?(iii) Find the mean and variance of the life of the electronic device.Concentrations of pollutants produced by chemical plants historically are known to exhibit behavior that resembles a lognormal distribution. This is important when one considers issues regarding compliance with government regulations. Suppose it is assumed that the concentration of a certain pollutant, in parts per million, has a lognormal distribution with parameters mean = 3.2 and std. dev. = 1. What is the probability that the concentration exceeds 7.5 parts per million?
- The Weibull distribution is widely used in statistical problems relating to aging of solid insulating materials subjected to aging and stress. Use this distribution as a model for time (in hours) to failure of solid insulating specimens subjected to AC voltage. The values of the parameters depend on the voltage and temperature; suppose a = 2.6 and B = 190. (a) What is the probability that a specimen's lifetime is at most 250? Less than 250? More than 300? (Round your answers to four decimal places.) at most 250 less than 250 more than 300 (b) What is the probability that a specimen's lifetime is between 100 and 250? (Round your answer to four decimal places.) (c) What value is such that exactly 50% of all specimens have lifetimes exceeding that value? (Round your answer to three decimal places.) hrDelivery times for shipments from a central warehouse are exponentially distributed with a mean of 2.64 days. A random sample of 81 shipments are selected and their shipping times are observed. Find the probability that the average shipping time is less than 2.28 days.The Weibull distribution is widely used in statistical problems relating to aging of solid insulating materials subjected to aging and stress. Use this distribution as a model for time (in hours) to failure of solid insulating specimens subjected to AC voltage. The values of the parameters depend on the voltage and temperature; suppose a = 2.2 and B = 220. (a) What is the probability that a specimen's lifetime is at most 250? Less than 250? More than 300? (Round your answers to five decimal places.) at most 250 0.73412 less than 250 0.73412 more than 300 0.13703 (b) What is the probability that a specimen's lifetime is between 100 and 250? (Round your answer to four decimal places.) 0.5723 (c) What value (in hr) is such that exactly 50% of all specimens have lifetimes exceeding that value? (Round your answer to three decimal places.) 186.242 x hr
- The Weibull distribution is widely used in statistical problems relating to aging of solid insulating materials subjected to aging and stress. Use this distribution as a model for time (in hours) to failure of solid insulating specimens subjected to AC voltage. The values of the parameters depend on the voltage and temperature; suppose a = 2.6 and B = 220. (a) What is the probability that a specimen's lifetime is at most 250? Less than 250? More than 300? (Round your answers to five decimal places.) at most 250 less than 250 more than 300 0.7520 0.7520 0.1065 x X X (b) What is the probability that a specimen's lifetime is between 100 and 250? (Round your answer to four decimal places.) 0.6312 (c) What value (in hr) is such that exactly 50% of all specimens have lifetimes exceeding that value? (Round your answer to three decimal places.) 191 XhrA scientist is studying the paramecium, a one-celled organism, under a microscope. There are 1500 paramecia in the slide he is studying, and the standard deviation of their lengths is 0.12mm. He views a sample of 30 paramecia and finds that the mean length of these 30 specimens is 0.25mm. Give the point estimate of the mean length of the entire paramecium population in the slide? (a) (b) Construct a 95% confidence interval for the mean length of the population. (c) State the maximum error for the estimate?The time between ambulance arrivals at the Methodist Hospital emergency room follows an exponential distribution with a mean of 10 minutes. (a) What is the likelihood the next ambulance will arrive in 15 minutes or less? (b) What is the likelihood the next ambulance will arrive in more than 25 minutes? (c) What is the likelihood the next ambulance will arrive in more than 15 minutes but less than 25? (d) Find the 80th percentile for the time between ambulance arrivals. (This means only 20% of the runs are longer than this time.)