Determine if the following validation value is considered within limits for its total error: CV%=3 Mean=4 True Value=2 Standard total allowable error for analyte=7
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Determine if the following validation value is considered within limits for its total error:
CV%=3
True Value=2
Standard total allowable error for analyte=7
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- The EPA recommends avoiding consumption of fish species if the mercury concentration is higher than 0.45 (ug mercury/g uncooked fish). The concentration in a large random sample of marlin was found to be 0.42 ug/g with a margin of error = 0.06 ug/g. Explain whether the EPA should consider marlin a species to avoid for consumption.The drainage loading on a stormwater collection system is normally distributed with mean 1.2 million gallon per day (MGD) and standard deviation 0.4 MGD. Compute the system capacity, i.e., Design Life level (DDL), of the systems with a design life of 15 years and maximum risk of failure of 0.15 over its design lifeTo compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 44 feet. Assume the population standard deviation is 4.9 feet. The mean braking distance for Make B is 46 feet. Assume the population standard deviation is 4.7 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e).
- To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 40 feet. Assume the population standard deviation is 4.8 feet. The mean braking distance for Make B is 43 feet. Assume the population standard deviation is 4.5 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e).To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 41 feet. Assume the population standard deviation is 4.6 feet.The mean braking distance for Make B is 42 feet. Assume the population standard deviation is 4.4 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e). (a) Identify the claim and state Ho and Ha. What is the claim? A.The mean braking distance is different for the two makes of automobiles. This is the correct answer. B.The mean braking distance is the same for the two makes of automobiles. C.The mean braking distance is less for Make A automobiles than Make B automobiles. Your answer is…To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 43 feet. Assume the population standard deviation is 4.6 feet. The mean braking distance for Make B is 47 feet. Assume the population standard deviation is 4.2 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e).
- To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 42 feet. Assume the population standard deviation is 4.5 feet. The mean braking distance for Make B is 46 feet. Assume the population standard deviation is 4.4 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e).To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 43 feet. Assume the population standard deviation is 4.6 feet. The mean braking distance for Make B is 46 feet. Assume the population standard deviation is 4.5 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. The critical value(s) is/are Find the standardized test statistic z for μ1−μ2.To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 43 feet. Assume the population standard deviation is 4.7 feet. The mean braking distance for Make B is 44feet. Assume the population standard deviation is 4.5 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e). a) identify the claim and state Ho and Ha b) find the critical values and identify the rejection regions c) Find the standardized test statistic z d) Decide whether to reject or fail to reject the null hypothesis. e) Interpret the decision in the context of the original claim.
- Karen was working the day shift in the hematology laboratory. The laboratory’s protocol called for three levels of blood cell controls to be run at the following times: (1) at the beginning of the shift, (2) within each run of patient samples during the day, and (3) any time reagents were changed. The mean for the low (abnormal) control for the red blood cell count was given as 2.00 3 1012/L, the standard deviation was 0.15, and the confidence limit (acceptable control range) was 2.00 3 1012/L 6 2 s (or 6 0.3).The first morning low control result was 2.10 (3 1012/L). In five subsequent runs, the low control re-sults were 2.16, 2.19, 2.20, 2.22, and 2.25. 1.These values represent: a shift b.a trend c.neither shift nor trend 2.Should Karen be concerned about these values? Explain. 3.does Karen need to take any action?Please show complete solutions. Will upvote, thank you.A product is designed to have length of 14cm+/0.12cm. the output of the manufacturing process is identified to be centered at 14.0.042cm and the standard deviation is estimated at 0.014cm. determine the capability of the system Cp