A study by Bechtel et al., 2009, described in the Archives of Environmental & Occupational Health considered polycyclic arom hydrocarbons and immune system function in beef cattle. Some cattle were near major oil and gas-producing areas of western Canada. mean monthly exposure to PM1.0 (particulate matter that is <1 μm in diameter) was approximately 7.2 μg/m³ with standard deviation Assume that the monthly exposure is normally distributed. What is the probability of a monthly exposure greater than 9 µg/m³ ? Ro your answer to three decimal places (e.g., 98.765).
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- The mean alkalinity level of water specimens collected from the Han River in Seoul, Korea, is 50 milligrams per liter. (Environmental Science & Engineering, September 1, 2000.) Consider a random sample of 100 water specimens collected from a tributary of the Han River. Suppose the mean and standard deviation of the alkalinity levels for the sample are Xbar= 67.8 mg/L and s = 14.4 mg/L. Is there sufficient evidence to indicate that the population mean alkalinity level of water in the tributary exceeds 50 mg/L? Use significance level 0.05 a. State the null and alternate hypothesis b. Calculate the test statistic c. Calculate the p-value d. Do you reject the null hypothesis or fail to reject the null hypothesis. e. Write your conclusionThe article “Tibiofemoral Cartilage Thickness Distribution and its Correlation with Anthropometric Variables” (A. Connolly, D. FitzPatrick, et al., Journal of Engineering in Medicine, 2008:29–39) reports that in a sample of 11 men, the average volume of femoral cartilage (located in the knee) was 18.7 cm3 with a standard deviation of 3.3 cm3 and the average volume in a sample of 9 women was 11.2 cm3 with a standard deviation of 2.4 cm2. Find a 95% confidence interval for the difference in mean femoral cartilage volume between men and women.An investigation of the relationship between traffic flow (measured in cars per day) and lead content (measured in micrograms per gram of dry weight) in the bark of trees near the highway yielded the following summary statistics: Sample Mean Sample Standard Deviation Lead Content (micrograms per gram dry weight) y¯=y¯= 680 sysy = 240 Traffic Flow (cars / day) x¯=x¯= 1750 sxsx = 800 The correlation between lead content and traffic flow was found to be r = 0.6 and a scatterplot showed the form to be linear. The least squares regression line for using X to predict Y was found to be y^=365+0.18xy^=365+0.18x. Which one of the following is a proper interpretation of the slope? Group of answer choices For each 1 car per day increase in traffic flow, we predict an corresponding increase of 0.18 in lead content of surrounding trees For each 0.6 car per day increase in traffic flow, we predict an corresponding increase of 365.18 in lead content of surrounding trees For each 1…
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- The antibody production of 12 male red-winged blackbirds before and after receiving testosterone implants was compared. The units for antibody levels were natural log (10-3 optical density) per minute (In(mOD/min)). The mean change in antibody production was d = 0.056, and the standard deviation was sd = 0.225 If you were assigned the task of repeating this experiment, and wanted to ensure that you could detect a mean change of 0.02 units with a probability of 0.8, then what sample size would you use? Since we are calculating n for a study of individuals, answers should be rounded up to the next whole number.You wish to determine the average VO2max (maximum rate of oxygen consumption, often associated with athletic performance) of a sample of 100 Olympic athletes, and to use a quantitative metric to assess your confidence in the average (mean) value. You calculate a mean of 71 ml/kg/min and a variance of 26.06 from your sample. Question: What are the standard error of the mean (SEM) and the approximate 95% CI of the mean?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 life