Visualize that two tributaries A and B at their confluence form a river C. Statistical properties of flow data for tributaries A and B indicate that tributary A has a yearly discharge rate smaller than its
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- Mercury is a persistent and dispersive environmental contaminant found in many ecosystems around the world. When released as an industrial by-product, it often finds its way into aquatic systems where it can have deleterious effects on various avian and aquatic species. The accompanying data on blood mercury concentration (µg/g) for adult females near contaminated rivers in a state was read from a graph in an article. 0.20 0.23 0.24 0.30 0.35 0.41 0.54 0.57 1.43 1.70 1.82 2.20 2.24 3.08 3.24 (a) Determine the values of the sample mean and sample median. Hint: xi = 18.55. (Round your answers to four decimal places.) x== Explain why they are different. The sample mean and sample median are never equal.They aren't different since the data is symmetric. There is heavy negative skewness in the data.There are an odd number of data values.There is heavy positive skewness in the data. (b) Determine the value of the 10% trimmed mean.…arrow_forwardThe number of interal disk drives (in million) made at a plant in Taiwan during the past 5 years follows: Year Disk drives 1 142 2 156 3 184 4 204 5 210 a) Using simple linear regression the forecast for the number of disk drives to be made next year= [__] disk drives (round your response to one decimal place)arrow_forwardFor a sample of 10 individuals, a researcher calculates residuals for the relationship between “number of delinquent friends” and “number of prior arrests” and finds that the positive residuals = 125. The researcher then collects a second sample of 10 individuals and calculates the residuals on the same two variables and discovers the sum of the positive residuals = 75. What can you conclude about the strength of the relationship between “number of delinquent peers” and “number of prior arrests” across these two random samples? How are they similar/different?arrow_forward
- Show all workings. Fill in the missing values ‘*’, ‘**’, and ‘***' Test whether age is significantarrow_forwardA population has = 60 and = 10. Find the z-score corresponding to each of the following sample means: A sample of n = 4 with M = 55 A sample of n = 25 with M = 55 A sample of n = 100 with M = 55 What do we notice about the z-scores as the sample size changesarrow_forwardA researcher wants to investigate the relationship between the hours a student spends studying for a test and the score on the test. The following data is gathered: Hours (x) 20 16 34 23 27 32 18 22 Score (y) 6.5 8.5 7 9.5 7.5 8 Annual (X-X) salary, $1000 Years of (Y-Y) (X-X)(Y-Ÿ) (X-X)? (Y-7)² schooling 20 6.5 -4 -1.25 16 1.5625 16 6. -8 -1.75 14 64 3.0625 34 8.5 10 0.75 7.5 100 0.5625 23 7 -1 -0.75 0.75 1 0.5625 27 3 1.25 3.75 9. 1.5625 32 9.5 8. 1.75 14 64 3.0625 18 7.5 -6 -0.25 1.5 36 0.0625 22 8 -2 0.25 -0.5 4 0.0625 192 62 46 294 10.5 Calculate: a. The regression line of y based on x. b. The estimated test score for a person who studied 28 hours.arrow_forward
- 10) The following results are from a regression where the dependent variable is COST OF COLLEGE and the independent variables are TYPE OF SCHOOL which is a dummy variable = 0 for public schools and = 1 for private schools, FIRST QUARTILE SAT which is the average score of students in the top quartile of SAT’s, THIRD QUARTILE SAT which is the average score of students in the 3rd quartile, and ROOM AND BOARD which is the cost of room and board at the school. The first set of results includes all the independent variables whereas the second set of results excludes the THIRD QUARTILE SAT variable. a) Based on these two sets of data, does there appear that multicollinearity is a problem (specifically, does it appear that THIRD QUARTILE SAT is highly collinear with the other independent variables? Explain. b) Calculate the VIF for THIRD QUARTILE SAT. c) Based on the VIF, do you think that multicollinearity is a problem? Explain.arrow_forwardA doctor notes the variables listed in the following table from every patient before admitting in his hospital. Which of the following variables are qualitative and which are quantitative? Which qualitative variables are nominal or ordinal? Which quantitative variables are discrete or continuous? ( 1 ) Gender (Male or Female) ( 2 ) Weight (lbs) ( 3 ) Phone Number ( 4 ) Height (cm) ( 5 ) Marital Status (Single, Married, Divorce, Widow) ( 6 ) Systolic Blood Pressure (mm of pressure) ( 7 ) Temperature (degree F) ( 8 ) Level of Calcium (microgram/milimeter) ( 9 ) Family of Income ( Amount) ( 10 ) Wihte Blood Cellsarrow_forward4. /13. Show that mean deviation about mean isarrow_forward
- A First Course in Probability (10th Edition)ProbabilityISBN:9780134753119Author:Sheldon RossPublisher:PEARSON