The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary: Coefficients: Estimate Std. Error -92.040 16.706 0.710 0.041 (Intercept) Length Using this information, give the equation of the least squares regression line. t value Pr(> t) -5.509 0.000 17.275 0.000
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find the least squares regression line equation from the given data.
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- The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary: Coefficients: Estimate Std. Error t value Pr(> |t|) (Intercept) −89.010 16.720 −5.324 0.000 Length 0.704 0.049 14.333 0.000 Using this information, give the equation of the least squares regression line.The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420)) gave the accompanying data on y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Use the following statistics to give the equation of the least squares regression line.x = 524.800, y = 303.660, sx = 14.429, sy = 11.200, r = 0.9662 a) ŷ = 1.245x − 89.940 b) ŷ = 0.750x − 89.940 c) ŷ = -89.940x + 0.750 d) ŷ = 1.245x + 89.940 e) ŷ = 0.750x + 89.940 f) None of the aboveThe decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on 10 values for the data sets where y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary: Coefficients: Estimate Std. Error t value Pr(> |t|) (Intercept) −89.010 16.703 −5.329 0.000 Length 0.705 0.046 15.293 0.000 Using this information, compute a 95% confidence interval for the slope. Assume that we have normal distribution and choose the resulting interval. a) [0.356, −54.814] b) [−121.749, −56.271] c) [0.611, 0.799] d) [−122.951, −55.069] e)…
- The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on 10 values for the data sets where y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary: Coefficients: Estimate Std. Error t value Pr(> |t|) (Intercept) −89.010 16.703 −5.329 0.000 Length 0.705 0.046 15.293 0.000 Using this information, compute a 95% confidence interval for the slope. a) [0.356, −54.814] b) [−121.749, −56.271] c) [0.611, 0.799] d) [−122.951, −55.069] e) [0.629, 0.781]The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on 10 values for the data sets where y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary: Coefficients: Estimate Std. Error t value Pr(> |t|) (Intercept) −90.020 16.702 −5.390 0.000 Length 0.705 0.049 14.358 0.000 Using this information, compute a 95% confidence interval for the slope.1. (Prob. 11-12, p. 438) An article in the Journal of Environmental Engineering (1989, Vol. 115(3), pp. 608–619) reported the results of a study on the occurrence of sodium and chloride in surface streams in central Rhode Island. The following data are chloride concentration y (in milligrams per liter) and roadway area in the watershed x (in percentage). y 4.4 6.6 9.7 10.6 10.8 10.9 0.19 0.15 0.57 0.70 0.67 0.63 y 11.8 12.1 14.3 14.7 15.0 17.3 0.47 0.70 0.60 0.78 0.81 0.78 y 19.2 23.1 27.4 27.7 31.8 39.5 0.69 1.30 1.05 1.06 1.74 1.62 a. Draw a scatter diagram of the data. Does a simple linear regression model seem appropriate here? b. Fit the simple linear regression model using the method of least squares. Find an estimate of o?. C. Estimate the mean chloride concentration for a watershed that has 1% roadway area. d. Find the fitted value corresponding to x = 0.47 and the associated residual.
- The article "Modeling of Urban Area Stop-and-Go Traffic Noise" (P. Pamanikabud and C. Tharasawatipipat, Journal of Transportation Engineering, 1999:152–159) presents measurements of traffic noise, in dBA, from 10 locations in Bangkok, Thailand. Measurements, presented in the following table, were made at each location, in both the acceleration and deceleration lanes. Location Acceleration Deceleration 78.1 78.6 78.1 80.0 3 79.6 79.3 4 81.0 79.1 78.7 78.2 78.1 78.0 78.6 78.6 78.5 78.8 78.4 78.0 10 79.6 78.4 Can you conclude that there is a difference in the mean noise levels between acceleration and deceleration lanes?The article "Estimating Population Abundance in Plant Species with Dormant Life-Stages: Fire and the Endangered Plant Grevillea caleye R Br." (T. Auld and J. Scott, Ecological Management and Restoration, 2004:125-129) presents estimates of population sizes of a certain rare shrub in areas burnt by fire. The following table presents population counts and areas (in m?) for several patches containing the plant. Агеа 3739 Population 3015 5277 1847 400 17 345 392 142 40 7000 2521 213 11958 1200 2878 707 113 1392 157 12000 10880 711 74 2259 223 81 15 33 18 1254 1320 229 351 1000 92 841 1720 1500 300 228 31 228 17 10 Compute the least-squares line for predicting population (y) from area (x). Б. a. Plot the residuals versus the fitted values. Does the model seem appropriate? Compute the least-squares line for predicting In y from In x. Plot the residuals versus the fitted values. Does the model seem appropriate? Using the more appropriate model, construct a 95% prediction interval for the…The depth of wetting of a soil is the depth to which water content will increase owing to extemal factors. The article "Discussion of Method for Evaluation of Depth of Wetting in Residential Areas" (J. Nelson, K. Chao, and D. Overton, Journal of Geotechnical and Geoenvironmental Engineering, 2011:293-296) discusses the relationship between depth of wetting beneath a structure and the age of the structure. The article presents measurements of depth of wetting, in meters, and the ages, in years, of 21 houses, as shown in the following table. Age Depth 7.6 4 4.6 6.1 9.1 3 4.3 7.3 5.2 10.4 15.5 5.8 10.7 4 5.5 6.1 10.7 10.4 4.6 7.0 6.1 14 16.8 10 9.1 8.8 Compute the least-squares line for predicting depth of wetting (y) from age (x). b. Identify a point with an unusually large x-value. Compute the least-squares line that results from deletion of this point. Identify another point which can be classified as an outlier. Compute the least-squares line that results from deletion of the outlier,…
- Foot ulcers are a common problem for people with diabetes. Higher skin temperatures on the foot indicate an increased risk of ulcers. The article "An Intelligent Insole for Diabetic Patients with the Loss of Protective Sensation" (Kimberly Anderson, M.S. Thesis, Colorado School of Mines), reports measurements of temperatures, in °F, of both feet for 181 diabetic patients. The results are presented in the following table. Left Foot Right Foot 80 80 85 85 75 80 88 86 89 87 87 82 78 78 88 89 89 90 76 81 89 86 87 82 78 78 80 81 87 82 86 85 76 80 88 89 Construct a scatterplot of the right foot temperature (y) versus the left foot temperature (x). Verify that a linear model is appropriate. b. Compute the least-squares line for predicting the right foot temperature from the left foot temperature. If the left foot temperatures of two patients differ by 2 degrees, by how much would you predict their right foot temperatures to differ? Predict the right foot temperature for a patient whose left…During the spring of 1999, many fuel storage facilities in Serbia were destroyed by bombing. As a result, significant quantities of oil products were spilled and burned,resulting in soil pollution. The article “Mobility of Heavy Metals Originating from Bombing of Industrial Sites” (B. Škrbić, J. Novaković, and N. Miljević, Journal of Environmental Science and Health, 2002:7–16) reports measurements of heavy metal concentrations at several industrial sites in June 1999, just after the bombing, and again in March of 2000. At the Smederevo site, on the banks of the Danube River, eight soil specimens taken in 1999 had an average lead concentration (in mg/kg) of 10.7 with a standard deviation of 3.3. Four specimens taken in 2000 had an average lead concentration of 33.8 with a standard deviation of 0.50. Find a 95% confidence interval for the increase in lead concentration between June 1999 and March 2000.The article "Characteristics and Trends of River Discharge into Hudson, James, and Ungava Bays, 1964-2000" (S. Dery, M. Stieglitz, et al., Journal of Climate, 2005:2540-2557) presents measurements of discharge rate x (in kmlyr) andpeakflow y (in m/s) for 42 rivers that drain into the Hudson, James, and Ungava Bays. The data are shown in the following table: Discharge Peak Flow 94.24 4110.3 66.57 4961.7 59.79 10275.5 48.52 6616.9 40.00 7459.5 32.30 2784.4 31.20 3266.7 30.69 4368.7 26.65 1328.5 22.75 4437.6 21.20 1983.0 20.57 1320.1 19.77 1735.7 18.62 1944.1 17.96 3420.2 17.84 2655.3 16.06 3470.3 1561.6 14.69 11.63 869.8 11.19 936.8 11.08 1315.7 10.92 1727.1 9.94 768.1 7.86 483.3