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Arsenic in groundwater. Refer to the Environmental Science & Technology (Jan. 2005) study of the reliability of a commercial kit to test for arsenic in groundwater, Exercise 12.16. (p. 701). You fit a first-order model for arsenic level (y) as a
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- More cereal Exercise 1 describes a regression model thatestimates a cereal’s potassium content from the amountof fiber it contains. In this context, what does it mean tosay that a cereal has a negative residual?arrow_forwardHow does the fuel consumption of a car change as its speed increases? The table presents data for a 2014 Chevrolet Cruze Turbo Diesel. Speed is measured in miles per hour, and fuel consumption is measured in miles per gallon. Speed 10 20 30 40 50 60 70 80 Fuel 38.1 54.0 68.4 63.6 60.5 55.4 50.6 43.8 Is there significant evidence of straight‑line dependence between speed and fuel use? What is the value of the t-statistic for testing: -1.4 0.628 0.395 -0.14 What are hypotheses and the P-value for the test? Which conclusion seems most justified? - There is little evidence of a straight line dependence between speed and fuel use. - There is significant evidence against a straight line dependence between speed and fuel use. - There is strong evidence that there is a positive correlation between speed and fuel use. - There is some evidence that there is a negative correlation between speed and fuel use. Make a scatterplot and use it to explain the result of your…arrow_forwardThe electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature ( x1 ), the number of days in the month ( x2 ), the average product purity ( x3 ), and the tons of product produced ( x4 ). The past year’s historical data are available and are presented in the following table:regression model is y = -102.7132 + 0.6054X1 + 8.9236X2 + 1.4374 X3 + 0.0136X4 a) Estimate sigma^2b.) Using ANOVA, test for significance of regression using α=0.05. Determine the critical value of the test statistic (2 decimal places only). c.) Using ANOVA, test for significance of regression using α=0.05. Determine the computed value of the test statistic d) Calculate R^2 for the computed regression model. Express your answer as a number less than 1 (NOT in %). e) Calculate R_adj^2 for the computed regression model. Express your answer as a number less than 1 (NOT in %).f) Test the significance of x3 at α=0.05. Determine the value of the test statistic. g)…arrow_forward
- 7.1 What is a join hypothesis? What is the hypothesis that is being tested by constructing the overall regression F-statistic in the multiple regression model? 7.3 What is a control variable and how does it differ from the variable of interest? Do coefficients on control variables measure causal effect? 8.3 How is the slope coefficient interpreted in a log-linear model, where the dependent variable is in a logarithm form but the independent variable is not? In a linear-log model? In a log-log model? 9.1 Explain the difference between internal validity and external validity. Is it possible for an econometric study to have internal but not external validity? 9.3 What is the effect of measurement error in Y? How is it different from the effect of measurement error in X? 9.4 What is sample selection bias?arrow_forwardSnowpacks contain a wide spectrum of pollutants thatmay represent environmental hazards. The article“Atmospheric PAH Deposition: Deposition Velocitiesand Washout Ratios” (J. of EnvironmentalEngineering, 2002: 186–195) focused on the depositionof polyaromatic hydrocarbons. The authors proposeda multiple regression model for relating depositionover a specified time period (y, in mg/m2) to tworather complicated predictors x1 (mg-sec/m3) and x2 (mg/m2), defined in terms of PAH air concentrations forvarious species, total time, and total amount of precipitation.Here is data on the species fluoranthene andcorresponding Minitab output:obs x1 x2 flth1 92017 .0026900 278.782 51830 .0030000 124.533 17236 .0000196 22.654 15776 .0000360 28.685 33462 .0004960 32.666 243500 .0038900 604.707 67793 .0011200 27.698 23471 .0006400 14.189 13948 .0004850 20.6410 8824 .0003660 20.6011 7699 .0002290 16.6112 15791 .0014100 15.0813 10239 .0004100 18.0514 43835 .0000960 99.7115 49793 .0000896 58.9716 40656…arrow_forwardIn a study of housing demand, the county assessor is interested in developing a regression model to estimate the market value (i.e., selling price) of residential property within his jurisdiction. The assessor feels that the most important variable affecting selling price (measured in thousands of dollars) is the size of house (measured in hundreds of square feet). He randomly selected 15 houses and measured both the selling price and size, as shown in the following table. OBSERVATIONi SELLING PRICE (× $1,000)Y SIZE (× 100 ft2 )X 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 265.2 279.6 311.2 328.0 352.0 281.2 288.4 292.8 356.0 263.2 272.4 291.2 299.6 307.6 320.4 12.0 20.2 27.0 30.0 30.0 21.4 21.6 25.2 37.2 14.4 15.0 22.4 23.9 26.6 30.7 a. Plot the data.b. Determine the estimated regression line. Give an economic interpretation of the estimated slope (b) coefficient.c. Determine if size is a statistically significant variable in estimating selling price.d. Calculate the coefficient…arrow_forward
- In an attempt to develop a model of wine quality as judged by wine experts, data on alcohol content and wine quality was collected from variants of a particular wine. From a sample of 17 wines, a model was created using the percentages of alcohol to predict wine quality. From the results of that regression, b1=0.4386 and Sb1=0.1141. a. At the 0.05 level of significance, is there evidence of a linear relationship between the percentage of alcohol and wine quality? b. Construct a 95% confidence interval estimate of the population slope, β1. b. The 95% confidence interval is __ ≤ β1 ≤ __ (Round to three decimal places as needed.)arrow_forwardThe 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 abovearrow_forward(a) The standard error Se of the linear regression model is given in the printout as "S." What is the value of Se?arrow_forward
- The following data shows memory scores collected from adults of different ages. Age (X) Memory Score (Y) 25 10 32 10 39 9 48 9 56 7 Use the data to find the regression equation for predicting memory scores from agearrow_forwardIn a study of housing demand, the county assessor develops the following regression model to estimate the market value (i.e., selling price) of residential property within his jurisdiction. The assessor suspects that important variables affecting selling price (YY, measured in thousands of dollars) are the size of a house (X1X1, measured in hundreds of square feet), the total number of rooms (X2X2), age (X3X3), and whether or not the house has an attached garage (X4X4, No=0, Yes=1No=0, Yes=1). Y=α+β1X1+β2X2+β3X3+β4X4+εY=α+β1X1+β2X2+β3X3+β4X4+ε Now suppose that the estimate of the model produces following results: a=166.048a=166.048, b1=3.459b1=3.459, b2=8.015b2=8.015, b3=−0.319b3=−0.319, b4=1.186b4=1.186, sb1=1.079sb1=1.079, sb2=5.288sb2=5.288, sb3=0.789sb3=0.789, sb4=12.252sb4=12.252, R2=0.838R2=0.838, F-statistic=12.919F-statistic=12.919, and se=13.702se=13.702. Note that the sample consists of 15 randomly selected observations. According to the estimated model, holding all…arrow_forwardc. At 5% significance level, is there evidence of a linear relationship between shelf space and sales? (use t-test for correlation coefficient) d. Determine the least square regression equation for this data.arrow_forward
- Algebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage