* Incorrect. In Applied Life Data Analysis (Wiley, 1982), Wayne Nelson presents the breakdown time of an insulating fluid between electrodes at 34kV. The times, in minutes, are as follows: 0.18, 0.78, 0.97, 1.27,2.89, 3.06, 4.09, 4.61, 4.88, 6.42,7.47, 8.06, 8.36, 12.80, 31.79, 32.62, 33.86, 36.80, and 72.73. Calculate the sample mean and sample deviation of the breakdown data. Round your answers to 2 decimal places. Mean- Standard Deviation => 14.61 19.10 minutes minutes
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- In Applied Life Data Analysis (Wiley, 1982), Wayne Nelson presents the breakdown time of an insulating fluid between electrodes at 34 kV. The times, in minutes, are as follows: 0.19, 0.78, 0.96, 1.31, 2.78, 3.16, 4.15, 4.67, 4.85, 6.50, 7.35, 8.01, 8.27, 12.06, 31.75, 32.52, 33.91, 36.71, and 72.89. Calculate the sample mean and sample standard deviation.An article in the ASCE Journal of Energy Engineering [“Overview of Reservoir Release Improvements at 20 TVA Dams” (Vol. 125, April 1999, pp. 1–17)] presents data on dissolved oxygen concentrations in streams below 20 dams in the Tennessee Valley Authority system. The observations are (in milligrams per liter):) The following table shows 10 communities ranked by decayed, missing, or filled (DMF) teeth per 100 children and fluoride concentration in ppm in the public water supply: Rank by DMF Teeth FluorideCommunity per 100 children X Concentration Y 1 8 1 2 9 3 3 7 4 4 3 9 5 2 8 6 4 77 1…
- The annual flows, in cubic meters per second, at the Weldon River at Mill Grove, Missouri for the period 1930 to 1960 are averaged as follows: 3.06 1.52 16.00 2.78 1.15 13.39 2.74 6.16 1.21 5.90 4.06 2.66 11.29 8.46 7.04 12.51 10.91 16.09 3.46 4.28 6.92 11.35 6.95 3.23 18.70 3.75 1.25 2.063.83 18.02 14 .41Fit the lognormal distribution to this data. Comment on the goodness-of-fit to the lognormal distribution.Life-saving drug: Penicillin is produced by the Penicillin fungus, which is grown in a broth whose sugar content must be carefully controlled. Several samples of broth were taken on three successive days, and the amount of dissolved sugars, in milligrams per milliliter, was measured on each sample. The results were as follows. Day 1: 5.2 5.0 5.4 5.2 5.3 5.0 4.9 5.0 5.2 5.0 4.6 5.3 Day 2: 5.6 4.8 4.9 5.3 5.2 4.9 5.4 5.0 5.4 4.9 5.5 5.4 Day 3: 5.9 4.9 5.3 5.4 5.2 5.5 5.0 5.8 5.5 5.4 5.4 5.1 Construct an ANOVA table. Round your answers to four decimal places as needed. One-way ANOVA: Sugar Concentration Source DF SS MS F P Days Error TotalA chemical reaction is run 12 times, and the temperature xi (in °C) and the yield yi (in percent of a theoretical maximum) is recorded each time. The following summary statistics are recorded: x⎯⎯=65.0, y⎯⎯=29.03,∑ni=1(xi−x⎯⎯)2=6032.0,∑ni=1(yi−y⎯⎯)2=835.42,∑ni=1(xi−x⎯⎯)(yi−y⎯⎯)=1988.6x¯=65.0, y¯=29.03,∑i=1n(xi−x¯)2=6032.0,∑i=1n(yi−y¯)2=835.42,∑i=1n(xi−x¯)(yi−y¯)=1988.6 Let β0 represent the hypothetical yield at a temperature of 0°C, and let β1 represent the increase in yield caused by an increase in temperature of 1°C. Assume that assumptions 1 through 4 for errors in linear models hold. Find a 95% prediction interval for the yield of a particular reaction at a temperature of 40°C. Round the answers to three decimal places. The 95% prediction interval is ( , ).
- A chemical reaction is run 12 times, and the temperature xi (in °C) and the yield yi (in percent of a theoretical maximum) is recorded each time. The following summary statistics are recorded: x⎯⎯=65.0, y⎯⎯=29.03,∑ni=1(xi−x⎯⎯)2=6032.0,∑ni=1(yi−y⎯⎯)2=835.42,∑ni=1(xi−x⎯⎯)(yi−y⎯⎯)=1988.6x¯=65.0, y¯=29.03,∑i=1n(xi−x¯)2=6032.0,∑i=1n(yi−y¯)2=835.42,∑i=1n(xi−x¯)(yi−y¯)=1988.6 Let β0 represent the hypothetical yield at a temperature of 0°C, and let β1 represent the increase in yield caused by an increase in temperature of 1°C. Assume that assumptions 1 through 4 for errors in linear models hold. Compute the error variance estimate s2. Round the answer to three decimal places.When water flows across farmland, some soil is washed away, resulting in erosion. An experiment was conducted to investigate the effect of the rate of water flow (liters per second) on the amount of soil (kilograms) washed away. The data are given in the following table: Flow rate 0.31 0.85 1.26 2.47 3.75 Eroded soil 0.82 1.95 2.18 3.01 6.07 Let xx represent the flow rate variable and yy represent the variable for soil eroded. Then \bar x = 1.73, s_x = 1.38, \bar y = 2.81, s_y = 1.99xˉ=1.73,sx=1.38,yˉ=2.81,sy=1.99 Use this to complete the following calculation of the correlation coefficient for these data. r = \frac{1}{n-1}\left[\left(\frac{x_1 - \bar x}{s_x}\right)\left(\frac{y_1 - \bar y}{s_y}\right) + \left(\frac{x_2 - \bar x}{s_x}\right)\left(\frac{y_2 - \bar y}{s_y}\right) + \cdots + \left(\frac{x_n - \bar x}{s_x}\right)\left(\frac{y_n - \bar y}{s_y}\right)\right]r=n−11[(sxx1−xˉ)(syy1−yˉ)+(sxx2−xˉ)(syy2−yˉ)+⋯+(sxxn−xˉ)(syyn−yˉ)]…3. The following Table gives data on output per hour (X) and real compensation per hour (Y) for the business and nonfarm business sectors of the U.S. economy. Year 1990 Y X 1991 1 10 1992 3 15 4 20 Estimate the slope of the OLS regression of Y on X (ẞ2) from the following regression: Yi = β₁ + β2 Xi + Ui
- The data given below indicate the existence of a linear relationship between the x and y variables. Suppose an analyst who prepared the solutions and carried out the RI measurements was not skilled and as a result of poor technique, allowed intermediate errors to appear. The results are the following:Concentration of solution in percent (x) 10 26 33 50 61Refractive indices (y) 1.497 1.493 1.485 1.478 1.477Step 1. Carefully plot the given x and y values (from the table) on a regular graphing paper. Label then connect the points to observe a zigzag plot due to the scattered points. Step 2: Copy and fill the table given below: x (x - x̄) (x - x̄) 2 y (y - ȳ) (y - ȳ) 2 (x - x̄) (y - ȳ) 10 1.497 26 1.49333 1.48550 1.47861 1.477∑ = ∑ = ∑ = ∑ = ∑ = ∑ = ∑ =x̄= ∑xi ÷ Nx̄= ȳ = ∑yi ÷ Nȳ = Step 3. After completing the table, present following computations and the interpretation.a. Calculate the correlation coefficient (r), using the working formula: r =Σ (x − x ) (y − ȳ)√(Σ(x − x )2)(Σ(y −…Periodically, the county Water Department tests the drinking water of homeowners for contaminants such as lead and copper. The lead and copper levels in water specimens collected in 1998 for a sample of 10 residents of a subdevelopement of the county are shown below. lead (μμg/L) copper (mg/L) 4.4 0.643 2.4 0.57 1.5 0.46 2.6 0.895 5.9 0.2 3.4 0.54 3.8 0.245 1.6 0.583 5.7 0.769 1.7 0.215 (a) Construct a 9999% confidence interval for the mean lead level in water specimans of the subdevelopment. ≤μ≤For these (x,y) pairs of data points: 1,5 3,7 4,6 5,8 7,9 Compute b1. Compute b0. What is the equation of the regression line?