Is it possible to get the following from a set of experimental data: (a) r23 = 0.8, r13 = - 0.5, r12 = 0.6 %3D %3D %3D (b) r23 = 0.7, r13 = - 0.4, r12 = 0.6 %3D %3D
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- Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 130 to 190 cm and weights of 41 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 167.53 cm, y 81.32 kg, r 0.259, P-value 0.009, and y = 106+ 1.09x. Find the best predicted value of y (weight) given an adult male who is 181 cm tall. Use a 0.10 significance lev. The best predicted value of y for an adult male who is 181 cm tall is kg. (Round to two decimal places as needed.)Example 1: Given the following data 72 = 0.8,ři3 = 0.7,3 = 0.6,0 =10.g. = 8 %3D %3D %3D 0z = 5. Determine the regression equation of X, on X, and X, .In multiple regression analysis involving 10 independent variables and 100 observations, the critical value tt for testing individual coefficients in the model will have:A. 10 degrees of freedomB. 89 degrees of freedomC. 100 degrees of freedomD. 9 degrees of freedom In a multiple regression analysis involving 40 observations and 5 independent variables, the total variation SST=350 and SSE=50. The multiple coefficient of determination is:A. 0.8469B. 0.8529C. 0.8408D. 0.8571
- A weight-loss program wants to test how well their program is working. The company selects a simple random sample of 51 individual that have been using their program for 15 months. For each individual person, the company records the individual's weight when they started the program 15 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (205, 190) would be for a specific person and it would indicate that the individual started the program weighing 205 pounds and currently weighs 190 pounds. In other words, they lost 15 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.707. This clearly shows there is strong correlation, which got the company excited. However, when they showed their data to a statistics professor, the professor pointed out that correlation was not the right tool to show that their program was effective. Correlation will NOT show whether or not there is…Suppose you are to estimate a simple regression for the following population model: Y=B₁ + B₁X + µl From a population of over thousands of observations, a small number of samples were randomly selected. The following is some of the information from the randomly selected sample.16.17 In an experiment comparing four diets (treatments), the weight gain y (pounds per day) of pigs was recorded along with two covariates, initial age x₁ (days) and initial weight x2 (pounds). The data are presented in Table 16.11. (a) Using (16.67), (16.68), and (16.69), find Ex, exy, and eyy. Find B. (b) Using (16.77), (16.81), and (16.82), find SSEyr, SST.x, and SS(alu, B). Then test Ho: a₁ = ₂ = a3 = a4, adjusted for the covariates, using the F statistic in (16.83). (c) Test Ho: B = 0 using (16.84). (d) Find B₁, B₂, B3, and 4 using (16.88). Find SSE(F), and SSE(R)y.x using (16.86) and (16.87). Test Ho: B₁ B₂ B3 B4 using (16.89). X1 X2 y X1 78 61 1.40 78 90 59 1.79 99 94 76 1.72 80 71 50 1.47 75 1.26 94 1.28 91 1.34 75 1.55 63 1.57 62 1.26 TABLE 16.11 Initial Age x₁, Initial Weight x2, and Rate of Gain y of 40 Pigs Treatment 1. Treatment 2 Treatment 3 Treatment 4 99 61 80 54 83 57 75 45 62 41 67 40 X2 y X1 74 1.61 78 75 1.31 83 64 1.12 79 48 1.35 70 1.29 85 1.24 83 1.29 1.43 1.29…
- The following is the result of the multiple linear regression analysis in STATISTICA, where the response Y = lung capacity of a person, xage = age of the person in years, xheight = height of the person in inches, = a categorical variable with 2 levels (0 = non- X smoke smoker, 1 = smoker), and xCaesarean = a categorical variable with 2 levels (0 = normal delivery, 1 = %3D %3D Caesarean-section delivery). b* Std.Err. Std.Err. t(720) p-value N=725 Intercept Age Height Smoke Caesarean of b 0.467772 0.017626 of b* -11.8001 0.1372 0.2790 -0.6407 -25.2263 7.7846 28.6552 -5.0142 0.000000 0.000000 0.000000 0.206427 0.026517 0.026340 0.754765 -0.074205 -0.033054 0.009735 0. 127774 0.092146 0.000001 0.022851 0.014799 0.014492 -0.2102 -2.2808 What is the predicted lung capacity of an 14-year old non-smoker whose height is 71 inches born by normal delivery? (final answer to 4 decimal places)Mist (airborne droplets or aerosols) is generated when metal- removing fluids are used in machining operations to cool and lubricate the tool and workpiece. Mist generation is a concern to OSHA, which has recently lowered substantially the workplace standard. The article "Variables Affecting Mist Generaton from Metal Removal Fluids" (Lubrication Engr., 2002: 10-17) gave the accompanying data on x = fluid-flow velocity for a 5% soluble oil (cm/sec) and y = the extent of mist droplets having diameters smaller than 10 μm (mg/m³): x y 89 177 189 354 362 442 965 .40 .60 .48 .66 .61 .69 .99 a. The investigators performed a simple linear regres- sion analysis to relate the two variables. Does a scat- terplot of the data support this strategy? b. What proportion of observed variation in mist can be attributed to the simple linear regression relationship between velocity and mist? c. The investigators were particularly interested in the impact on mist of increasing velocity from 100 to 1000 (a…Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 139 to 188 cm and weights of 38 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 167.62 cm, y = 81.37 kg, r 0.113, P-value = 0.263, and y = - 105+1.01x. Find the best predicted value of y (weight) given an adult male who is 142 cm tall. Use a 0.05 significance level. %3D The best predicted value of y for an adult male who is 142 cm tall is kg. (Round to two decimal places as needed.)
- You run a regression analysis on a bivariate set of data (n = 120). With i = 66.3 and y = 50.6, you obtain the regression equation y = 4.097x – 11.636 with a correlation coefficient of r = 0.56. You want to predict what value (on average) for the response variable will be obtained from a value of 120 as the explanatory variable. What is the predicted response value? y = (Report answer accurate to one decimal place.)9.12 For the chemical reaction data of Table 7.4 with dependent variable y2, compute the diagnostic measures ŷi, &i, hii, ri, ti, and Di. Display these in a table similar to Table 9.1. Are there outliers or potentially influential obser- vations? Calculate PRESS and compare to SSE.You run a regression analysis on a bivariate set of data (n = 89). With a = 35.4 and y = 53.5, you obtain the regression equation %3D y = 3.651x – 38.171 0.1. You want to predict what value (on average) for the %3D - with a correlation coefficient of r = response variable will be obtained from a value of 110 as the explanatory variable. What is the predicted response value? y%3D
