Assume that we estimated the following model by OLS: y =β₁ + β₂x + u. The sample size of the data is n=62. We calculated that the standard errors for β₁ and β₂ are se(β₁)=1 and se(β₂)=2. Also, the estimates for β₁ and β₂ are β₁=3 and β₂=5. We want to test: H₀ : β₁ =5 H₁ : β₁ ≠5. for α=0.05 significance level. What is the p-value of the test?
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Assume that we estimated the following model by OLS:
y =β₁ + β₂x + u.
The
H₀ : β₁ =5
H₁ : β₁ ≠5.
for α=0.05 significance level. What is the p-value of the test?
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- Arm circumferences (cm) and heights (cm) are measured from randomly selected adult females. The 142 pairs of measurements yield x=32.14cm, y=163.36cm, r=.084, P value=.32 and y=160+.111x. Find the best predicted value of y (height) given an adult female with an arm circumference of 40cm. Let the predictor variable x be arm circumference and the response variable y be height. Use a .05 significance level.The regression equation is computed for a set of n = 18 pairs of X and Y values with a correlation of r = 0.50 and SSy = 48. Find the standard error of estimate for the regression equation. The standard error of estimate = How big would the standard error be if the sample size were n = 66? The standard error of estimate =Assume that we estimated the following model by OLS: y =β₁ + β₂x + u.The sample size of the data is n=62. We calculated that the standard errors for β₁ and β₂ are se(β₁)=1 and se(β₂)=2. Also, the estimates for β₁ and β₂ are β₁=3 and β₂=5. We want to test: H₀ : β₂=0 H₁ : β₂≠0.for α=0.05 significance level. What is the t statistic? [We denote the estimates by bold font]
- Recall the data for the three populations. p1 = 0.576 n1 = 250 p2 = 0.48 n2 = 300 p3 = 0.45 n3 = 200 Find the critical value for the pairwise difference between populations i = 1 and j = 3, CV13, rounding the result to four decimal places. CVij = ??2 pi(1 − pi) ni + pj(1 − pj) nj CV13 = ?20.05 p1(1 − p1) n1 + p3(1 − p3) n3 = 5.991 0.576(1 − 0.576) 250 + 0.45(1 − 0.45) = Find the critical value for the pairwise difference between populations i = 2 and j = 3, CV23, rounding the result to four decimal places. CVij = ??2 pi(1 − pi) ni + pj(1 − pj) nj CV23 = ?20.05 p2(1 − p2) n2 + p3(1 − p3) n3 = 5.991 0.48(1 − 0.48) 300 + 0.45(1 − 0.45) =The difference between a regression weight and a beta weight is: A regression weight assumes linearity. A beta weight is for the population while a regression weight is for the sample. A regression weight is less biased. A beta weight is a standardized regression weight.The price X (dollars per pound) and consumption y (in pounds per capita) of beef were samples for 10 randomly selected years. The following data should be used to answer the question that follows. n = 10 Ex = 36.19 Ix² = 134.17 2.9 < x s 6.2 Ey = 774.7 Iy² = 60739.23 Exy = 2832.21 Using this data, a student calculated SSy = 28.43 SSx = 3.2 SSy= 717. Calculate the %3D %3D value of the standard error or regression, Se , and enter you answer accurate to the nearest hundredth (2 decimal places).
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- The average time in years to get an undergraduate degree in computer science was compared for men and women. Random samples of 100 male computer science majors and 100 female computer science majors were taken. Choose the appropriate parameter(s) for this situation. One population mean µ1 Difference between two population proportions p1 − p2 One population proportion p Difference between two population means µ1 − µ2Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 132 to 194 cm and weights of 38 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x 167.75 cm, y=81.58 kg, r0.318, P.value = 0.001, and y-109 1.14x. Find the best predicted value of y (weight) given an adult male who is 184 cm tal, Use a 0.05 significance level. The best predicted value of y for an adult male who is 184 cm tall is kg. (Round to two decimal places as needed.)Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 136 to 190 cm and weights of 39 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yiel x= 167.51 cm, y = 81.36 kg,r= 0.232, P-value = 0.020, and y = - 103+ 1.13x. Find the best predicted value of y (weight) given an adult male who is 153 cm tall. Use a 0.01 significance level. The best predicted value of y for an adult male who is 153 cm tall is kg. (Round to two decimal places as needed.)