Use the following set of points to test the null hypothesis H₁B₁=0 versus H₁ : ß₁ ‡0. Use the critical value method with the a=0.10 level of significance. The1slope of the regression line for this data is computed to be b₁ = 1.06496, and the standard error of b₁ is computed to be Sb = 0.097861.Xy1916 3132Send data to ExcelPart: 0 / 4Part 1 of 48 29 17 16 15 18Critical value(s):5 27 12 12 16 14Find the critical value(s). Round the answer to three decimal places. If there is more than one critical value, separate them with commas.0,0,...XŚ Part 2 of 4Compute the test statistic. Always round t-score values to three decimal places.t =Part: 2 / 4Part 3 of 4Determine whether to reject Ho(Choose one) the null hypothesis Ho.Part: 3 / 4Part 4 of 4Summarize the results.There (Choose one)the variables.××enough evidence to conclude that there is a linear relationship betweenŚXŚ

The following information has been given:The slope is The standard error of slope is The sample size…

Answered: Use the following set of points to test…

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter1: Functions

Section1.2: The Least Square Line

Problem 8E

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= Consider the following dataset with three observations, i.e., Y : (2.2, 2.8, 4.2) and X (0.4, 0.8, 1.2), and the linear regression model Y = Bo+B₁X. Calculate the LOOCV (Leave- One-Out Cross-Validation) error. =
One of the residuals in a linear regression model is equal to 6.5. Other results from the model areMSE = 3.2, MSR = 4.5, SSE = 182, and SSR = 243. The value of the standardized residual is:a. 3.06b. 3.63c. 0.48d. 0.42e. None of the other answers is correct
Consider the model Ci= B0+B1 Yi+ ui. Suppose you run this regression using OLS and get the following results: b0=-3.13437; SE(b0)=0.959254; b1=1.46693; SE(b1)=0.0697828; R-squared=0.130357; and SER=8.769363. Note that b0 and b1 the OLS estimate of b0 and b1, respectively. The total number of observations is 2950. The number of degrees of freedom for this regression is A. 2950 OB. 2948 OC. 2952 OD. 2
Let kids denote the number of children ever born to a woman, and let educ denote years of education for the woman. A simple model relating fertility to years of education is: kids; = Bo + B1educ; + uż. 1. What are the parameters in the model? 2. What kinds of factors are contained in u? Are these likely to be cor- related with level of education? 3. Will a simple regression analysis uncover the ceteris paribus effect of education on fertility? Explain.
The least-square regression line for the given data is y=-0.206x + 2.097. Determine the residual of a data point for which x= 1 and y=-3, rounding to three decimal places. X -5 y 11 OA. - 4.891 OB. - 1.715 O C. - 1.109 OD. 1.891 - 3 -6 4 8 1 - 3 - 1 -2 -2 1 ло 0 5 25 -5 3 6 -40 7
The following sample contains the scores of 6 students selected at random in Mathematics and English. Use the scores in English as the dependent variable Y. Mathematics score (X) 70 92 80 74 65 83 English score (Y) 74 84 63 87 78 90 ∑x=464, ∑y=476,∑x^2=36354,∑y^2=38254, ∑xy=36926. Estimate the regression parameters and also write the prediction equation.
A set of n = 15 pairs of X and Y values has a correlation of r = +0.80 with SSY = 75, and the regression equation for predicting Y is computed. Find the standard error of estimate for the regression equation. How big would the standard error be if the sample size were n = 30.
Use the following results obtained from a simple linear regression analysis with 12 observations. Y = 37.2895- (1.2024)X Sb = 0.2934 Test to determine if there is a significant negative relationship between the independent and dependent variables at alpha= .05. Give the resulting conclusion. a. is rejected. B.cannot be tested with the given information. c. is not rejected. D. is not an appropriate null hypothesis for this situation.
The following estimated regression equation is based on 10 observations was presented. ŷ = 29.1270 + 0.5906x1 + 0.4980x2 . Here SST=6,724.125 , SSR = 6,216.375 , sb1 = 0.0813, sb2 = 0.0567. Compute MSR & MSE to 3 decimals, then compute F using the appropriate F test (round answer to 3 decimals). Use α = 0.05.
You have estimated a multiple regression model with 6 explanatory variables and an intercept from a sample with 46 observations. What is the critical value of the test statistic (tc) if you want to perform a test for the significance of a single right-hand side (explanatory) variable at α = 0.05? a.) 2.023 b.) 2.708 c.) 2.423 d.) 2.704
Use the following set of points to test the null hypothesis H0:β1=0 versus ≠:H1β10. Use the P-value method with the =α0.01 level of significance. The slope of the regression line for this data is computed to be b1=−0.88401, and the standard error of b1 is computed as sb=0.311147. Use the TI-84 calculator. x 10 15 8 18 19 13 y 15 10 23 11 12 14 Compute the test statistic. Always round the t-score values to three decimal places.
A student used multiple regression analysis to study how family spending (y) is influenced by income(x1), family size (x2), and additionsto savings(x3). The variables y, x1, and x3 are measured in thousandsof dollars. The following results were obtained. ANOVA df SSRegression 3 45.9634Residual 11 2.6218Total Coefficients Standard Error Intercept 0.0136x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 -Write out the estimated regression equation for the relationship between the variables. (1mark)-Compute coefficient of determination. What can you say about the strength of thisrelationship? -Carry out a test to determine whether y is significantly related to the independent variables.Use a 5% level of significance.-Carry out a test to see if x3 and y are significantly related. Use a 5% level of significance.

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