Given a simple regression analysis, suppose that we have obtained the fitted regression model: ^yi=6+8xi and also...
Given a simple regression analysis, suppose that we have obtained the fitted regression model:
^yi=6+8xi and also the following statistics: SE=3.20, x̄=8,n=42, and ∑ (xi-x̄)2 =420
1) Find the 95% confidence interval for the point where x =18.
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Given a simple regression analysis, suppose that we have
obtained the fitted regression model:
^yi=6+8xi and also...
please help! Following is a simple linear regression model: y = a + A + &...
please help!
Following is a simple linear regression model: y = a + A + & The following results were obtained from some statistical software. R2 = 0.523 Syx (regression standard error) = 3.028 n (total observations) = 41 Significance level = 0.05 = 5% Variable Interecpt Slope of X Parameter Estimate 0.519 -0.707 Std. Err. of Parameter Est 0.132 0.239 Note: For all the calculated numbers, keep three decimals. Write the fitted model (5 points) 2. Make a prediction...
A simple linear regression model is given as follows Yi = Bo + B1Xi+ €i, for...
A simple linear regression model is given as follows Yi = Bo + B1Xi+ €i, for i = 1, ...,n, where are i.i.d. following N (0, o2) distribution. It is known that x4 n, and x = 0, otherwise. Denote by n2 = n - ni, Ji = 1 yi, and j2 = 1 1. for i = 1, ... ,n1 < n2 Lizn1+1 Yi. n1 Zi=1 1. Find the least squares estimators of Bo and 31, in terms of...
2.4 We have defined the simple linear regression model to be y =B1 + B2x+e. Suppose...
2.4 We have defined the simple linear regression model to be y =B1 + B2x+e. Suppose however that we knew, for a fact, that ßı = 0. (a) What does the linear regression model look like, algebraically, if ßı = 0? (b) What does the linear regression model look like, graphically, if ßı = 0? (c) If Bi=0 the least squares "sum of squares" function becomes S(R2) = Gyi - B2x;)?. Using the data, x 1 2 3 4 5...
1. Suppose that Yi = Bo + B1Xi + €¡ where ; is N(0,0.6), Bo =...
1. Suppose that Yi = Bo + B1Xi + €¡ where ; is N(0,0.6), Bo = 2 and 31 = 1. (a) What are the conditional mean and standard deviation of Yị given that Xi = 1? What is P(Yi < 3|X; = 1)? (b) A regression model is a model for the conditional distribution of Yị given Xị. However, if we also have a model for the marginal distribution of X; then we can find the marginal distribution of...
We run the following linear regression model in Excel (or any other softwares) Yi = β0...
We run the following linear regression model in Excel (or any other softwares) Yi = β0 + β1Xi + β2Wi + εi , where i = 1, 2, . . . , 100. The results suggest that the slope on Xi is 97.28 with t-statistics 0.91, and the slope on Wi is 15.81 with t-statistics 11.39. What does it tell us?
we use a person's dad's height to predict how short or tall the person will be by Suppose building a regression...
we use a person's dad's height to predict how short or tall the person will be by Suppose building a regression model to investigate if a relationship exists between the two variables. Suppose the confidence/prediction interval results are as follows: Predicted/Fitted Values of Height Lower Predicted Bound57.739 Lower Fitted Bound 66.451 Predicted Value Fitted Value 67.532 67.532 Upper Predicted Bound 77.326 Upper Fitted Bound 68.613 SE (Fitted Value) SE (Predicted Value) 0.5432 4.9212 Unusualness (Leverage) 0.0123 Percent Coverage 95 Corresponding...
2. Consider a simple linear regression model for a response variable Yi, a single predictor variable...
2. Consider a simple linear regression model for a response variable Yi, a single predictor variable ri, i-1,... , n, and having Gaussian (i.e. normally distributed) errors Ý,-BzitEj, Ejį.i.d. N(0, σ2) This model is often called "regression through the origin" since E(Yi) 0 if xi 0 (a) Write down the likelihood function for the parameters β and σ2 (b) Find the MLEs for β and σ2, explicitly showing that they are unique maximizers of the likelihood function. (Hint: The function...
Suppose we have a regression model Yi = bXi + Ei where Y = X =...
Suppose we have a regression model Yi = bXi + Ei where Y = X = 0 and there is no intercept in the model. Consider a slope estimator ĥ - E(X;)2(Y;) 2(x;)2 Show whether this will yield an unbiased estimate of b or not.
A simple linear regression (linear regression with only one predictor) analysis was carried out using a...
A simple linear regression (linear regression with only one predictor) analysis was carried out using a sample of 23 observations From the sample data, the following information was obtained: SST = [(y - 3)² = 220.12, SSE= L = [(yi - ġ) = 83.18, Answer the following: EEEEEEEE Complete the Analysis of VAriance (ANOVA) table below. df SS MS F Source Regression (Model) Residual Error Total Regression standard error (root MSE) = 8 = The % of variation in the...
Consider the multiple linear regression (MLR) model that satisfies the classical assumptions: Yi = Bo +...
Consider the multiple linear regression (MLR) model that satisfies the classical assumptions: Yi = Bo + B1Xil +...+Bkxik + Ui estimated by OLS/MOM. Let the estimators beßo, Ŝ1,..., ØK. Question 1 (1 point) The p-value for undertaking a hypothesis test is the smallest significance level for which we reject a null hypothesis that is correct. True False Question 2 (1 point) To test Ho: B3 = 34 vs H1 : B3 – B4 > 0, we form the test statistic...
please help!
Following is a simple linear regression model: y = a + A + & The following results were obtained from some statistical software. R2 = 0.523 Syx (regression standard error) = 3.028 n (total observations) = 41 Significance level = 0.05 = 5% Variable Interecpt Slope of X Parameter Estimate 0.519 -0.707 Std. Err. of Parameter Est 0.132 0.239 Note: For all the calculated numbers, keep three decimals. Write the fitted model (5 points) 2. Make a prediction...
A simple linear regression model is given as follows Yi = Bo + B1Xi+ €i, for i = 1, ...,n, where are i.i.d. following N (0, o2) distribution. It is known that x4 n, and x = 0, otherwise. Denote by n2 = n - ni, Ji = 1 yi, and j2 = 1 1. for i = 1, ... ,n1 < n2 Lizn1+1 Yi. n1 Zi=1 1. Find the least squares estimators of Bo and 31, in terms of...
2.4 We have defined the simple linear regression model to be y =B1 + B2x+e. Suppose however that we knew, for a fact, that ßı = 0. (a) What does the linear regression model look like, algebraically, if ßı = 0? (b) What does the linear regression model look like, graphically, if ßı = 0? (c) If Bi=0 the least squares "sum of squares" function becomes S(R2) = Gyi - B2x;)?. Using the data, x 1 2 3 4 5...
1. Suppose that Yi = Bo + B1Xi + €¡ where ; is N(0,0.6), Bo = 2 and 31 = 1. (a) What are the conditional mean and standard deviation of Yị given that Xi = 1? What is P(Yi < 3|X; = 1)? (b) A regression model is a model for the conditional distribution of Yị given Xị. However, if we also have a model for the marginal distribution of X; then we can find the marginal distribution of...
we use a person's dad's height to predict how short or tall the person will be by Suppose building a regression model to investigate if a relationship exists between the two variables. Suppose the confidence/prediction interval results are as follows: Predicted/Fitted Values of Height Lower Predicted Bound57.739 Lower Fitted Bound 66.451 Predicted Value Fitted Value 67.532 67.532 Upper Predicted Bound 77.326 Upper Fitted Bound 68.613 SE (Fitted Value) SE (Predicted Value) 0.5432 4.9212 Unusualness (Leverage) 0.0123 Percent Coverage 95 Corresponding...
2. Consider a simple linear regression model for a response variable Yi, a single predictor variable ri, i-1,... , n, and having Gaussian (i.e. normally distributed) errors Ý,-BzitEj, Ejį.i.d. N(0, σ2) This model is often called "regression through the origin" since E(Yi) 0 if xi 0 (a) Write down the likelihood function for the parameters β and σ2 (b) Find the MLEs for β and σ2, explicitly showing that they are unique maximizers of the likelihood function. (Hint: The function...
Suppose we have a regression model Yi = bXi + Ei where Y = X = 0 and there is no intercept in the model. Consider a slope estimator ĥ - E(X;)2(Y;) 2(x;)2 Show whether this will yield an unbiased estimate of b or not.
A simple linear regression (linear regression with only one predictor) analysis was carried out using a sample of 23 observations From the sample data, the following information was obtained: SST = [(y - 3)² = 220.12, SSE= L = [(yi - ġ) = 83.18, Answer the following: EEEEEEEE Complete the Analysis of VAriance (ANOVA) table below. df SS MS F Source Regression (Model) Residual Error Total Regression standard error (root MSE) = 8 = The % of variation in the...
Consider the multiple linear regression (MLR) model that satisfies the classical assumptions: Yi = Bo + B1Xil +...+Bkxik + Ui estimated by OLS/MOM. Let the estimators beßo, Ŝ1,..., ØK. Question 1 (1 point) The p-value for undertaking a hypothesis test is the smallest significance level for which we reject a null hypothesis that is correct. True False Question 2 (1 point) To test Ho: B3 = 34 vs H1 : B3 – B4 > 0, we form the test statistic...
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