Suppose you estimate a simple linear regression, and the result is that the slope coefficient is 6.278. The Standard Error of the slope coefficient is 1.238. If you specify a Confidence Level of 95% with the corresponding Critical Value of 1.96, what is the UPPER bound of the Confidence Interval for the slope coefficient?
Q: Show the graphical form of the econometric error using sample regression line (SRL) and the…
A: linear regression model is used in economics to show the relation ship between dependent and…
Q: The following data were collected on the height (inches) and weight (pounds) of women swimmers.…
A: Initially it is important to get the values of X*Y & X2, which is mentioned in the table below:
Q: You are given the estimated regression equation y=234-6.2X2+082X3 R-Square-0.42 (7.2) (0.95) (0.45)…
A: The formula to calculate the test statistic is given by, t=B2Standard Error of B2=-6.20.95=-6.526…
Q: mo
A: Regression analysis is a form of predictive modelling technique which investigates the relationship…
Q: In regression analysis, the existence of a significant pattern in successive values of the error…
A: Regression analysis uses various statistical tools and processes in order to estimate the…
Q: SSE is sum of squares of the errors about the regression line.
A: SSE is the sum of the squared differences between each observation and its group's mean. It can be…
Q: Analysis of Variance Source DF SS MS Regression 1 Residual Error 13 0.2364 Total 14 11.3240 What is…
A: Since we know that total SS is the sum of SS from Regression and residuals
Q: rue or False For a linear regression model including only an intercept, the OLS estimator of that…
A:
Q: A regression of yt on x+ was conducted and an ADF test on the estimated residuals was performed. The…
A: A regression is a statistical approach for describing the actual connection between one or more…
Q: For a regression model y = XB + u where u is N(0, o 1), y is nx1 matrix, X is nxp matrix, B is px1…
A:
Q: Consider the simple regression model Yi = B2x1 + & Find the least squares estimator b, and show Eŷ,…
A:
Q: In terms of econometric perspective, what are the assumptions or elements that you need to consider…
A: As per the classical presumptions, the components of the unsettling influence vector ε are…
Q: For the regression Y = B0+B1X+u, the variance u is conditional homoskedastic. Is it correct if you…
A: Solution: The concept of regression models, the errors of a regression model, the assumptions of…
Q: The following sample observations were randomly selected. (Round intermediate calculations and final…
A: Given y X 4 5 6 5 5 3 7 6 2 7 We have to find the regression equation y=β0+β1x
Q: If the sample coefficient of determination (R2) is 0.75, this means that a. 75 percent of the…
A: Coefficient of determination (R2) is a statistical measure which tells us the goodness of fit of…
Q: a simple linear regression equation shows the relationship between-
A: There are two types of variables that are widely used: Dependent variable - This variable is…
Q: a 95% confidence interval for B1, the regression slope coefficient. confidence interval for B1, the…
A:
Q: (a)Heteroscedasticity can lead to A. smaller t values B. all of the statements are correct C.…
A: Heteroscedasticity occurs when the variance of the dependent variable is not constant. Even with…
Q: In a simple linear regression you are told that the estimate of the slope coefficient was 0.7 and…
A: Here, t- statistic (t)= -2.4 Slope coefficient (b1) = 0.7 We used to test H0 : β1 = 1 (Unity) Ha…
Q: Could someone answer this for me please You estimate a simple linear regression model using a sample…
A: Answer: As it is mentioned : Y= 97.25 +19.74*X(3.86) (3.42 interval estimate =99%
Q: The assumption that the error terms in a regression model follow the normal distribution with zero…
A: OLS (Ordinary Least Squares): This method helps in estimating the unknown parameters in a linear…
Q: Select your answer - v b. What does the scatter diagram developed in part (a) indicate about the…
A: (b) Determine the type of relationship exists between the two variables. From the scatter plot…
Q: Suppose you are the manager of a firm that produces good X in Ghana In order to make informed…
A:
Q: A scatter plot shows data for the cost of a vintage car from a dealership (y in dollars) in the year…
A: The researchers and policymakers generally use a regression model to get the best result from their…
Q: 1.In econometrics, a sample is Select one: a. the entire group of entities that we are interested…
A: Since you have posted multiple questions so as per answering guideline, we will solve first…
Q: You are given the estimated regression equation y=234-6.2X2+082X3 R-Square=0.42 (7.2) (0.95) (0.45)…
A: The formula for calculation will be, t =B2Standard Error of B2=-6.20.95=-6.526
Q: what are the key features , Strength and limitation of following model? and when which model should…
A: Ordinary Least Squares regression (OLS) is a method for estimating the coefficients of linear…
Q: When the regression line passes through the origin then: O The intercept is zero. The regression…
A:
Q: A multiple regression model has the estimated form y hat (estimated value of y)= 5 + 6x + 7w As w…
A: In multiple regression, dependent variable is regressed on two or more independent variables.
Q: The simple linear regression model in the exhibit 2 data shows that, Both the intercept and the IDV…
A: "Since you have asked multiple questions, we will solve the first question for you. If you want any…
Q: Suppose Y is the annual income, X is the number of years of education, and D is a dummy variable…
A: Linear regression shows relationship between tell variable.
Q: A website that rents movies online recorded the age and the number of movies rented during the past…
A: Sample size n = 25< 30 SE(b1) = 0.0827
Q: 18 Calcurate the least square regression líne equation with the given X and Y values. Consider the…
A: X Y X2 XY 60 3.1 3600 186 61 3.6 3721 219.6 62 3.8 3844 235.6 63 4 3969 252 65 4.1 4225…
Q: When the R2 of a regression equation is very high, it indicates that all the coefficients are…
A: R2 indicates the co-efficient of determinations. The higher the values, the higher is the…
Q: Based on data from 63 counties, the following model was estimated by least squares:ŷ = 0.58 -…
A: The regression function shows the linear relationship between dependent variable and independent…
Q: Consider the linear regression y; = Bo + B,x, +u, i= 1,..,n,n+1,.,n+ p where E(u,) =0. Is it…
A: Yes it is possible.
Q: A key assumption for the identification of the ceteris paribus effect in a multiple linear…
A: Multiple linear regression model is a model of several explanatory variables for predicting the…
Q: Suppose you wanted to test the hypothesis that BDR equals zero. That is, Ho: BDR=0 vs H: BDR#0…
A: t- test is a tool used for hypothesis testing which allows to test whether an assumption is…
Q: You estimated a linear regression model with 3 explanatory variables using a sample of 29…
A: The F-test of overall significance in regression depicts whether the model of linear regression…
Q: A multiple regression of y on a constant x, and x2 produces the following results: ý = 4 + 0.4x +…
A: Given that : The objective of the following analysis is to test the null hypothesis that the two…
Q: QUESTION 8 Having many relevant instruments: a. is good because they provide more information. D. is…
A: When making economic analysis, various aspects are considered for an effective regression model.
Q: When Y is regressed on X, B, > 0, sx# 0, sy# 0, and the fraction of the variation in Y explained by…
A: Note:- “Since you have asked multiple question, we will solve the first question for you. If you…
Q: The standard deviation of the error terms in an estimated regression equation is known as:
A: Error term is the left over variable in a model when independent and dependent variable are unable…
Q: (Yi, X1i, X2i) satisfy the assumptions of the attachment. You are interestedin β1, the causal effect…
A: Regression analysis is an important technique of forecasting in the field of econometrics. It…
Q: Question 15 When the R2 of a regression equation is very high, it indicates that all the…
A: The regression equation is written as follows: Y = b0+b1X Here, Y is the dependent variable b0 is…
Q: Using a sample of recent university graduates, you estimate a simple linear regression using initial…
A: Estimated regression equation: Starting salary = 3200 + 550 x WAM
Q: An important type of nonlinear cost curve is the learning curve, and it: shows how the labor hours…
A: According to the learning curve, collective experience in the production of a good over time…
Q: Construct a 95% confidence interval for the average value of y for the following data. Use x = 25,…
A:
Q: 1. If in a simple linear regression, SST = 315 and the sample correlation coefficient between your…
A: When talking abou linear regression model, there are different methods to determine sample…
Q: For the estimated regression equation ŷ= 15 + 6x1 + 5x2 + 4x1X2, a unit increase in x2, while…
A: Here, we calculate the given for the estimated regression equation by the following method given…
2
Step by step
Solved in 2 steps
- 1. Suppose have the sample linear regression function: we Y = B, + B,X, +e,, Bo and B are OLS estimates, prove the following equations hold: Ee, = 0 а. %3D b. Se,x, = 0, x, is the deviation form of Xi EeÝ, = 0 c. d. Y = Y 2. Suppose the sample size n=10, we have the following figures for the sample data: ΣΥ-1110; ΣΧ-1 680; ΣΧY -204200 | ΣΧ31 5400; ΣΥ-133300 The representation of PRF is Y = b, +b,X, +u,, u, O iid N(0,4) The OLS estimates for the SRF is ß, and B a. calculate B, and B with the above figures. b. calculate the standard error of B, and B- c. calculate the determination coefficient: R? d. construct 95% confidence interval for b, and b, respectively. e. conduct hypothesis test: HO: b, =0, H1: b, #0. f. conduct hypothesis test: HO: b, =1, H1: b, #1.ANOVA Sigmficance F 0,046 df SS MS F 130433116.219 130433116.219 4.083 Regression Residual Total 113 3609911959.86s 31946123.539 114 3740345076.087 Cosfficrent Standard Error Stát Pvalne 1535.215 Intercept Age 10725.802 6.987 0,000 69.964 34.625 2.021 0.046 Which of the following statements is the best explanation of the R? Select one O'A3.5% of the accident damage can be explained by the age of the driver. B. 3.5% of the variation in accidernt damage can be eaplained by variation in the age of the drver. CC3.5% of the coefficients r stat and p value can be explained by the age of the dtver. D.3.5% of the total errar can be eiplained by the SSE Scanned with CamScannerYou are given the estimated regression equation y=234-6.2X2+082X3 R-Square%-D0.42 (7.2) (0.95) (0.45) The number between parentheses are standard error the Sample size N=100 The test statistics to test that B2=-5 against the alternative that it is less than -5 is equal to O a. -6.526 O b. -1.263 C. -11.789 d. None of the option is correct
- Exercises 5.1 Suppose that a rescarcher, using data on class size (CS) and average test scores from 100 third-grade classes, estimates the OLS regression TestScore- 520.4 - 5.82 x CS, R² =0.08, SER = 11.5. (20.4) (2.21) a. Construct a 95% confidence interval for B, the regression slope coef- ficient. b. Calculate the p-value for the two-sided test of the null hypothesis Hs B1 -0. Do you reject the null hypothesis at the 5% level? At the 1% level?12- Which of the following is true in case of measurement error in the regressor? a) O Predictors are biased and consistent 35 b) O Predictors are unbiased and consistent C) O Predictors are unbiased and inconsistent d) O Predictors are biased and inconsistent Leave blankIf two regressors are a linear combination of each other, what is the result if we run an OLS regressions with both of those regressors present? The regressors will cause the variance of the estimates to be higher but the estimates will still be unbiased. O a. We cannot run OLS because we have perfect multicollinearity. Ob. It will ensure our residuals are linear and not plagued by nonlinearity. OC. It will increase the power of our estimates since the two regressors are related. Od. None of these. Oe.
- As a manager of a small software retailing company, you are concerned with projected profit next year. While profit can be determined as the difference between sales and maintenance cost, or in symbols, P = S - M, where P is profit, S is sales, and M is maintenance cost including technical support. It is argues that when sales goes up so does maintenance cost because the cost of technical support will go up. Further, it is measured that the correlation between S and M is 0.8. Now given the figure that sales next year is expected to be $300 thousand with standard deviation of $4 thousand and maintenance cost is expected to be $150 thousand with standard deviation of $6 thousand, what would be the expected profit and its standard deviation you will include in your report?Describe the important characteristics of the variance of a conditional distribution of an error term in a linear regression. What are the implicationsfor OLS estimation?6 9 13 Yi 7 18 9. 26 23 a. Which of the following scatter diagrams accurately represents the data? A. 24+ 24+ 20- 20- 16+ 16+ 12+ 12+ 8+ 8+ 4- -4 4 12 16 24 28 x -4 4 8. 12 16 20 24 28 x -4t -4t С. D. 24 -----24+ 20- 20- 16- 16- 20 B. 20 00 00 O.
- A certain standardized test measures students' knowledge in English and math. The English and math scores for 10 randomly selected students were recorded and analyzed. The results are shown in the computer output. Predictor Coef SE Coef t-ratio Constant -124.13 78.712 0.046 Math 1.223 0.1966 6.220 0.000 S = 34.55 R-Sq = 82.8% R-Sq (Adj) = 83.5% Which of the following represents the standard deviation of the residuals? O 1.223 34.55 78.712 124.13If the sample coefficient of determination (R2) is 0.25, this means that O 25 percent of the variation in the independent variable is explained by the regression. O 75 percent of the variation in the independent variable is explained by the regression. O 75 percent of the variation in the dependent variable is explained by the regression. 25 percent of the variation in the dependent variable is explained by the regression.25) Consider the estimated equation from your textbook = 698.9 - 2.28STR, R2 = 0.051, SER = 18.6, Corresponding standard errors of coefficients are as such: SE (698.9) = 10.4 SE (-2.28) = 0.52 The absolute value of t-statistic for the slope is approximately: A. 67.20 B. 1.76 C. -4.38 D. 0.52