Find an estimator for b when a = 0 using the method of moments.
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A: θb is an unbiased point estimator for a parameter θ.i.e. A random sample of 10000 is taken.
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- How would I solve this part of the question? I'm not sure what to input for the excel formula "Use the paired t-test function (=ttest(array1, array2, tails, type) to determine the if the two sets of measurements are correlated with each other."Suppose a data set of 200 observations (n = 200) was analyzed using OLS to examine the relationship between CEO salary and various measures of firm performance. The regression results are as follows, with standard errors in parentheses: logy = 5 + 0.2logx₁0.03x₂ +0.002x3 (0.2) (0.04) (0.004) where? (0.009) y = CEO salary in thousands of dollars X₁ = annual firm sales X₂ = percentage of sales lost to competitors X3 = return on stock in percent R² = 0.290 Suppose you want to test the null hypothesis that percentage of sales lost to competitors has no ceteris paribus effect on the salaries of CEOS. For the one-sided alternative hypothesis ß₂ < 0 and 1% rejection rule (i.e., at the 1% level), you would_ the null hypothesis that ß₂ = 0.A set of x and y scores has Mx=4,SSx=10,My=5,SSy=40,SP=20.Which is the regress equation for predicting y from x?
- Below is data of lobster sales volume from a seafood company. We're are using exponential smoothing (α = 0.5) and 3-year moving average to forecast it. a) Fill the blanks above and write your processes below. b) What are the mean absolute deviations (MADs) of the two methods? Whichmethod will you choose based on the results? *Please solve for a-b, either type your work and answers or write them neatly on paper* thank you!A paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter2) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a scatterplot in the paper. BMI Change (kg/m²) Depression Score Change S = The accompanying computer output is from Minitab. Depression score change 15- 10- -0.5 S Fitted Line Plot Depression score change = 6.577 +5.440 BMI change 20- 5.30586 Coefficients T 0.0 0.5 -0.5 R-sq 25.96% - 1 Term Coef Constant 6.577 BMI change 5.440 % 0.5 BMI change 1.0 SE Coef 2.28 2.90 9 0 0.1 0.7 0.8 1 1.5 4 T-Value 2.88 1.87 Interpret this estimate. s is the typical amount by which the ---Select--- line. 4 5 Regression Equation Depression score change = 6.577 +5.440 BMI change P-Value 0.0164 0.0906 S 5.30586 25.96% R-Sq R-Sq (adj) 18.56% 8 (b) Give a point estimate of o. (Round your answer to…Suppose the relationship between Y and X is given by: Y = 25 - 3X + error By how much does the expected value of Y change if X decreases by 1 unit?
- If our data were a perfect fit to our regression model, such that y; = ŷ;, we would expect | to be in the CI on p.Calculate x, which gives f(x) = 2 in the dataset, using Newton's Divided Differences Method with reverse interpolation.If the coefficient of determination between two independent variables is 0.33, what is the VIF? VIF= (Round to three decimal places as needed.)
- A physician wants to see if there was a difference in the average smokers' daily cigarette consumption after wearing a nicotine patch. The physician set up a study to track daily smoking consumption. In the study, the patients were given a placebo patch that did not contain nicotine for 4 weeks, then a nicotine patch for the following 4 weeks. Test to see if there was a difference in the average smoker's daily cigarette consumption using α = 0.01. The hypotheses are: H0 : μD = 0 H1 : μD ≠ 0 t-Test: Paired Two Sample for Means Placebo Nicotine Mean 18.75 12.3125 Variance 66.599 34.6667 Observations 16 16 Pearson Correlation 0.6105 Hypothesized Mean Difference 0 df 15 t Stat 3.5481 P(T<=t) one-tail 0.0126 t Critical one-tail 2.6025 P(T<=t) two-tail 0.0252 t Critical two-tail 2.9467 What is the correct p-value? Question 1 options:…The calculation of the coefficient of determination r depends on the number of independent variables. An adjusted value of based on the number of degrees of freedom is calculated using the formula shown below, where n is the number of data pairs and k is the number of independent variables. =1-(1-7)(n-1)] adj n-k-1 Data were found on eight pre-owned sedans of a certain make. Suppose a multiple regression on these data has 6 independent variables. The coefficient of determination is found to be 0.972 based on a sample of 24 paired observations. After calculating rdi, determine the percentage of the variation in y that can be Compare this result with the one obtained using . adj explained by the relationships between variables according to r th %3D 12 adj (Round to three decimal places as needed.) % of the variation in y can be explained by the relationships between variables. About on (Round to one decimal place as needed.) The value of radi the value of 2. is adj uest Que Quest Enter…Based on its linear aproximation, what can we say about the question?