In linear regression, when are we likely use the prediction interval and confidence interval? Mention some scenarios that we might need it.
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In linear regression, when are we likely use the prediction interval and confidence interval? Mention some scenarios that we might need it.
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- Illustrate the Regression Discontinuity Estimators?Enter the equation of the least‑squares regression line, with the numerical values rounded to three decimal places and ?� as the explanatory variable. (If you are using CrunchIt, adjust the default precision under Preferences as necessary.please only do: if you can teach explain each
- Please answer as many as your allowed too. Thank you :) A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.68b=0.168 (a) Write the equation of the Least Squares Regression line of the formˆyy^= + x(b) Which is a possible value for the correlation coefficient, rr? -1.417 1.417 0.702 -0.702 (c) If a country increases its life expectancy, the happiness index will increase decrease (d) If the life expectancy is increased by 0.5 years in a certain country, how much will the happiness index change? Round to two decimal places.(e) Use the regression line to predict the happiness index of a country with a life expectancy of 69 years. Round to two decimal places.The prediction equation for the data given below is y_hat = -3.98 + 0.56x. What is the residual value when x = 10? 10 2 11 2 15 4 17 0.38 1.62 None Existsthe light and build a 95% confidence interval on the proportion of English soccer fans believing that Liverpool will win the 2019-2020 title. If needed, give the exact Excel formula allowing to compute the confidence interval. Question 5 You have a sample of 223 observations about the daily returns of a company called VA and of an index fund called IND. The table below provides some partial results about a simple linear regression in which VA is the dependent variable and IND is the independent variable. The fitted regression model is: VA = bo + bị* IND. Explain and justify clearly your answer to each question. Give the numerical value when possible. Coefficient Standard Error Upper 95% Test Estimate Statistic Lower 95% Intercept 0.0000584 Q1 0.052 -0.0021549 Q3 Slope 92 0.0555300 30.581 오4 1) What is the value that should appear in the cell with the label Q1? 2) What is the value that should appear in the cell with the label Q2? 3) What is the value that should appear in the cell with…
- ruan Use wage1.txt data set for this question. Consider the following regression: logtwage)-Bo-Beduc-3.exper+u. Suppose we want to test whether the return of an additional year in school will pay more than spending an additional year in the labor market Which of the following is the correct set of hypotheses for this test? Ho: 1-2 HA: 1-20 31 Ho: 1-2 HA: 1-8 270 Ho: 1-220HA: 1-³ 20 Ho: 1-2 HA: 1-820 0.914 what are the limitations of accuracy when using the best fit line compared to equation of the least squares regression line to make predictionsParts b, c, and d only please.
- 11. In this same article on sleep duration and start time, researchers also considered whether school start time was related to obtaining an adequate amount of sleep. An adequate amountbof sleep was considered at least 8.5 hours of sleep, as recommended by the National Sleep Foundation. The authors used logistic regression models to associate the probability of adequate sleep to school start time. Here are some adapted logistic regression results from this study: In(odds of adequate sleep) = 6, + B,, where x1 = school start time, measured as the number of minutes after 7 AM that the school starts. For this model, B,-0.014, SE(B,)-0.005. - What Is the estimated odds ratlo of adequate sleep, and 95% CI, for students who start at 8:30 AM compared to those who start at 7:30 AM? a. 1.01 (1.00, 1.02) b. 1.52 (1.13, 2.05) C. 2.32 (1.27, 4.22) d. 4.05 (1.49, 11.02)A linear regression model based on a random sample of 36 observations on the response variable and 4 predictors has a multiple coefficient of determination equal to 0.697. What is the value of the adjusted multiple coefficient of determination?5