Based on the regression output, what is R 2 (or coefficient of determination)
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- Distinguish between the following: (a) Heteroskedasticity and autocorrelation (b) specified regression model vs estimated regression equation (c) data type vs level of measurementDistinguish between the following: (a) Heteroskedasticity and autocorrelation (b) specified regression model vs estimated regression equation (c) data type vs level of measurement (d) ANOVA and Multiple Regression (e) Outliers vs InfluencersAnalyze the residual lot below. Does it violate any of the conditions for an adequate linear model? A. No, the plot of residuals is random. B. Yes, the residuals do not display constant error variance. C. Yes, there is a discernable pattern in the residuals.
- An article in the Journal of Agricultural Science [“The Use of Residual Maximum Likelihood to Model Grain Quality Characteristics of Wheat with Variety, Climatic and Nitrogen Fertilizer Effects” (1997, Vol. 128, pp. 135–142)] investigated means of wheat grain crude protein content (CP) and Hagberg falling number (HFN) surveyed in the United Kingdom. The analysis used a variety of nitrogen fertilizer applications (kg N/ha), temperature (ºC), and total monthly rainfall (mm). The following data below describe temperatures for wheat grown at Harper Adams Agricultural College between 1982 and 1993. The temperatures measured in June were obtained as follows:15.2 14.2 14.0 12.2 14.4 12.514.3 14.2 13.5 11.8 15.2Assume that the standard deviation is known to be σ = 0.5.(a) Construct a 99% two-sided confidence interval on the mean temperature.(b) Construct a 95% lower-confidence bound on the mean temperature.(c) Suppose that you wanted to be 95% confident that the error in estimating the mean…Lyme disease is an inflammatory disease that results in a skin rash and flulike symptoms. It is transmitted through the bite of an infected deer tick. The following data represent the number of reported cases of Lyme disease and the number of drowning deaths for a rural county. Cases_of_Lyme_Disease Drowning_Deaths Month3 0 J2 1 F2 2 M4 1 A5 3 M15 9 J22 17 J13 5 A6 3…An agronomist undertook an experiment to investigate the factors that potato harvest. In his research, agronomist decided to divide the farm into 30 half hectare plots and apply varies level of fertilizer. Potato was then planted and the harvest at the end of the season was recorded. Fertilizer(Kg) Harvest (tons) 210 43.5 220 40.0 230 48.0 240 65.0 250 80.0 260 85.0 270 95.0 280 80.0 290 97.3 Note: No excel ANOVA output allowed. Students need to show all the steps in calculations. You are required to; Find the simple regression line and interpret the coefficients. Find the coefficient of determination and interpret its value. Does the model appear to be a useful tool in predicting the potato harvest? If so, predict the harvest when 250KG of fertilizer is applied. If not explain why not.
- A hospital records the number of floral deliveries its patients receive each day. For a two-week period, the records show PERIOD SALES 1. 15 2. 27 3. 26 4. 24 5. 18 6. 21 7. 26 8. 19 9. 15 10. 28 11. 25 12. 26 13. 17 14. 23 Determine, on the basis of minimizing the mean square error, whether a three-period moving average model or simple exponential smoothing with alpha of .4 gives a better forecast for this problem.Consider a simple regression Y = B1 + B2 X + u. Suppose we found out that the variance of error term is changing with larger values of X (heteroscedasticity). Show how you overcome the problem of heteroscedasticity by using White’s heteroscedasticity consistent variances (only for variance of the slope estimate). Show and explain.The article “Models for Assessing Hoisting Times of Tower Cranes” (A. Leung and C. Tam, Journal of Construction Engineering and Management, 1999: 385–391) presents a model constructed by a stepwise regression procedure to predict the time needed for a tower crane hoisting operation. Twenty variables were considered, and the stepwise procedure chose a nine-variable model. The adjusted R2 for the selected model was 0.73. True or false: a) The value 0.73 is a reliable measure of the goodness of fit of the selected model. b) The value 0.73 may exaggerate the goodness of fit of the model. c) A stepwise regression procedure selects only variables that are of some use in predicting the value of the dependent variable. d) It is possible for a variable that is of no use in predicting the value of a dependent variable to be part of a model selected by a stepwise regression procedure.
- 1a. Develop an estimated regression equation for these data. 1b. Compute the residuals and standardized residualsData: Rate difference per 1000 PY: ___-2.17__; 95% CI __-4.30___ to _-0.03____ HR: __79___; 95% CI _0.63____ to _0.99____ Which statement is the most correct interpretation of the risk of pooled stroke or systemic emboli in the propensity-matched analysis? Apixaban resulted in a statistically significant decrease in stroke or systemic emboli compared to rivaroxaban Apixaban resulted in a statistically significant increase in stroke or systemic emboli compared to rivaroxaban There was no statistically significant difference in stroke or systemic emboli between apixaban and rivaroxaban.Weekly downtime of internet services from an internet service provider (in hours) has expected value 0.5 and variance 0.25. Based on past experience, the data scientist of a retailer store has calculated the loss function to the store from the downtime as C=30X+2X2 where X is the amount of weekly downtime and C is cost. Find the Expected cost, i.e, E(C).