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- We wish to determine if there is a correlation between the birth weight (in grams) of nine newborn infants and the length of their mothers’ stay (in days) in the hospital. The results of a correlation and regression analysis are indicated in the Excel output below. The mean birth weight of the newborn infants (the independent variable) was 3162.5 grams, and the mean length of their mothers’ stay in the hospital (the dependent variable) was 7 days. SUMMARY OUTPUT Regression Statistics Multiple R 0.862675 R Square 0.744208 Adjusted R Square 0.707666 Standard Error 6.02142 Observations 9 ANOVA df SS MS F Significance F Regression 1 738.4198 738.4198 20.36599 0.002756 Residual 7 253.8025 36.25749 Total 8 992.2222…sample of trucks and their "static weight" and "weight in motion" weights are in thousands of pounds. What percent of the variability in static weight can be explained by the linear model rounded to the nearest 10th?Water is being poured into a large cone shape cistern. The volume of water measured and centimeters cubed is reported at different time intervals measured in seconds. A regression analysis was completed and is displayed in the computer output. what is the equation of the lease squared regression line?
- find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. In each case, there is sujficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. Altitude and Temperature Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded by the author during Delta Flight 1053 from New Orleans to Atlanta. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet).You want to look at an ANOVA table of a regression in which a dependent variable is predicted using an intercept and one slope coefficient. Unfortunately, as you want to look at the table, you knock over your coffee mug which smudges out some of the numbers. Here is what you still can read: • n=7 • F-ratio = 15 • Residual sum of squares (RSS) = 16 • t-score of the slope coefficient = 3.873 How big is the explained sum of squares (ESS)? a 44 b 52 c 48 d 40 How big is the total sum of squares (TSS)? a 64 b 52 c 60 d 56 How big is the explained R-squared? a 0.7 b 0.75 c 0.8 d Cannot be determined What's the p-value for the F-ratio? a 0.012 b 0.024 c 0.036 d…Louis Katz, a cost accountant at Papalote Plastics, Inc. (PPI), is analyzing the manufacturing costs of a molded plastic telephone handset produced by PPI. Louis's independent variable is production lot size (in 1,000's of units), and his dependent variable is the total cost of the lot (in $100's). Regression analysis of the data yielded the following tables. Coefficients Standard Error t Statistic p-value Intercept 3.996 1.161268 3.441065 0.004885 x 0.358 0.102397 3.496205 0.004413 Source df SS MS F Se = 0.898 Regression 1 9.858769 9.858769 12.22345 r2 = 0.526341 Residual 11 8.872 0.806545 Total 12 18.73077 Using a = 0.05, Louis should ________________.
- An agribusiness performed a regression of wheat yield (bushels per acre) using observations on 21 test plots with four predictors (rainfall, fertilizer, soil acidity, hours of sun). The standard error was 1.02 bushels.Suppose you examined blood of 36 patients with the aim to study the relation between sugar level in blood (in mg/dL) and the amount of artificial sweetener (measured in grams). Your regression shows: blood=7.1 + 0.4*sweatener - 0.2*female. What is the most precide interpretation of the estimated coefficient for the constant?Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R² = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year State the trend line (regression line). y= 3.0161 x -5819.5 year number of vehicle registrations R^2 = 0.9695 not enough information to determine Registrations (in millions)