on for the number of reported dead birds (x) versus the number of human West Nile virus cases (y) is y=−10.2638+0.0491x. If the number of dead birds reported in a year is 732, how many human cases of West Nile virus can be expected?  Also we know r=0.5490.     No prediction can be made.     19.6     26     38.1

The quadratic model for the given data is wrong.

Please help me better understand how to solve this word problem.   In a study of 2000 model cars, a researcher computed the least-squares regression line of price (in collars) on horsepower. He obtained the following equation of: Price = -7000 + 170 X horsepower.  Based on the least-squares regression line, what would we predict the cost of a 2000 model car with horsepower equal to 230 to be (assuming no extrapolation error)?

According to the data reported by the New York State Department of Health regarding West Nile Virus for the years 2000-2004, the least squares line equation for the number of reported dead birds (x) versus the number of human West Nile virus cases (y) is  ŷ = −10.2638 + 0.0491x. Part 1) If the number of dead birds reported in a year is 677, how many human cases of West Nile virus can be expected? (Round your answer to the nearest whole number.) _________ cases

Write down the different Multiple Regression Equations?

An airline has determined that the relationship between the number of passengers (x) on a flight and the total weight (y) (in pounds) of luggage stored in the baggage compartment can be estimated by the least-squares regression equation y = 250 + 27x. Predict the weight of luggage for a flight with 125 passengers.

Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold that day as the response variable. The least squares regression (LSR) line for the data is =-114.05+2.17X. On one of the observed days, the temperature was 85 °F and 66 bags of ice were sold. The number of bags of ice predicted to be sold by the LSR line, y, when the temperature is 85 °F is 70. Using the predicted value, compute the residual at this temperature. Answer:

To monitor and improve its productivity, a company made an investigation and found out that the factor that affects the productivity the most is the absenteeism. The company data analytics department have collected data about the two variables (Productivity and Absenteeism) for the 12 past years as shown in the table below. Now the purpose of the company is to determine, through regression analysis, whether the productivity is statistically affected by the absenteeism level or not. Year Absenteeism Productivity (in number of absent worker) (in Million AED) 1 204 342 2 352 336 3 154 406 4 206 410 5 422 278 6 530 214 7 750 138 8 482 268 9 374 262 10 120 356 11 188 396 12 634 152 Questions: Construct a scatter diagram for the data about productivity and absenteeism then interpret the possible relationship that can be found. Construct a simple regression model to predict the…

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: -a+bx a=-0.761 b-0.063 (a) Write the equation of the Least Squares Regression line of the form

Each month for several months, the average temperature in °C (x) and the number of pounds of steam (y) consumed by a certain chemical plant were measured. The least-squares line computed from the resulting data is y = 245.82 + 1.13x. Predict the number of pounds of steam consumed in a month where the average temperature is 65°C. If two months differ in their average temperatures by 5°C, by how much do you predict the number of pounds of steam consumed to differ?