Question

It appears that over the past 50 years, the number of farms in the United States declined while the average size of farms increased. The following data provided by the U.S. Department of Agriculture show five-year interval data for U.S. farms. Use these data to develop the equation of a regression line to predict the average size of a farm (y) by the number of farms (x). Discuss the slope and y-intercept of the model. Year Number of Farms (millions) Average Size (acres) 1950 5.64 212 1955 4.63 254 1960 3.93 297 1965 3.32 344 1970 2.96 377 1975 2.53 421 1980 2.47 426 1985 2.28 438 1990 2.14 463 1995 2.08 472 2000 2.18 434 2005 2.09 441 2010 2.20 419 (5). Use the model to calculate the coefficient of determination (. How to interpret the value of ? Based on your understanding, do we have a good and do we have a good model? (6). Given alpha = 0.05, test if we have a significant negative slope? What is the statistical decision? What is the final conclusion (do we find the model have better predictive power than average (y) model (lazy model))?

Answer 1

ANSWER :

BY USING MS-EXCELL FINDING REGRESSION EQUATION DIRECTLY

THE FOLLOWING STEPS ARE THE PROCESS

Step1 ) Enter data in Excel .

Step 2 ) Select data >>Click on insert >>

We have regression equation y=-71.19x +595

Average Size = -71.19*Number of Farms + 595

Interprete for slope= If number of Forms increase by 1 unit then we predict Average size decreases by 71.19

Interprete for intercept = If number of Forms is 0 then we predict Average size is 595