A commercial vegetable and fruit grower carefully observes the relationship between the per-acre amount of fertilizer used on a certain variety of pumpkin and the extra revenue made from the sales of the resulting pumpkin crop. These observations are recorded in the following table Amount of fertilizer 250 500 750 1000 1250 1500 1750 2000 (pounds/acre) Extra revenue earned 288 435 516 555 576 588 594 597 (dollars/acre) The fertilizer costs 42 cents per pound. What would you advise the grower is the most profitable amount of fertilizer to use?

The regression model y = 5.5(1.025)* represents the number of items sold in millions (y) by a company each year (x) after 2010. Select all of the appropriate statements that apply to the model. O The number of items sold each year grows by 2.5%. O There were originally 550,000 items sold. O There were approximately 4.3 million items sold in 2000. O There will be approximately 7 million items sold in 2020. O There will be approximately 8 million items sold in 2030.

Using the regression to model annual income, a variable for years of education has a slope = 2000. This means that the model predicts each additional year of education will yield an extra 2,000 for the average person's salary, regardless of how many total years of education a person has.  A. True B. False

Data contains brain mass in different species versus glia-neuron ratio, the latter being a measurement of brain metabolism as the glia provides the metabolic needs of the neurons.  The relationship between THE LOGARITHM of the brain mass (in the third column) and Glia-neuron ratio (fourth column) appears linear and it is these two variables that we wish to analyze via linear regression.  We would like to know if the human brain fits the trend from the other species.  Towards this end we will perform the regression on all species EXCEPT humans (Homo sapiens).  Again, throw out the human data from your analysis.  You will however need the human numbers for some of the questions.    What is the coefficient of determination (R2) for the data? What is the standard error of the slope of the regression line (SEb) ?