Linearize this model and use it to estimate A and B based on the following data. y=(A).(x).(e³x) 0.2 0.4 0.6 0.9 1.3 1.5 1.7 1.8 *10.75 0.75 1.25 1.45 1.25 0.85 0.55 0.35 0.28 0.18 Develop a Pseudocode for the calculations. Plot your fit along with the data.

The number of banks in a country has been dropping steadily since 1984, and the trend in recent years has been roughly linear. The annual data for the years 1999 through 2008 can be summarized as follows, where x represents the years since 1990 and y the number of banks, in thousands. n=10 Ex-235 ²-5605 Ey-77.564 Ey²=603.80424 Exy-1810.155 a. Find an equation for the least squares line. b. Use your result from part a to predict the number of banks in the year 2020. c. If this trend continues linearly, in what year will the number of banks drop below 6200? d. Find and interpret the correlation coefficient.

Consider the following regression equation: y = -3.9 + 7.2x What does 7.2 depict in the regression equation above? a) The direction of the line.  b) The y-intercept.     c) The point where x = 0.  d) The y when x = 7.2.

The rabbit population at the city park increases by 16% per year. If there are intially 119 rabbits in the city park. 1. Write a model for the population (y) in terms of years (t). y=  2. Find the rabbit population in 17 years. (Round to the nearest whole rabbit)=  3. [Estimate] When the rabbit population reaches 11033. It will happen between year and year