A B 1 Cost to supplier ('000$) Price for Consumer ('000$) IN 5.339 5.932 4.73 7.49 5.198 5.732 4.442 7.256 4.897 6.104 4.312 7.122 5.327 7.492 LD 00 5.165 6.639 10 5.322 6.401 11 4.203 6.367 12 4.562 7.069 13 4.228 6.176 14 3.998 6.707 15 4.09 5.699 16 4.346 7.39 17 4.204 6.478 18 4.235 6.832 19 4.958 6.946 20 4.491 6.088 21 4.062 7.006 22 4.929 6.027 23 4.322 6.289 24 5.43 6.608 25 5.011 7.398 26 4.946 5.754 27 4.968 6.301 28 4.861 6.129 29 4.135 6.933 30 3.698 6.005 31 5.322 7.397 32 3.872 6.067 33 3.784 5.904 34 3.862 5.566 35 4.056 6.902 36 5.416 6.749 37 4.614 5.9 38 3.96 7.083 39 5.264 6.04 40 4.331 7.49 41 4.433 6.058 42 5.055 7.178 43 3.562 7.366 44 4.177 5.891 45 4.204 6.247 46 4.629 7.14 47 4.93 6.396 48 4.452 6.681 49 3.779 5.754 50 4.19 6.475 51 5.051 6.122 52The local council wishes to develop a model to predict the relationship between prices to install solar panels in dollars and the cost to suppliers. The Excel data file Solar.xIsx, located in the folder LBRT #3 > LBRT #3 Data Files, contains the data for fifty responders that installed solar panels and from fifty suppliers. Use Excel Data Analysis to estimate a linear model for the relationship, as well as a 94% confidence interval for the slope and a residual plot. State all numerical answers below correct to four decimal places using the Excel output results. 1. the intercept 2. the slope coefficient , and 3. the standard error of the estimate 4. Using this model, predict the price of installing a solar panel if the cost is $4.3k for the suppliers. Use all decimal places in your calculation by selecting and using the values of bo and b1 in the output generated by Excel. Note: Write your answer in $'000. 5. Does the prediction involve extrapolationg the relationship? Type yes or no. From the output for 94% confidence interval for the slope coefficient report 6. the lower bound and 7. the upper bound