Consider the non-linear model:    sales = a + b * exp (c * advertising_spend).    Where a represents baseline sales, b is a scaling factor, and c is the growth rate of sales in response to advertising spend. If c = 0.03, by how much would sales increase on average for a $10,000 increase in advertising spend from an initial spend of $50,000? Additionally, consider if diminishing returns begin to take effect.     What is the percentage increase in sales for the $10,000 increase from $50,000 to $60,000?

refer to below table ,Conduct a sensitivity analysis to determine the sensitivity of NPV to changes in the sales price, number of units sold, the variable costs per unit, fixed costs and the cost of capital. Set these variables’ values at 10% above and 10% below their base-case values. 2. Include a graph in your analysis with below table? 10% above   Year Net Cash Flow (RM) Discount Rate (13.20%) Present Value (RM)     0 -1,217,800.00 1 -1217800     1 328,750.00 0.883392 290415.19     2 337,330.00 0.780382 263246.2     3 346,423.15 0.689383 238818.31     4 355,195.10 0.608996 216312.32     5 614,461.20 0.537982 330569.16         NPV 121561.19                         10% below   Year Net Cash Flow (RM) Discount Rate (10.80%) Present Value (RM)     0 -1,145,800.00 1 -1145800     1 184,000.00 0.902527 166064.98     2 185,395.00 0.814555 151014.45     3 189,459.85 0.735158 139282.93     4 193,936.89 0.6635 128677.14     5 448,143.25 0.598827 268360.17…

Show with a formula that describes the average estimatesustainable sales growth. Then, make a clear description and systematically about the relationship between its variables. What if a company doesn't experiencing “retention profit”?

A manager uses regression to express sales as a function of advertising expenditures (X1), and per capita income (X2) in your sales area. The following multiple linear regression equation is developed:   Y = 10 + 0.51X1 + 0.45X2 The coefficient of determination is 0.96   Determine which of the following conclusions is valid regarding the coefficient of determination:   Multiple Choice   The coefficient of determination should always be greater than one.   More analysis is needed. The coefficient of determination leaves much unexplained.   The coefficient of determination is positive because the constant term is positive.   The regression line fits the data used in the sample very well. There is a strong indication of the relationship of the two variables with sales.