Assume a Logistic regression model (Equation 14.20 in the Text Book) . Look at the data and provide a name for the data table (for example, let x = price of stocks and y's a yes or no response (1=yes,0=no) Support your naming convention and explain what management decision Is being made with the data presented. . Find the maximum likelihood estimates of Bo and Bj. State the fitted response function and explain what the parameters of the function represent. . Obtain a scatter plot of the data with both the fitted logistic response function from part 2 and a Lowess smooth superimposed. Does the logistic response function appear to fit well? Describe in detail your response, what makes it fit well. What role does it play in assisting in management decisions? . Find exp(b1) and provide a detailed interpretation of this number. How would the decision maker use this information? . What is the estimated probability associated with x - 407 Explain what the results in relationship to your model and management decision making. . Estimate the increase in x for which 75% of the y values are 0. Explain this relationship as it related to your model and the decision that may result from the increase in your x variable. 41 48 1 1 1