The following data resulted from a study commissioned by a large management consulting company to investigate the relationship between amount of job experience (months) for a junior consultant and the likelihood of the consultant being able to perform a certain complex task. (image w/ success and failure)  Interpret the accompanying MINITAB logistic regression output, and sketch a graph of the estimated probability of task performance as a function of experience. (2nd image)

To determine characteristics associated with Y = whether a cancer patient achieved remission (1 = yes), a study used logistic regression. The most important explanatory variable was a labeling index (LI) that measures proliferative activity of cells after a patient receives an injection of tritiated thymidine. It represents the percentage of cells that are “labeled.” Table 4.8 shows the grouped data. Software reports Table 4.9 for a logistic regression model using LI to predict π = P (Y = 1). A. Show how software obtained π ̂ = 0.068 when LI = 8. B. Show that π ̂ = 0.50 when LI = 26.0 D. The lower quartile and upper quartile for LI are 14 and 28. Show that π ̂ increases by 0.42, from 0.15 to 0.57, between those values. E. When LI increases by 1, show the estimated odds of remission multiply by 1.16

A popular television show recently released a video previewing the upcoming season on his website as fans of the show discovered the video the number of views of the preview video has grown each day during the last two weeks the number of days in the release of the video and the natural log of the number of video views as shown in the scatterplot. based on the scatterplot and residual plot, what type of model would be appropriate for summarizing the relationship between days and numbers of views? an exponential model is appropriate because the Residual plot does not show a clear pattern A linear model is appropriate because of scatterplot shows a strong positive linear relationship A power model is appropriate because the scatterplot of days a natural log of use is strong and linear an exponential model is appropriate because the relationship between the days in the natural log of views in linear and the residual plot does not show a clear pattern

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