1. Developing a model to estimate demand for mobile apps. For this you have access to...
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1. Developing a model to estimate demand for mobile apps. For this you have access to a large volume of app level data (in a file called GlobalMobile AppsExercise.csv), including information about the 'rank' of the app on the app store. Assume rank = 1/sales. Rank= 3.493+ 1.159*app_store (Apple) + 1.196*app_store (Google)-0.17* region (US)- 0.089*in_app_purchase (plug-in purchase) +0.294*app_type (free) + 0.276*app_type (grossing) + 0.15* log (1+price) +0.0013*app_age_current_version-0.035*log (file size) +0.12*log (num_screenshot)-0.032*average_rating 1. Developing a model to estimate demand for mobile apps. For this you have access to a large volume of app level data (in a file called GlobalMobile AppsExercise.csv), including information about the 'rank' of the app on the app store. Assume rank = 1/sales. Rank= 3.493+ 1.159*app_store (Apple) + 1.196*app_store (Google)-0.17* region (US)- 0.089*in_app_purchase (plug-in purchase) +0.294*app_type (free) + 0.276*app_type (grossing) + 0.15* log (1+price) +0.0013*app_age_current_version-0.035*log (file size) +0.12*log (num_screenshot)-0.032*average_rating
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