Jessica and Paul run a company that provides IT support to local nonprofits and public organizations. To better estimate their staffing needs, they have been recording data on the number of support calls received from their clients per day, as shown in the “ITCalls” Excel file.they also recorded the value of several other attributes:ActiveContracts – the number of clients with whom they are workingAverageClientSize – the median size of their current clients (measured by # of employees)NewSoftwareReleased – a binary variable specifying whether or not there was a new software release that day that would be relevant to their clients; a 0 indicates no new release, and a 1 indicates a new release.Run a regression model in either Excel or RapidMiner to predict the number of calls in a given day based on the three other attributes. If using RapidMiner, be sure to change the role of Calls to label when importing, and in the Linear Regression operator, set the feature selection parameter to none. Use your regression model to answer the following questions:
1) What does the coefficient on ActiveContracts tell us? Be as specific as possible.
2) What does the coefficient on NewSoftwareReleased tell us? Be as specific as possible (Note that it is binary; its only possible values are 0 and 1.)
3) Is AverageClientSize significant? How can you tell?
4) Using this model, predict the number of calls on a day in which there are 10 active contracts, the average client size is 25, and no new software was released.
5) Would we get a better model if we removed any of these attributes? If so, which one(s)? If not, why not?
6) Jessica and Paul suspect that calls might be higher on some days of the week than others.However, a text attribute can’t be used in a regression model. What should be done to allow the day of the week to be included in the regression model along with the other attributes? How would you do it? (You do not have to actually build the model.)
We value our customers and so we ensure that what we do is 100% original..
With us you are guaranteed of quality work done by our qualified experts.Your information and everything that you do with us is kept completely confidential.
You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.Read more
The Product ordered is guaranteed to be original. Orders are checked by the most advanced anti-plagiarism software in the market to assure that the Product is 100% original. The Company has a zero tolerance policy for plagiarism.Read more
The Free Revision policy is a courtesy service that the Company provides to help ensure Customer’s total satisfaction with the completed Order. To receive free revision the Company requires that the Customer provide the request within fourteen (14) days from the first completion date and within a period of thirty (30) days for dissertations.Read more
The Company is committed to protect the privacy of the Customer and it will never resell or share any of Customer’s personal information, including credit card data, with any third party. All the online transactions are processed through the secure and reliable online payment systems.Read more
By placing an order with us, you agree to the service we provide. We will endear to do all that it takes to deliver a comprehensive paper as per your requirements. We also count on your cooperation to ensure that we deliver on this mandate.Read more