If the analysis of variance​ F-test leads to the conclusion…

If the analysis of variance​ F-test leads to the conclusion that at least one of the model parameters is​ nonzero, can you conclude that the model is the best predictor for the dependent variable​ y? Can you conclude that all of the terms in the model are important for predicting​ y? What is the appropriate​ conclusion?    

Please use following details to answer Q 18 The abandon rate…

Please use following details to answer Q 18 The abandon rate of a call center is a critical variable in influencing customer satisfaction.  A high abandon rate indicates that customer calls are not getting their questions answered in a timely fashion resulting in high frustration levels.   Management has established a target of no more than 10% abandoned calls.  There are several key variables that impact the abandon rate of the call center.  In the empirical regression model, these variables include the following: Lost calls (%). Percent of incoming calls abandoned by the member.  Wait time (in seconds) as measured from the first ring of the customer call until the call is answered by a Customer Service Representative System response time (in seconds). Length of time it takes the system to respond to a request for information Number of Customer Service Reps logged onto the system Volume of calls (thousands of calls) Therefore, Lost calls = f(Wait time, sysresponse, CSRs, Callvol) A linear multiple regression model as shown below was fitted to the hypothesized relationship above. Based on the linear regression model below, does the model have significant overall fit for data ?