the following questions, referencin the models and information. Type your responses in the spaces below. a. Simple correlation = b. ____YES _____NO _____Unable to determine the answer The reason is... c. ____YES _____NO _____Unable to determine the answer The reason is... ____YES _____NO _____Unable to determine the answer d. The reason is... e. f. g. h. ____MODEL 1 ____MODEL 2 ____MODEL 3 The reason is... i. j. _____Degrees of freedom _____t-multiple _____ME Lower bound:_____ hundred units Upper bound : ____ hundred units Universal Studios is developing a model to predict first week number of tickets sold to its non-animated movies. Universal collects information on 17 recent releases and wants to identify those characteristics that are related to TICKETS. TICKETS Number of tickets sold in the first week (in millions of tickets) COST Production plus marketing cost (in millions of dollars) THEATRE Number of theatres (in hundreds of theatres) HOLIDAY = 1 if the movie opened on a holiday weekend DRAMA = 1 if the movie is a dramatic movie (ex. Twilight Saga) ACTION = 1 if the movie is an action adventure movie (ex. Pirates of the Caribbean SUPERHERO = 1 if the movie is a superhero movie (ex. Spiderman) CMO =1 if the movie is a comedy/musical other movie (excluded category) The data was used to fit the following three models in which the dependent variable is TICKETS MODEL 1: Multiple Regression for tickets Multiple Adjusted StErr of R-Square Summary R-Square R 0.8973 Estimate 0.8051 0.7922 3.3093 Sum of Squares Mean of Squares F---Ratio Degrees of ANOVA Table Freedom 1 15 Explained Unexplained 678.7886 164.2702 Coefficient t---Value p---Value 3.9855 0.0944 1.8490 7.8729 0.0843 0.0000 p---Value 678.7886 10.9513 Standard Error Confidence Interval 95% Lower Upper Regression Table Constant cost 2.1556 0.0120 8.5800 0.0689 0.6089 0.1200 MODEL 2: Multiple Regression for tickets Multiple Adjusted StErr of Estimate R---Square Summary R R---Square 0.9405 0.8846 0.8579 2.7362 Sum of Squares Mean of Squares F---Ratio p---Value Degrees of ANOVA Table Explained Unexplained Freedom 3 13 745.7338 97.3251 248.5779 7.4865 Coefficient Standard Error t---Value p---Value Confidence Interval 95% Lower Upper 2.1404 0.0491 2.0814 0.0181 1.0284 2.7071 0.3225 0.0180 1.6813 3.3123 0.7985 2.1165 2.1056 1.5650 0.0552 0.1416 6.6369 0.0099 value 1.2602 Regression Table Constant cost theatre holiday 2.3561 0.0883 suppressed 7.8848 MODEL 3: Multiple Regression for tickets Summary Multiple R-Square R Adjusted StErr of R-Square Estimate 2.6654 0.9569 0.9157 0.8652 Degrees of Sum of Mean of ANOVA Table Freedom Squares Squares Explained 6 10 772.0149 71.0439 F---Ratio Unexplained 128.6691 7.1044 p---Value Standard Coefficient Regression Table Constant cost theatre holiday drama action superhero Confidence Interval 95% t---Value p---Value Error 4.9852 0.0513 1.7970 4.1837 0.8494 2.7367 0.0201 0.8259 2.1604 2.3351 1.8216 value 2.1758 1.9365 0.3637 0.0985 suppressed 0.0546 0.0816 0.7236 2.3487 3.6062 2.0283 1.9935 1.1580 1.8090 0.2738 0.1006 Lower Upper 11.0829 0.0066 0.0432 0.6301 4.3535 2.1705 0.8355 1.1124 0.0961 3.6371 8.9974 a) What is the value of the simple correlation between TICKETS and COST? b). If you are able to determine the answer, is showing the film in more theatres associated with higher ticket sales (with cost and holiday opening held constant) with = 0.05? (Justify your response). c) If you are able to determine the answer, do higher cost movies have higher ticket sales (with THEATRE, HOLIDAY and movie genre held constant) with = 0.05? (Justify your response). d) If you are able to determine the answer, do movies opening on holiday weekends have different ticket sales than those opening on non-holiday weekends (with COST held constant) with = 0.05? (Justify your response). e) Interpret the coefficient for COST in Model 1 (that is, interpret the estimated value of 0.0944 without considering whether or not this value is \"statistically significant\"). f) Interpret the coefficient for ACTION in Model 3 (that is, interpret the estimated value of 2.3487 without considering whether or not this value is \"statistically significant\"). g) Interpret the coefficient for THEATRE in Model 2 (that is, interpret the estimated value of 1.6813 without considering whether or not this value is \"statistically significant\"). h) Which model would you recommend to predict TICKETS with = 0.05? (Justify your response). i) Based on model 3, predict TICKETS for a superhero movie opening in 3500 theatres on a holiday weekend that cost $150,000,000. Use all variables in Model 3 to obtain your prediction even if some of them are not \"statistically significant\". j) What is the 95% prediction interval for your prediction in part i)? 6.0522 6.8679 8.0479