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Test the model for Joint significant of all regressors at 5% level

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Consider a model estimated on a sample of 1000 movies from the Kinopoisk. The model predicts the movie rating depending on the budget, actors' popularity and genre (drama, action, comedy, others). Variables: rating - the index of fil popularity from 0 to 10 ; budget - amount spent on the production of the movie (in 1000$ ); actors' popularity - the cumulative popularity index of the actors acting in the movie (in percentage points); drama, action, comedy - dummy variables indicating genre ( 1 or 0). rating i=+1 budget i+2 actors popularity yi+3 drama i+4 action i+5 comed i+i R2=0.4TSS=2542.20N=1000 cov(1,2)=0.4ratingi=1.6(0.826)+0.81(0.021)budgeti+0.12(0.008)actorspopularityi+0.2(0.167)dramai+0.33(0.05)actioni+0.041(0.023)comedyi())() Consider a model estimated on a sample of 1000 movies from the Kinopoisk. The model predicts the movie rating depending on the budget, actors' popularity and genre (drama, action, comedy, others). Variables: rating - the index of fil popularity from 0 to 10 ; budget - amount spent on the production of the movie (in 1000$ ); actors' popularity - the cumulative popularity index of the actors acting in the movie (in percentage points); drama, action, comedy - dummy variables indicating genre ( 1 or 0). rating i=+1 budget i+2 actors popularity yi+3 drama i+4 action i+5 comed i+i R2=0.4TSS=2542.20N=1000 cov(1,2)=0.4ratingi=1.6(0.826)+0.81(0.021)budgeti+0.12(0.008)actorspopularityi+0.2(0.167)dramai+0.33(0.05)actioni+0.041(0.023)comedyi())()

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