ch-7 Disney is grossing more over time because the p-value is positive. Disney i

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Disney is grossing more over time because the p-value is positive. Disney is grossing less over time because the p-value is positive. Disney is grossing more over time because the p-value is negative. Disney is grossing less over time because the p-value is negative. Disney is grossing more over time because the coefficient is positive. Disney is grossing less over time because the coefficient is positive. Disney is grossing more over time because the coefficient is negative. Disney is grossing less over time because the coefficient is negative. Bookmark question for later Can we rely on these results and expect to see something similar as new movies are added? Bookmark question for later Fill in all missing values of mpaa_rating with the value “Empty” Create dummy code features to convert mpaa_rating to sets of numeric 0/1 features for all values except “Empty” Run another MLR a few rows below the previous one using both days_since_release and all of the dummy codes you just created for mpaa_rating What did the inclusion of these dummy coded mpaa_rating features do to the model fit? Options: 1There is no way to tell from these results 2It made the model fit better 3Did not change it at all 4It made the model fit worse 17)Upload the Excel file containing the data and all of your regression models 7,17questions and read the instructions for both questions in assignment document.
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 Chapter 9 Assignment. Here is the Instruction: Follow all the tasks shown in the video clips in Ch 9 and do them yourself while watching the clips. At the End, Turn in the File that You Produce While Watching the Author’s Demonstration. 
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Chapter 10 Assignment. Here is the Instruction: Follow all the tasks shown in the video clips in Ch 10 and do them yourself while watching the clips. At the End, Turn in the File that You Produce While Watching the Author’s Demonstration. 
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 Chapter 7 Logistic Regression Assignment. Submit R File for Codes and Word Document with Your Analysis. 
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 11.6 ML Studio: Algorithm Selection (football and airline) Background You are a data scientist for a major airline that has been collecting customer satisfaction surveys from random customers. You are hoping to better understand what causes your customers to be loyal and come back to your airline whenever they need a flight. Data Use the two csv files below to complete the tasks. airline_satisfaction.csv Dataset details: https://www.kaggle.com/datasets/teejmahal20/airline-passenger-satisfaction nfl_plays_2022.csv Dataset found at: http://www.nflsavant.com/about.php This may is the same dataset used in the feature selection assessment. You do not need to reupload it into ML Studio if you already did so. Task Complete the tasks found in the question details below Download and use the template file provided to track your models and upload it where directed Publish your completed experiment to the AI Gallery and paste the URL where directed 10)Publish your experiment to the AI Gallery and copy/paste the URL below 11)Upload the Excel file template you used to record all of your modeling results.