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Draw a scatter plot of the residuals for each line of best fit for Pick Number vs Career Length and for Pick Number vs Salary Hint: We want to get the predictions for every player in the dataset Hint 2: This question is really involved, try to follow the skeleton code! n [36]: icted_career_lengths = ... icted_salaries = ... er_length_residuals = ... ry_residuals = ... with_residuals = nfl.with_columns("Career Length Residuals", career_length_residuals, "Salary Residuals", salary_residu with_residuals.show(5) w generate two scatter plots! with_residuals.scatter("Pick Number", "Career Length Residuals") with_residuals.scatter( "Pick Number", "Salary Residuals") Player Salary Year Drafted Pick Number Position Career Length Career Length Residuals Salary Residuals Baker Mayfield 570000 2018 1 1 QB 2 Ellipsis Ellipsis Cam Newton 16200000 2011 1 QB 9 Ellipsis Ellipsis Eli Manning 11500000 2004 1 QB 16 Ellipsis Ellipsis Eric Fisher 10350000 2013 1 OT 7 Ellipsis Ellipsis Jadeveon Clowney 15967200 2014 1 DE 6 Ellipsis Ellipsis

Respuesta :

Gather data pairings where there is a possibility of a relationship. With the independent variable on the horizontal axis and the dependent variable on the vertical axis, create a graph. Where the x-axis value and y-axis value overlap for each set of data, place a dot or a symbol.

What makes a scatter plot useful?

To determine the existence of a relationship or correlation between two variables, use a scatter plot. Are you attempting to determine if the combination of your two factors could have any significance. You may find out whether your data points might be related by plotting a scattergram with them.

Which three types of scatter plots are there?

Scatter plots or charts come in three different shapes U-shaped, linear, and exponential. Positive, negative, or no correlation are the three that matter most.

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