Question

Instructions: The following is the recorded earthquakes on South Carolina from August, 2016 to February, 2017. Use the data to find the residuals. Then draw a residual plot by hand. Use the residual plot to determine if the linear model is the best regression model for this data.

Magnitude Depth (km. )

[Table]

1. 7 2. 9

1. 1 0. 8

1. 4 1. 9

0. 7 3. 2

0. 8 4. 3

1. 9 4

1. 7 6. 3

1. 9 6. 9

1. 9 0. 9

1. 1 2

Source: USGS


x Residual (Round to nearest tenth)

1. 7 Answer

1. 1 Answer

1. 4 Answer

0. 7 Answer

0. 8 Answer

1. 9 Answer

1. 7 Answer

1. 9 Answer

1. 9 Answer

1. 1 Answer

Answer 1

To find the residuals for earthquake data, subtract the predicted values from the actual values. Then, plot the residuals on a residual plot to determine if the linear model is the best regression model for the data.

Step-by-step explanation:

To find the residuals for the given earthquake data, we need to subtract the predicted values from the actual values. The predicted values can be obtained from the linear regression equation. Let's assume the linear regression equation is y = mx + b, where y represents the depth of the earthquake and x represents the magnitude. The residual can be calculated as the actual depth minus the predicted depth:

Residual = Actual Depth - (m * Magnitude + b)

After calculating the residuals, we can plot them on a residual plot by graphing the residuals against the magnitude values. We can then analyze the residual plot to determine if the linear model is the best regression model for this data. If the residuals are randomly scattered around the horizontal axis and there is no clear pattern or trend, it indicates that the linear model is a good fit for the data.

Answer 2

1.7 = -0.7

1.1 = -2.1

1.4 = -1.4

Unsure about 0.7

0.8 = 1.7

1.9 (unsure about both)

1.1 = -0.9

Step-by-step explanation:

Hope this helps :)))