<em>Rearrange unknown terms to the left side of the equation</em>
![\boldsymbol{\sf{ 9x > 50.4-9 \ \ \longmapsto \ \ \ [Subtract]}}](https://tex.z-dn.net/?f=%5Cboldsymbol%7B%5Csf%7B%20%209x%20%3E%2050.4-9%20%5C%20%5C%20%5Clongmapsto%20%5C%20%5C%20%5C%20%5BSubtract%5D%7D%7D)
<em>Calculate the sum or difference.</em>

<em>Convert decimal to fraction.</em>

<em>Reduce the greatest common factor for both sides of the inequality.</em>
<em> </em>
<em>Reduce the fraction</em>

Can you please take another picture that is closer to the diagram, it's quite blurry.
To solve this you must simply add $2.10 + $4.45 together to get a sum of $6.55. Next, you must subtract the $6.55 from $13.50 to get a difference/final solution of $6.95. So, in conclusion, Luke made a profit of $6.95 from mowing the lawn.
Answer:
Residual = -2
The negative residual value indicates that the data point lies below the regression line.
Step-by-step explanation:
We are given a linear regression model that relates daily high temperature, in degrees Fahrenheit and number of lemonade cups sold.

Where y is the number of cups sold and x is the daily temperature in Fahrenheit.
Residual value:
A residual value basically shows the position of a data point with respect to the regression line.
A residual value of 0 is desired which means that the regression line best fits the data.
The Residual value is calculated by
Residual = Observed value - Predicted value
The predicted value of number of lemonade cups is obtained as

So the predicted value of number of lemonade cups is 23 and the observed value is 21 so the residual value is
Residual = Observed value - Predicted value
Residual = 21 - 23
Residual = -2
The negative residual value indicates that the data point lies below the regression line.