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.
What is y={-\dfrac{1}{3}}x-9y=− 3 1 x−9y, equals, minus, start fraction, 1, divided by, 3, end fraction, x, minus, 9 written i
Kobotan [32]
Answer:

Step-by-step explanation:
We are given that

We have to find the standard form of given equation


By using multiplication property of equality

We know that
Standard form of equation

Therefore, the standard form of given equation is given by

in the equation as we can say x= 2y-10.
so, substitute x=2y-10 everywhere then the x in 1240 gets cancelled with 2y-10 then solve the remaining you will get 4y-20+3y=1240
7y=1260
y=1260/7
y=180
then substitute the value of y everywhere
2x+3y=1240
2x+3(180)=1240
2x=1240-540
2x=700
x=350
DONE.
Answer:
-20+1 every minute
Step-by-step explanation:
-4(x + 3) < = -2 - 2x
-4x - 12 < = -2 - 2x
-4x + 2x < = -2 + 12
-2x < = 10
x > = -5
the correct number line will have closed circle on -5 with shading to the right