The table shows the mileages x (in thousands of miles) and the selling prices y (in thousands of dollars) of several used automobiles of the same year and model. Mileage, x: 22 14 18 30 8 24
Price, y: 16 17 17 14 18 15
a.) Use a graphing calculator to find the equation of the line of best fit. Round the slope to the nearest tenth and y-intercept to the nearest integer.
y=
b.) Identify the correlation coefficient. Round to the nearest thousandth.
r=
Interpret the correlation coefficient.
the data show a ___ ___ correlation.

The line of best fit has an equation of:

y = -0.1875x + 19.625

A linear equation is given by:

y = mx + b;

where y, x are variables, m is the slope of the line and b is the y intercept.

Let x represent the mileages (in thousands of miles) and y the selling prices(in thousands of dollars) of used automobiles.

Plotting the points using geogebra graphing calculator, the line of best fit has an equation of:

y = -0.1875x + 19.625

Therefore the slope is -0.1875 and the y intercept is 19.625

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ŷ = -0.18363X + 19.71681

-0.9685

Step-by-step explanation:

Given the data:

Mileage, x: 22 14 18 30 8 24

Price, y: 16 17 17 14 18 15

Using the online regression calculator :

The regression equation obtained is :

ŷ = -0.18363X + 19.71681

Where ;

y = predicted variable

- 0.18363 = slope or gradient

X = predictor variable

19.71681 = intercept

The correlation Coefficient R = -0.9685

This signifies a strong negative relationship between the x and y variable.

all but the second one

step-by-step explanation:

cuz that one goes over 180

mark brainliest

it would be:

c.parallelogram.