Answer:
Look for the y-intercept where the graph crosses the y-axis. Look for the x-intercept where the graph crosses the x-axis. Look for the zeros of the linear function where the y-value is zero.
Step-by-step explanation:
Hope it helps you
Please mark it as brainliest
Sorry for taking so long, it wont let me type a while ago. I have it all fix now hehe. I took a picture of my work, ask me if you still don’t understand.
Answer:
3 * 20s
Step-by-step explanation:
In order to find out how much Mr. Hartman will spend in total we first need to multiply the price of the keyboard and mouse by the number of computers in a single computer station. Once we have these products we add them together. Finally, we multiply this new value by 3 since there are a total of 3 computer stations. If we turn this into an expression it would be the following...
3 * (13.50s + 6.50s)
We can even simplify this by first adding the cost of the keyboard and mouse and then multiplying by s
3 * 20s
Answer: There is not a good prediction for the height of the tree when it is 100 years old because the prediction given by the trend line produced by the regression calculator probably is not valid that far in the future.
Step-by-step explanation:
Years since tree was planted (x) - - - - height (y)
2 - - - - 17
3 - - - - 25
5 - - - 42
6 - - - - 47
7 - - - 54
9 - - - 69
Using a regression calculator :
The height of tree can be modeled by the equation : ŷ = 7.36X + 3.08
With y being the predicted variable; 7.36 being the slope and 3.08 as the intercept.
X is the independent variable which is used in calculating the value of y.
Predicted height when years since tree was planted(x) = 100
ŷ = 7.36X + 3.08
ŷ = 7.36(100) + 3.08
y = 736 + 3.08
y = 739.08
Forward prediction of 100 years produced by the trendline would probably give an invalid value because the trendline only models a range of 9 years prediction. However, a linear regression equation isn't the best for making prediction that far in into the future.
