Answer:
m : the slope of the line.
( x, y ) : any point on the line.
( x1, y1 ) : a given point on the line.
Answer: It is usefull.
Step-by-step explanation:
The regression squared talks to us about how well the model fits in the experimental data, where 0.0 means that the model does not fit at all, and 100% means that the model fits perfectly.
This is always true? well, really not, there are cases where you can have a regression square of 0.98, which would imply that the model is correct, but when you see the residual vs fit the plot, you may see some pattern, which implies that there is a problem with the model (you always expect to see randomness when you look at this graph). While for a prediction, this actually may work (at least in the range of the data points, outside this range the model and the data may not coincide at all)
Now, it still is useful in a certain range, so we can actually conclude that if R^2 = 0.949 represents a model that is useful for predicting the exam marks.
The answer is D. x/11
Say you need to find the xth place in the sequence. Based on the fact that the 1st place is 1/11, the 2nd place is 2/11, and so on, to find the value of the xth place in the sequence the answer is x/11.
Answer: 2(N+15) = 6N
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We let N be the number.
Then, "<span>the sum of a number and fifteen" would be
N + 15
Two times this sum would give us
2(N+15) ... you must distribute!
This must be equal to six times the number. Six times the number is 6N, therefore
2(N+15) = 6N</span>
The roots (zeros) are the x values where the graph intersects the x-axis. To find the roots (zeros), replace y with 0 and solve for x.
Answer:
x = -9
