An example of a trig function that includes multiple transformations and how it is different from the standard trig function is; As detailed below
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How to interpret trigonometric functions in transformations?</h3>
An example of a trigonometric function that includes multiple transformations is; f(x) = 3tan(x - 4) + 3
This is different from the standard function, f(x) = tan x because it has a vertical stretch of 3 units and a horizontal translation to the right by 4 units, and a vertical translation upwards by 3.
Another way to look at it is by;
Let us use the function f(x) = sin x.
Thus, the new function would be written as;
g(x) = sin (x - π/2), and this gives us;
g(x) = sin x cos π/2 - (cos x sin π/2) = -cos x
This will make a graph by shifting the graph of sin x π/2 units to the right side.
Now, shifting the graph of sin xπ/2 units to the left gives;
h(x) = sin (x + π/2/2)
Read more about Trigonometric Functions at; brainly.com/question/4437914
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Step-by-step explanation:
(9-4)/(5+7)= 5/12
y - 4 = 5/12(x + 7)
y - 48/12 = (5/12)x + 35/12
y = (5/12)x + 83/12
Answer:
Step-by-step explanation:
Recall that a horizontal translation (shift) in 3 units to the right involves directly subtracting 3 from the variable x (horizontal axis variable) , and that moving the function up 5 units involves adding to the whole function 5 units. That is:
If she works 40 hours getting paid $12 an hour she will get $480
Answer: Choice C
Amy is correct because a nonlinear association could increase along the whole data set, while being steeper in some parts than others. The scatterplot could be linear or nonlinear.
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Explanation:
Just because the data points trend upward (as you go from left to right), it does not mean the data is linearly associated.
Consider a parabola that goes uphill, or an exponential curve that does the same. Both are nonlinear. If we have points close to or on these nonlinear curves, then we consider the scatterplot to have nonlinear association.
Also, you could have points randomly scattered about that don't fit either of those two functions, or any elementary math function your teacher has discussed so far, and yet the points could trend upward. If the points are not close to the same straight line, then we don't have linear association.
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In short, if the points all fall on the same line or close to it, then we have linear association. Otherwise, we have nonlinear association of some kind.
Joseph's claim that an increasing trend is not enough evidence to conclude the scatterplot is linear or not.
