The graph is vertically stretched by a factor of 2 and translated 3 units right when it is transformed. Option A is correct.
<h3>What is transformation of a function?</h3>
Transformation of a function is shifting the function from its original place in the graph.
Types of transformation-
- Horizontal shift- Let the parent function is f(x). Thus by replacing parent function with f(x-b) shifts the graph b units right and by replacing parent function with f(x+b) shifts the graph b units left.
- Vertical shift- Let the parent function is f(x). Thus by replacing parent function with f(x)-c shifts the graph c units down and by replacing parent function with f(x)+c shifts the graph c units up.
The given function is,
This function is changed to the function,
Here the 3 units is substrate in the function. Thus, it is shiftet 3 units right. The number 2 is multiplied in the function which vertically stretched the graph by a factor of 2.
Thus, the graph is vertically stretched by a factor of 2 and translated 3 units right when it is transformed. Option A is correct.
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When n is small (less than 30), how does the shape of the t distribution compare to the normal distribution then"it is flatter and wider than the normal distribution."
<h3>What is normal distribution?</h3>
The normal distribution explains a symmetrical plot of data around the mean value, with the standard deviation defining the width of the curve. It is represented graphically as "bell curve."
Some key features regarding the normal distribution are-
- The normal distribution is officially known as the Gaussian distribution, but the term "normal" was coined after scientific publications in the nineteenth century demonstrated that many natural events emerged to "deviate normally" from the mean.
- The naturalist Sir Francis Galton popularized the concept of "normal variability" as the "normal curve" in his 1889 work, Natural Inheritance.
- Even though the normal distribution is a crucial statistical concept, the applications in finance are limited because financial phenomena, such as expected stock-market returns, do not fit neatly within a normal distribution.
- In fact, prices generally follow a right-skewed log-normal distribution with fatter tails.
As a result, relying as well heavily on the a bell curve when forecasting these events can yield unreliable results.
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Answer:
b
Step-by-step explanation:
Answer:
(x-6)^2+(y-14)^2=4
Step-by-step explanation:
