What is 60.046 in expanded form
1 answer:
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ANSWER
D. As the x-values increase, the y-values would decrease
EXPLANATION
The given function is
The slope of this function is
Since the slope is negative, there is a negative or an inverse relationship between x and y.
As the values of x increases, the values of y decreases.
Also, as the values of x decreases, the values of y increases.
The first option is not true because as x is becoming bigger and bigger negatively, y will become positive.
For instance, when
This implies that,
Options B is obviously not true because the function has a negative relationship between x and y.
Option C is also false because, x can be positive since it is the independent variable.
See graph
Therefore, the correct answer is option D.
D. As the x-values increase, the y-values would decrease
EXPLANATION
The given function is
The slope of this function is
Since the slope is negative, there is a negative or an inverse relationship between x and y.
As the values of x increases, the values of y decreases.
Also, as the values of x decreases, the values of y increases.
The first option is not true because as x is becoming bigger and bigger negatively, y will become positive.
For instance, when
This implies that,
Options B is obviously not true because the function has a negative relationship between x and y.
Option C is also false because, x can be positive since it is the independent variable.
See graph
Therefore, the correct answer is option D.
Answer:
The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:
Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:
The two parameters are:
who represent the mean and is on the center of the distribution
who represent the standard deviation
One particular case is the normal standard distribution denoted by:
Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated
Step-by-step explanation:
The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:
Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:
The two parameters are:
who represent the mean and is on the center of the distribution
who represent the standard deviation
One particular case is the normal standard distribution denoted by:
Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated