Answer: x = 34
Step-by-step explanation:
⁴ ⁻ˣ/₅ + ˣ + 2/₃ = 6
Now resolve into fraction and convert to a linear equation
4 - x /₅ + x + 2/₃ = 6
3( 4 -x ) + 5( x + 2 )/15 = 6
3( 4 - x ) + 5( x + 2 ) = 6 x 15
12 - 3x + 5x + 10 = 90
2x + 22 = 90
2x = 90 - 22
2x = 68
x = 34
Using the function concept, it is found that:
- Graph B is a function because each value of x corresponds to exactly one y-value.
In a function, <u>one value of the input can be related to only one value of the output</u>.
- In a graph, it means that for each value of x(horizontal axis), there can be only one respective value of y(vertical axis).
In this problem, at Graph A, when x = 5, for example a vertical line crosses the function 3 times, hence there are 3 respective values of y for x = 5, and the same is valid for other values of x, hence it is not a function.
At Graph B, <u>for each value of x, there is only one value of y</u>, hence it is a function.
Hence:
Graph B is a function because each value of x corresponds to exactly one y-value.
To learn more about the function concept, you can take a look at brainly.com/question/12463448
Answer:
<em>Expected Payoff ⇒ $ 1.50 ; Type in 1.50</em>
Step-by-step explanation:
Considering that 1 out of the 100 tickets will have a probability of winning a 150 dollar prize, take a proportionality into account;

<em>Thus, Solution ; Expected Payoff ⇒ $ 1.50</em>
Answer:
Se=1.2
Step-by-step explanation:
The standard error is the standard deviation of a sample population. "It measures the accuracy with which a sample represents a population".
The central limit theorem (CLT) states "that the distribution of sample means approximates a normal distribution, as the sample size becomes larger, assuming that all samples are identical in size, and regardless of the population distribution shape"
The sample mean is defined as:

And the distribution for the sample mean is given by:

Let X denotes the random variable that measures the particular characteristic of interest. Let, X1, X2, …, Xn be the values of the random variable for the n units of the sample.
As the sample size is large,(>30) it can be assumed that the distribution is normal. The standard error of the sample mean X bar is given by:

If we replace the values given we have:

So then the distribution for the sample mean
is:
