Lets think of it this way:-
1/2 is one half
Whats half of 12? 6
Now, 7 is greater than 6, which means the fraction 7/12 is greater than 1/2
Answer: 7/12 is bigger
3 1/2 gallons of white paint is 61.25
1 3/4 gallons of blue paint is 33.25
so the total is 94.50 dollars
Answer:
A
Step-by-step explanation:
In the slope-intercept form (y=mx+c), the coefficient of x is the slope and c is the y-intercept.
<u>g(x)= -6x +3</u>
Slope= -6
y- intercept= 3
<u>f(x)</u>
y- intercept is the point at which the graph cuts through the y- axis, and it occurs at x= 0.
The two points on the graph are (0, 3) and (1, 1).
slope
![= \frac{y1 - y2}{x1 - x2}](https://tex.z-dn.net/?f=%20%3D%20%20%5Cfrac%7By1%20-%20y2%7D%7Bx1%20-%20x2%7D%20)
![= \frac{3 - 1}{0 - 1}](https://tex.z-dn.net/?f=%20%3D%20%20%5Cfrac%7B3%20-%201%7D%7B0%20-%201%7D%20)
![= \frac{2}{ - 1}](https://tex.z-dn.net/?f=%20%3D%20%20%5Cfrac%7B2%7D%7B%20-%201%7D%20)
= -2
y- intercept= 3
Thus, both have different slopes but the same y-intercepts.
Answer:
1/2
Step-by-step explanation:
Simple probability is a ratio of the number of ways the thing we want to happen can to the total possible outcomes.
(For example, we flip a coin and want heads, but it can land on heads or tails. Our probability of getting heads is 1/2, one way to get heads over the 2 possible outcomes)
So for this problem, there's 20 possible things that CAN happen (3 + 7 + 10) and 10 ways we get what we want (a green marble).
Our probability of getting a green marble is
, which simplifies to ![\frac{1}{2}](https://tex.z-dn.net/?f=%5Cfrac%7B1%7D%7B2%7D)
Answer:
True
Step-by-step explanation:
Assume the following
Mean is represented by μ
Standard deviation by σ
Sample mean by x
Sample Size by n
Given that all possible values of a random variable calculated from a sample of size n with a population mean and standard deviation μ and σ, respectively, it's known that the sampling distribution of the sample mean x is its probability distribution.
Having said that, assume that a simple random sample of size n is drawn from a large population with mean μ and standard deviation σ, as stated above.
The sampling distribution of x will be distributed normally as long as the random variable is normally distributed.