Answer:
f=3d/k
Step-by-step explanation:
Answer:
y = 4/3x - 4
Step-by-step explanation:
to find the equation of a line with 2 points, we use the slope formula which is:
![\frac{y_2-y_1}{x_2-x_1}](https://tex.z-dn.net/?f=%5Cfrac%7By_2-y_1%7D%7Bx_2-x_1%7D)
we will use (6,4) as
and we will use (-3,-8) as
. we plug this into the slope formula:
![\frac{-8-4}{-3-6}](https://tex.z-dn.net/?f=%5Cfrac%7B-8-4%7D%7B-3-6%7D)
-8 - 4 = -12
-3 - 6 = -9
the slope is ![\frac{-12}{-9}](https://tex.z-dn.net/?f=%5Cfrac%7B-12%7D%7B-9%7D)
but we can simplify this further by dividing the fraction by -3
-12 / -3 = 4
-9 / -3 = 3
the simplified version of the slope is ![\frac{4}{3}](https://tex.z-dn.net/?f=%5Cfrac%7B4%7D%7B3%7D)
we can write this in slope-intercept form which is y =mx + b, with b being the y intercept and m being the slope
y = 4/3x + b <--- we need to solve for <em>b</em> in order to find the y intercept, so substitute x & y for a point on the line, we can use any point we are given, but for this example i will use (6,4)
4 = 4/3(6) + b < multiply 4/3 x 6
4 = 8 + b < subtract 8 from both sides
-4 = b
our y intercept would be (0,-4)
the equation looks like the following:
y = 4/3x - 4, which is our answer
Answer:
The 2 represents that each toppings costs $2.
Answer:
And we can find this probability using the complement rule and with excel or the normal standard table:
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the weights of a population, and for this case we know the distribution for X is given by:
Where
and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability using the complement rule and with excel or the normal standard table: