The perpendicular equation would include a slope that is the opposite reciprocal of the original slope.
Steps:
1. Get x to the other side in the original equation. This making the slope -4 or -4/1.
2. Turn the slope into it’s opposite reciprocal m = 1/4.
3. If you use point-slope form, y - y1 = m( x - x1 ), you can substitute y1 and x1 with the numbers in the point given. But since we previously found the opposite reciprocal, we will replace “m” as well. *By the way, the subtraction of a negative makes a positive. [y + 3 = 1/4( x + 4 )]
4. Solve:
A: Distribute (y + 3 = 1/4x + 1)
B: Subtract 3 from both sides (y = 1/4x -2)
Perpendicular Equation: y = 1/4x - 2
The lengths could be 7 and 5
Answer:
B = 38
Step-by-step explanation:
b=3b-76
-3b -3b
-2b=-76
b=38
Answer:
−2(3x+12y−5−17x−16y+4)
=(−2)(3x+12y+−5+−17x+−16y+4)
=(−2)(3x)+(−2)(12y)+(−2)(−5)+(−2)(−17x)+(−2)(−16y)+(−2)(4)
=−6x−24y+10+34x+32y−8
=28x+8y+2
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Answer:
And using a calculator, excel or the normal standard table we have that:
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 withdrawals of a population, and for this case we know the following info
and
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
From the central limit theorem we know that the distribution for the sample mean is given by:
We can find the probability of interest like this:
And using a calculator, excel or the normal standard table we have that: