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3 years ago

Parallel and perpendicular line (4,7);y3x+6

Mathematics

1 answer:

enyata [817]3 years ago

8 0

Answer:

Parallel Line: y = 3x - 5

Perpendicular Line: y = -1/3x + 25/3

Step-by-step explanation:

The equation given is a linear equation in slope-intercept form, y = mx + b, where m = slope and b = y-intercept. With lines that are parallel to each other, they containt the same slope. So, to form an equation of a line that is parallel to the first equation, the slope = 3. Using the given point (4, 7), x = 4 and y = 7, we can use our slope-intercept form to solve for 'b':

7 = (3)(4) + b or 7 = 12 + b or b = -5

So, our equation for a parallel line would be: y = 3x - 5.

For perpendicular lines, the slope must be the opposite reciprocal of the slope from the first equation. So, if m = 3, than the slope of the perpendicular line must be - 1/3. Using the same point (4, 7) we can use our slope-intercept form to solve for 'b':

7 = (-1/3)(4) + b or 7 = -4/3 + b or b = 25/3

So, our equation for a perpendicular line would be: y = -1/3x + 25/3

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Answer:

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Step-by-step explanation:

Since the figures are similar then the ratios of corresponding sides are equal, that is

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3 years ago

Read 2 more answers

A random sample of 1000 people was taken. Four hundred fifty of the people in the sample favored Candidate AT. The 95% confidenc

azamat

Answer:

$0.45 - 1.96 \sqrt{\frac{0.45(1-0.45)}{1000}}=0.419$

$0.45 + 1.96 \sqrt{\frac{0.45(1-0.45)}{1000}}=0.481$

And the 95% confidence interval would be given (0.419;0.481). And the best option would be:

b. .419 to .481

Step-by-step explanation:

We know the following info:

$n = 1000$ sample size selected

$X= 450$ represent the number of people who favored Candidate AT

The sample proportion would be:

$\hat p=\frac{450}{1000}=0.45$

The confidence interval would be given by this formula

$\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}$

For the 95% confidence interval the value of $\alpha=1-0.95=0.05$ and $\alpha/2=0.025$ , with that value we can find the quantile required for the interval in the normal standard distribution.