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Artyom0805 [142]
3 years ago
8

15 Points!

Mathematics
2 answers:
e-lub [12.9K]3 years ago
8 0

Answer:

Co-ordinates of A are ( a, b )

Co-ordinates of C are ( 2c, d )

Slope of line segments AD and BC is \frac{-b}{c-a}

Step-by-step explanation:

We know that, the co-ordinates of the mid-point of a line segment having end points (x,y) and (x_{1} , y_{1} ) is (\frac{x+x_{1} }{2} , \frac{y+y_{1} }{2} )

Now as 'A' is the mid-point of the line segment RS having end points (0,0) and (2a,2b).

The co-ordinates of A will be ( \frac{0+2a}{2}, \frac{0+2a}{2} ) i.e ( a, b )

Now as 'C' is the mid-point of the line segment TV having end points (2c,2d) and (2c,0).

The co-ordinates of C will be ( \frac{2c+2c}{2}, \frac{2d+0}{2} ) i.e. ( \frac{4c}{2} , \frac{2d}{2}) i.e. ( 2c, d ).

Further, we need to find the slope of line segments AD and BC.

AD has end points ( a, b ) and ( c, 0 ). Then the slope of AD will be \frac{0-b}{c-a} i.e \frac{-b}{c-a}

Similarly, BC has end points ( a+c, b+d ) and ( 2c, d ). Then the slope of BC will be \frac{d-b-d}{2c-a-c} i.e \frac{-b}{c-a}

Hence, the slope of AD and BC is \frac{-b}{c-a}.

goblinko [34]3 years ago
7 0

Answer:

coordinate of point A is (a,b)

coordinate of point C is (2c,d)

slope of AD and BC =\frac{b}{a-c}

Step-by-step explanation:

According to midpoint formula

If we have points P (x_{1} ,y_{1} ) and Q (x_{2} ,y_{2} )

then the coordinate (x,y) of mid point of line PQ is given by

x=\frac{x_{1} +x_{2} }{2} and y=\frac{y_{1} +y_{2} }{2}

now from the given diagram A is the mid point of line joining  R(0,0) and S(2a,2b)

Using midpoint formula, coordinates of point A is given by

x=\frac{0+2a}{2}= a and y=\frac{0+2b}{2} =b

so we have

coordinate of point A is (a,b)

Also C is the midpoint of line joining T (2c,2d) and V(2c,0)

coordinate of point C is given by

x= \frac{2c+2c}{2} =2c and y=\frac{2d+0}{2} =d

so we have

coordinate of point C is (2c,d)

it is given that coordinate of point B is (a+c, b+d) and coordinate of D is (c,0)

If we have points P (x_{1} ,y_{1} ) and Q (x_{2} ,y_{2} )

then the slope of PQ =\frac{y_{2} -y_{1} }{x_{2}-x_{1}  }

hence slope of AD= \frac{0-b }{c-a}

                                 =\frac{-b}{c-a}

                                  =\frac{-b}{-(a-c)}

                                  =\frac{b}{a-c}

and slope of BC  =\frac{d-(b+d)}{2c-(a+c)}

                            =\frac{d-b-d}{2c-a-c}

                             =\frac{-b}{c-a}

                              =\frac{b}{a-c}

so we have

slope of AD and BC =\frac{b}{a-c}

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The mean amount purchased by a typical customer at Churchill's Grocery Store is $27.50 with a standard deviation of $7.00. Assum
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Answer:

a) 0.0016 = 0.16% probability that the sample mean is at least $30.00.

b) 0.8794 = 87.94% probability that the sample mean is greater than $26.50 but less than $30.00

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Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this question, we have that:

\mu = 27.50, \sigma = 7, n = 68, s = \frac{7}{\sqrt{68}} = 0.85

a. What is the likelihood the sample mean is at least $30.00?

This is 1 subtracted by the pvalue of Z when X = 30. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem, we have that:

Z = \frac{X - \mu}{s}

Z = \frac{30 - 27.5}{0.85}

Z = 2.94

Z = 2.94 has a pvalue of 0.9984

1 - 0.9984 = 0.0016

0.0016 = 0.16% probability that the sample mean is at least $30.00.

b. What is the likelihood the sample mean is greater than $26.50 but less than $30.00?

This is the pvalue of Z when X = 30 subtracted by the pvalue of Z when X = 26.50. So

From a, when X = 30, Z has a pvalue of 0.9984

When X = 26.5

Z = \frac{X - \mu}{s}

Z = \frac{26.5 - 27.5}{0.85}

Z = -1.18

Z = -1.18 has a pvalue of 0.1190

0.9984 - 0.1190 = 0.8794

0.8794 = 87.94% probability that the sample mean is greater than $26.50 but less than $30.00.

c. Within what limits will 90 percent of the sample means occur?

Between the 50 - (90/2) = 5th percentile and the 50 + (90/2) = 95th percentile, that is, Z between -1.645 and Z = 1.645

Lower bound:

Z = \frac{X - \mu}{s}

-1.645 = \frac{X - 27.5}{0.85}

X - 27.5 = -1.645*0.85

X = 26.1

Upper Bound:

Z = \frac{X - \mu}{s}

1.645 = \frac{X - 27.5}{0.85}

X - 27.5 = 1.645*0.85

X = 28.9

90% of sample means will occur between $26.1 and $28.9.

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