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artcher [175]
3 years ago
11

i NEED ASAP I WILL GIVE BRAINLIEST Figure ABCD has vertices A(−2, 3), B(4, 3), C(4, −2), and D(−2, 0). What is the area of Figur

e ABCD? 6 square units 12 square units 18 square units 24 square units

Mathematics
1 answer:
Crank3 years ago
5 0

Answer:

The area of figure ABCD is 24 square units.

Step-by-step explanation:

We see that the given points form the vertices of a trapezium ABCD with bases AD and CB with measure,

AD= 3 units and CB=5 units

and the height of the trapezium is AB= 6 units.

The area of trapezium ABCD is:

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there is 135 feet of masking tape on a roll henry has 6 rolls. how many feet of masking tape does he have in all?
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Henry has 810 feet of making tape 

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Number of plane surface in a matches box​
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Step-by-step explanation:

Same as plane surfaces on a regular cuboid

7 0
3 years ago
Consider the triangle A(4,0), B(-2,4), C(0,6)<br> What will be the equation of the altitude BM?
katovenus [111]

Answer:

BM: <u>y = (2/3) x + 16/3</u> with segment length of 2.77

Step-by-step explanation:

AC formula: m = (6-0)/(0-4) = -3/2

(y-0)/(x-4) = -3/2       y = (-3/2)x + 6   ... (1)

BM slope: BM⊥ AC   m = 2/3

BM formula: (y-4) / (x- -2) = (y-4) / (x+2) = 2/3

y-4 = 2/3 x + 4/3

<u>y = (2/3) x + 16/3</u>   ... (2)    -2≤x≤0.31

intercept of AC and BM (M) from (1) and (2): (-3/2)x + 6 = (2/3) x + 16/3

(13/6) x = 2/3      x = (2/3) / (13/6) = 4/13 ≈ 0.31

y = (2/3) (4/13) + (16/3) = (8/39) + (208/39) = 216/39 = 72/13 ≈ 5.54

M (4/13 , 72/13) or (0.31 , 5.54)

segment BM = √(4/13 - -2)² + (72/13 - 4)² = √1300/169 = 2.77

4 0
2 years ago
The variance can never bea.zerob.larger than the standard deviationc.negatived.smaller than the standard deviation
MrRa [10]

Answer:

c.negative

True, by definition since the variance take in count the differences around the mean squared, then we can't have a negative value for a sum of square values.

Step-by-step explanation:

We need to remember that the variance is a measure of dispersion for a dataset respect to a measure of central tendency called the mean. The mean is defined as:

\bar x = \frac{\sum_{i=1}^n X_i}{n}

And the population mean is given by:

\mu= \frac{\sum_{i=1}^n X_i}{N}

The population variance is defined by:

\sigma^2 = \frac{\sum_{i=1}^n (X_i -\mu)^2}{N}

And the sample variance is defined as:

s^2= \frac{\sum_{i=1}^n (X_i -\bar x)}{n-1}

Now if we analyze the options we have this:

a.zero

False, if all the values are the same then the mean would be the same to the values and the difference between each value and the mean would 0 and indeed the variance would be 0.

b.larger than the standard deviation

False, if the population standard deviation is \sigma=2 then the variance would be \sigma^2 = 4 and as we can see is higher than the standard deviation

c.negative

True, by definition since the variance take in count the differences around the mean squared, then we can't have a negative value for a sum of square values.

d.smaller than the standard deviation

False, if the population standard deviation is \sigma=0.1 then the variance would be \sigma^2 = 0.01 and as we can see is lower than the standard deviation

7 0
3 years ago
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