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3 years ago

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The perimeter of a parallelogram is 48 meters. The width of the parallelogram is 8 meters less than its length. Find the length

and the width of the parallelogram.

1 answer:

SVEN [57.7K]3 years ago

5 0

Answer; length = 14 width = 10

Step-by-step explanation:

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In triangle ABC, Aat the top of the triangle, B at 90° and C at the third end, angle C = 21°, the hypotenus = 15m,find BC = y th

dsp73

Answer

Step-by-step explanation:

Law of sines: SinB/15 = SinA/BC

B = 90

A = 180-90-21=69°

BC= (15*SinA)/SinB = (15*sin69)/1 ≈ 14m

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Y=9/8x+7 is the equation for the graphed line

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Vladimir79 [104]

Answer:

The equation representing the left table is

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The equation representing the right table is

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The solution to the system of equations is

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Michelle is fishing from a small boat. A fish swimming at the same depth as the hook at the end of her fishing line is 16 meters

Rama09 [41]

Answer:

12 meters

Step-by-step explanation:

You have to use the inverse of the pythagorean theorem to do this so you do square root of (20x20-16x16) which is 12

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2 years ago

In a study relating the degree of warping, in mm, of a copper plate (y) to temperature in °C (x), the following summary statisti

kipiarov [429]

Answer:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

Step-by-step explanation:

Linear regression is a way "to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables)".

Regression estimates are "used to describe data and to explain the relationship between one dependent variable and one or more independent variables"

The linear model is given by the following equation $Y=mx +b$ , where y is the dependent variable, x the independent variable, m the slope and b the intercept.

For this case we have the following info given:

$\sum_{i=1}^n (x_i -\bar x)^2 =98775$

$\sum_{i=1}^n (y_i -\bar y)^2 =19.4$

$\bar x =26.36$

$\bar y =0.5188$

n= 40 represent the sample size

$\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y) =796.94$

The total sum of squares is given by this formula:

$SST= \sum_{i=1}^n (y_i -\bar y)^2 =19.4$

And from the formulas for a simple regression, we need to calculate the slope for the regression like this:

$m=\frac{\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)}{\sum_{i=1}^n (x_i -\bar x)^2}$

And if we replace the values given we have:

$m=\frac{796.94}{98775}=0.008068$

We have another useful equation in order to find the sum of squares for the regression, given by:

$SSR=m* \sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)=0.008068*796.94=6.430$

And we know this equivalence:

$SST= SSR+SSE$

And solving for the sum of squares for the error we have:

$SSE=SST-SSR=19.4-6.430=12.97$

So then we have the final solutions:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

6 0

3 years ago