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ella
1 day ago
13

Alana is writing a coordinate proof to show that the diagonals of a rectangle are congruent. She starts by assigning coordinates

to a rectangle as shown. Then she uses the coordinates to write and simplify expressions for the lengths of the diagonals.
What is the length of one of the diagonals of the rectangle?

Enter an expression in the box for the length of the diagonal.

Mathematics
2 answers:
Zina [9.1K]1 day ago
5 0

Response:

The accurate response is  √a^2 + b^2 I took the test and this is the correct answer I assure you

Detailed explanation:


Svet_ta [9.5K]1 day ago
4 0
d(S,P) = √(0-0)^2 + √(b-0)^2
d(S,P) = √b^2
d(S,P) = b
therefore
SP = b

d(P, Q) = √(a-0)^2 + √(b-b)^2
d(P, Q) = √a^2
d(P, Q) = a
thus
PQ = a 

SQ = c^2 = a^2 + b^2
SQ = √(a^2 + b^2)

response
 the length of one diagonal of the rectangle equals √(a^2 + b^2)
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Answer:

Area= 247 feet²

Volume= 1235 feet³

Step-by-step explanation:

The storage pod features a rectangular base measuring 19 feet by 13 feet, with a flat ceiling height of 5 feet above.

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Length = 19 feet

Width = 13 feet

Area = 19*13

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At a recent county fair, you observed that at one stand people's weight was forecasted, and were surprised by the accuracy (with
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Answer:

a) Slope: \hat \beta_1 =\frac{7625.9}{1248.9}=6.106

Intercept: \hat \beta_o = 157.955 -6.106 (69.686)=-267.548

b) r=\frac{7625.9}{\sqrt{[1248.9][94228.8]}}=0.657

Additionally, the coefficient of determination is r^2 = 0.657^2 =0.432

Step-by-step explanation:

Definitions and data provided

The correlation coefficient is a measure that quantifies the strength of the relationship between two variable movements, denoted as r and ranging between -1 and 1.

The sum of squares refers to the total of the squared deviations, where deviation is defined as the difference between each value and the grand mean.

When performing multiple regression, the aim is to analyze the relationship between multiple independent variables and one dependent variable.

n=110, \sum x_i y_i = \sum (X-\bar X)(Y-\bar Y) =7625.9,\sum x^2_i=\sum (x-\bar x)^2 =1248.9, sum y^2_i=\sum(y-\bar y)^2 =94228.8

\sum Y_i =17375, \sum X_i = 7665.5

Part a

The slope can be calculated using this formula:

\hat \beta_1 =\frac{\sum (x-\bar x) (y-\bar y)}{\sum (x-\bar x )^2}

Following the substitutions, we have:

\hat \beta_1 =\frac{7625.9}{1248.9}=6.106

The intercept can be determined with this formula:

\hat \beta_o = \bar y -\hat \beta_1 \bar x

Average values for x and y can be calculated this way:

\bar X=7665.5/110 =69.686, \bar y= 17375/110=157.955

Replacing yields:

\hat \beta_o = 157.955 -6.106 (69.686)=-267.548

Part b

The correlation coefficient can be calculated using the following formula:

r=\frac{\sum (x-\bar x)(y-\bar y) }{\sqrt{[\sum (x-\bar x)^2][\sum(y-\bar y)^2]}}

In our situation:

n=110, \sum x_i y_i = \sum (X-\bar X)(Y-\bar Y) =7625.9,\sum x^2_i=\sum (x-\bar x)^2 =1248.9, sum y^2_i=\sum(y-\bar y)^2 =94228.8

We can compute the correlation coefficient by substituting values:

r=\frac{7625.9}{\sqrt{[1248.9][94228.8]}}=0.657

The coefficient of determination is r^2 = 0.657^2 =0.432

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