Answer:
1/3
Step-by-step explanation:
im just smart (wink)
Step-by-step explanation:

- Length of MN ( Base ) = 8
- Length of NL ( Hypotenuse ) = 10

- Length of LM ( Perpendicular )


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Step-by-step explanation:
For a quadratic equation y = ax² + bx + c, the vertex (the maximum or minimum point) is at x = -b/(2a).
1) y = -0.5t² + 2t + 38
The maximum is at:
t = -2 / (2 × -0.5)
t = 2
The maximum height is:
y = -0.5(2)² + 2(2) + 38
y = 40
The coordinates of the vertex are (2, 40). That means the missile reaches a maximum height of 40 km after 2 minutes.
2) y = -4.9t² + 12t + 1.6
The maximum is at:
t = -12 / (2 × -4.9)
t = 1.22
The maximum height is:
y = -4.9(1.22)² + 12(1.22) + 1.6
y = 8.95
The coordinates of the vertex are (1.22, 8.95). That means the missile reaches a maximum height of 8.95 m after 1.22 seconds.
3) y = -0.04x² + 0.88x
The maximum is at:
x = -0.88 / (2 × -0.04)
x = 11
The maximum height is:
y = -0.04(11)² + 0.88(11)
y = 4.84
The maximum height of the tunnel is 4.84 meters.
The maximum width is when y = 0.
0 = -0.04x² + 0.88x
0 = -0.04x (x − 22)
x = 22
The maximum width is 22 feet.
1) 8 + 4 = -5 + 7
12 = 2
FALSE
2) y = -11x + 4
(0, -7): -7 = -11(0) + 4 ⇒ -7 = 0 + 4 ⇒ -7 = 4 False
(-1, -7): -7 = -11(-1) + 4 ⇒ -7 = 11 + 4 ⇒ -7 = 15 False
(1, -7): -7 = -11(1) + 4 ⇒ -7 = -11 + 4 ⇒ -7 = -7 True
(2, 26): 26 = -11(2) + 4 ⇒ 26 = -22 + 4 ⇒ 26 = -18 False
Answer: C
3) Input Output
0 0
<u> 1 </u> 3
2 <u> 6 </u>
3 9
<u> 4 </u> <u> 12 </u>
5 15
6 <u> 18 </u>
Rule: input is being added by 1, output is 3 times x
4) c = 65h
5) 2x = -6

x = -3
6) 8j - 5 + j = 67
9j - 5 = 67 <em>added like terms (8j + j)</em>
<u> +5</u> <u>+5 </u>
9j = 72

j = 8
7) y = mx + b
<u> -b</u> <u> -b </u>
y - b = mx


Step-by-step explanation:
Regression analysis is used to infer about the relationship between two or more variables.
The line of best fit is a straight line representing the regression equation on a scatter plot. The may pass through either some point or all points or none of the points.
<u>Method 1:</u>
Using regression analysis the line of best fit is: 
Here <em>α </em>= intercept, <em>β</em> = slope and <em>e</em> = error.
The formula to compute the intercept is:

Here<em> </em>
and
are mean of the <em>y</em> and <em>x</em> values respectively.

The formula to compute the slope is:

And the formula to compute the error is:

<u>Method 2:</u>
The regression line can be determined using the descriptive statistics mean, standard deviation and correlation.
The equation of the line of best fit is:

Here <em>r</em> = correlation coefficient = 
and
are standard deviation of <em>x</em> and <em>y</em> respectively.
