Answer:
A multiplier of 1.641 corresponds to a percentage increase or decrease of 64.1%.
Step-by-step explanation:
To determine a percentage increase or decrease of a certain number, a calculation consisting of the multiplication of said number by 1 plus the decimals corresponding to the percentage to be increased must be performed. Thus, for example, if you want to increase a number by 50%, you must multiply that number by 1.50. Therefore, if you multiply a number by 1,641, this implies that you are wanting to increase or decrease the initial number by 64.1%.
F(-3,-2), I(-4, 3), A(-2,3), M(1, -1)<br>
to<br>
I’(-4,-3), A’ (-2, -3), M’(1,1), F(-3,2)
icang [17]
I am not sure what exactly the question is, but all points are a reflection across the x-axis. I hope that helps.
The initial value: 25, rate of change: -5 ⇒ answer C
Step-by-step explanation:
The table:
→ x : 1 : 3 : 5 : 7
→ y : 20 : 10 : 0 : -10
The linear relation between x and y is y = m x + b, where
- m is the rate of change
- b is the initial value
Let us use the table to find m and b
∵ 
, where 
and 
are any two ordered pairs in the table
∵ = (1 , 20)
∵ = (3 , 10)
∴ 
∵ m is the rate of change
∴ The rate of change is -5
Substitute the value of m in the form of the linear relation
∴ y = -5 x + b
To find b substitute x and y in the equation by the coordinates of any points in the table, let us chose point (5 , 0)
∵ x = 5 and y = 0
∴ 0 = -5(5) + b
∴ 0 = -25 + b
- Add 25 to both sides
∴ 25 = b
∵ b represents the initial value
∴ The initial value is 25
The initial value: 25, rate of change: -5
Learn more:
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Answer:
Kindly check explanation
Step-by-step explanation:
Given the data:
Temperature (degrees Celsius) : 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Percent heat loss from beak : 35 36 38 28 41 43 55 46 39 54 45 58 60 56 62 67
Using an online regression calculator ; the regression equation obtained is :
ŷ = 2.0927X + 0.6029
X = independent variable
Y = predicted variable
2.0927 = slope
0.6029 = intercept
B.) temperature = 25
ŷ = 2.0927(25) + 0.6029
= 52.9204
C.) the explained variance is the value of the coefficient of determination (R²) which is the square of the correlation Coefficient
0.8785² = 0.7718
D.) the correlation Coefficient r is 0.8785 using the Coefficient of regression calculator
