We will because we will turn into aliens and then shoot dogs into the universe
Answer:
The answer is A
Step-by-step explanation:
Answer:
s₁ > s₂
Is accurate comparison
Step-by-step explanation:
If we have two different point for a straight line the slope of such line is given by:
P₁ = ( x₁ , y₁ ) P₂ = ( x₂ , y₂ )
The slope of the line is
s₁ = (y₂ - y₁ ) / ( x₂ - x₁)
Then for the pairs of points:
P₁ (2 , 50 ) and P₂ ( 4 , 100)
y₂ - y₁ = 100 - 50 ⇒ y₂ - y₁ = 50
and
( x₂ - x₁ ) ⇒ 4 - 2 = 2
Then
s₁ = 50/2
s₁ = 25
In the second case
Points
P₁ ( 2 , 40 ) P₂ ( 4 , 80 )
s₂ = (y₂ - y₁ ) / ( x₂ - x₁)
y₂ - y₁ = 80 - 40 = 40
x₂ - x₁ = 4 - 2 = 2
s₂ = 40/2
s₂ = 20
Then
s₁ > s₂
Is accurate comparison
The value of (abscissa of P) -(abscissa of Q) is -1.
The given coordinates are P(4,6) and Q(5,-7).
We need to find (abscissa of P) -(abscissa of Q).
<h3>What is
abscissa?</h3>
The horizontal coordinate of a point in a planar Cartesian coordinate system that is determined by measuring parallel to the x-axis is what abscissa stands for.
Now, (abscissa of P) -(abscissa of Q)=4-5=-1
Hence, the value of (abscissa of P) -(abscissa of Q) is -1.
To learn more about abscissa visit:
brainly.com/question/1214621.
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Mean: 160.12Standard Deviation: 19.76Median: 162Maximum: 202 Minimum: 120
The mean is calculated by adding all of the numbers in the data set and dividing by the number of values that were added:
173 + 123 + 171 + 175 + 188 + 120 + 177 + 160 + 151 + 169 + 162 + 128 + 145 + 140 + 158 + 132 + 202 + 162 + 154 + 180 + 164 + 166 + 157 + 171 + 175 ÷ 25 = 160.12
Standard deviation is found by calculating the mean (160.12) , and then subtracting the mean and square root result for each number. Finally, working out the mean of the squared differences and taking the square root of the final answer results in a standard deviation of 19.76. (The attached image has the formula for finding standard deviation).
Median is the number that is found in the middle when placing the numbers in order from least to greatest.
The maximum is the largest number in the data set.
The minimum is the smallest number in the data set.