Given:
Two diameters intersect each other.
To find:
The correct statement regarding two adjacent arcs created by two intersecting diameters.
Solution:
We know that, two diameter intersect each other at origin and measure of arc is equal to the corresponding angle generated by the intersection of diameters.
If two lines intersect each other then we get 4 angles and sum of any two adjacent angles is 180°.
It means the sum of any two adjacent central angles generated by the intersection of diameters is 180°.
So, the sum of two adjacent arcs created by two intersecting diameters is 180°.
Therefore, the correct option is C.
<h3>Domain: (-5, 3]</h3><h3>Range: [-4, 5)</h3>
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Explanation:
The domain is the set of allowed x values. In terms of a graph, we look at the left most point to see that x = -5 is the smallest x value possible. However, there's an open hole at this endpoint, so -5 itself is actually not part of the domain. So x must be larger than -5. At the same time, x can be as large as x = 3. Look at the very right tip of the graph to find this x value.
So x spans from -5 to 3, excluding -5 but including 3. We would write 
which converts to the interval notation (-5, 3]. Note the mix of curved parenthesis and square bracket. The curved parenthesis means to exclude the endpoint, while the square bracket means include the endpoint.
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The range is the set of possible y outputs. Find out the lowest point of the graph. That is when y = -4 and this value is included due to the filled in circle at the endpoint. But we do not include the largest y value y = 5 as there's an open hole at this endpoint.
So the range is the set of y values such that 
which in interval notation would be written as [-4, 5)
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So in short, you're looking for the min and max of x and y to get the domain and range respectively. Be sure to exclude any values where there are open holes as those do not count as part of the graph.
ANSWER:
I believe you wish to calculate the sum of squares total (SST) for this regression analysis. The sum of squares total is 1053.15
Step-by-step explanation:
The sum of squares total is numerically derived by adding the sum of squares regression (regression sum of squares) to the sum of squares error (error sum of squares). The regression sum of squares here is 752.25 and the error sum of squares is 300.9
This gives us a total sum of squares of 1053.15
Sums of squares tell if a linear regression of one variable (or variables) on another is good or not.
The squared differences between the observed dependent variable and its mean is a measure of the total variability of the data set.
So the SST is equal to 752.25 + 300.9 = 1053.15
Answer:
y-6 = 2 (x-5)
Step-by-step explanation:
point slope form
y-y1 = m(x-x1)
y-6 = 2 (x-5)
I agree with Josie, because it would be easier since the other three numbers are decimals. If you prefer fractions, then change the three decimals to mixed numbers.
