By representing the equation is written in the form y = ax + b .
The value of b is 8.
According to the question
A start-up company opened with 8 employees.
So, Number of employees = 8
At zero quarter = 8
The company’s growth plan assumes that 2 new employees will be hired each quarter
After 1 quarter = Number of employees + 2 new employees
After one quarter = 8 + 2 = 10
Equation is written in the form y = ax + b to represent the number of employees, y, employed by the company x quarters after the company opened
y = ax + b
10 = 2 × 1 + b
10 = 2 + b
Subtract 2 on both sides of the equation
b = 10 - 2
b = 8
The value of b is 8.
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Answer:
Step-by-step explanation:
Alternate angles are angles that are opposite, on the other side of the lines, so imagine it as a z shape.
In this case, alternate angles include, 3, 13, other equal angles are vertically opposite, so that would include 7, 1, 15. Vertically opposite angles that are two angles made opposite with 2 intersecting lines.
Hope this helps,
Cate
Answer:
80 degrees
Step-by-step explanation:
100 + angle A = 180
180-100= 80
So, the measure of angle A is 80 degrees
Answer:
a) y = 0.74x + 18.99; b) 80; c) r = 0.92, r² = 0.85; r² tells us that 85% of the variance in the dependent variable, the final average, is predictable from the independent variable, the first test score.
Step-by-step explanation:
For part a,
We first plot the data using a graphing calculator. We then run a linear regression on the data.
In the form y = ax + b, we get an a value that rounds to 0.74 and a b value that rounds to 18.99. This gives us the equation
y = 0.74x + 18.99.
For part b,
To find the final average of a student who made an 83 on the first test, we substitute 83 in place of x in our regression equation:
y = 0.74(83) + 18.99
y = 61.42 + 18.99 = 80.41
Rounded to the nearest percent, this is 80.
For part c,
The value of r is 0.92. This tells us that the line is a 92% fit for the data.
The value of r² is 0.85. This is the coefficient of determination; it tells us how much of the dependent variable can be predicted from the independent variable.