Answer:
She earns 5.5 dollars per hour at the library
Step-by-step explanation:
I am going to assume that the questions is "how much she earns per hour at the library?"
Let's call x the amount of dollars earn by hour at the library. We know that she worked for 6 hours, thus she made 6x dollars.
Later her grandma gave her 20 dollars and she has now 53 dollars.
Let's write the equation and solve it
Amount earned + Amount given by her grandma = 53

Thus, based on this information we would have that Kia earns 5.5 dollars per hour.
The equation for this problem would be:
x+y = 16
Rearranging the equation, it can be expressed as:
y = 16 - x
To obtain ordered pairs, replace random values of x up to 16 to find the value of y. The ordered pairs are tabulated and the graph is shown in the attached picture.
(a) what are the x and y components of each vector?
For vector v1:
v1 = 6.6 (cos (180) i + sine (180) j)
v1 = 6.6 (-1i + 0j)
v1 = -6.6i
For vector v2:
v2 = 8.5 (cos (55) i + sine (55) j)
v2 = 8.5 ((0.573576436) i + (0.819152044) j)
v2 = 4.88 i + 6.96 j
(b) determine the sum v v 1 2
The sum of both vectors is given by:
v1 + v2 = (-6.6i) + (4.88 i + 6.96 j)
Adding component to component:
v1 + v2 = (-6.6 + 4.88) i + (6.96) j
v1 + v2 = (-1.72) i + (6.96) j
If that is 6-3(log2n)=0 then how you would go about solving it is by looking at log2n like x. In this case, for 6-3x=0, x would have to =2. So log2n has to =2. If log2n=2 and we assume that the base is 10 (because if there is no written base on a log then it is 10) then we need to rewrite the log to exponential form. Rewritten it's 10^2=2n. 100=2n, divide both sides by 2 and you get n=50.
Answer:
E IS THE CORRECT ANSWER
The R-squared is 0.64 and it means that the dependent value explains 64% of the independent value in the simple regression analysis
Step-by-step explanation:
R-Squared value is a very important indicator in a regression analysis.
What does it measure?
It measures how close to the line of best fit are the data points. How good the fitted line is can be indicated by the value of the r-squared.
The maximum value it can take is 1 and at this value, there is a direct and complete relationship between the independent variable x and the dependent variable y. The value 1 represents an 100% relationship between both parties.
The r-squared has a value of between 0 and 100%. The closer to 100, the better the model while the closer to 100, the more faulty the model is. In fact, a value of 0 indicates no relationship at all between the dependent and the independent variable.
With an R-squared value of 0.64, the regression model works above average to explain that the dependent variable explains 64% of the independent value in the simple regression analysis.