Answer:
I think it's A
Step-by-step explanation:
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Answer:
Here's what I get.
Step-by-step explanation:
1. Representation of data
I used Excel to create a scatterplot of the data, draw the line of best fit, and print the regression equation.
2. Line of best fit
(a) Variables
I chose arm span as the dependent variable (y-axis) and height as the independent variable (x-axis).
It seems to me that arm span depends on your height rather than the other way around.
(b) Regression equation
The calculation is easy but tedious, so I asked Excel to do it.
For the equation y = ax + b, the formulas are

This gave the regression equation:
y = 1.0595x - 4.1524
(c) Interpretation
The line shows how arm span depends on height.
The slope of the line says that arm span increases about 6 % faster than height.
The y-intercept is -4. If your height is zero, your arm length is -4 in (both are impossible).
(d) Residuals

The residuals appear to be evenly distributed above and below the predicted values.
A graph of all the residuals confirms this observation.
The equation usually predicts arm span to within 4 in.
(e) Predictions
(i) Height of person with 66 in arm span

(ii) Arm span of 74 in tall person

Answer:
Greatest common factor is 5
Step-by-step explanation:
5 goes into each of the coefficients.
Answer:
Step-by-step explanation:
answer:
3x - 18 = 2y
5x - 6y = 14
5x - 3*(2y) = 14
5x - 3*(3x - 18) = 14
5x - 9x + 54 = 14
-4x = -40
x = 10
3*10 - 18 = 2y
30 - 18 = 2y
12 = 2y
y = 6