Answer:
I say 12, but i can be wrong.
Step-by-step explanation:
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:
200.4 at 0.25%
Step-by-step explanation:
Given data
P= P200
r= 0.25%
t= 1 year
n= 12
A= P(1+ r/n)^nt
substitute
A= 200(1+ 0.0025/12)^12*1
A= 200(1+ 0.00020833333)^12
A= 200(1.0002)^12
A= 200* 1.002
A= 200.4
Hence the amount is 200.4 at 0.25%
Answer:
25
Step-by-step explanation:
Easy! You plug in 3 for n! H(3) = 3^3 - 2
3^3 = 27 - 2 = 25
Answer:
steps below
Step-by-step explanation:
cos 23° = 6/x
0.92 = 6/x
x = 6/0.92 = 6.52