Answer:
Step-by-step explanation:
Given is a table showing the weights, in hundreds of pounds, for six selected cars. Also shown is the corresponding fuel efficiency, in miles per gallon (mpg), for the car in city driving.
Weight Fuel eff. x^2 xy y^2
X Y
28 20 784 560 400
3 22 9 66 484
35 19 1225 665 361
32 22 1024 704 484
30 23 900 690 529
29 21 841 609 441
Mean 26.16666667 21.16666667 797.1666667 549 449.8333333
Variance 112.4722222 1.805555556
Covariance -553.8611111
r -0.341120235
Correlaton coefficient =cov (xy)/S_x S_y
Covariance (x,y) = E(xy)-E(x)E(y)
The correlation coefficient between the weight of a car and the fuel efficiency is -0.341
Theoretical probability:
1 ... (16 and 2/3) %
2 ... (16 and 2/3) %
3 ... (16 and 2/3) %
4 ... (16 and 2/3) %
5 ... (16 and 2/3) %
6 ... (16 and 2/3) %
Experimental results:
1 ... 18
2 ... 16
3 ... 16
4 ... 17
5 ... 16
6 ... 17
The total number of rolls in the experiment was
(18 + 16 + 16 + 17 + 16 + 17) = 100
so the expected frequency for each outcome was 16-2/3 times,
and the SIMULATION probabilities were
1 ... 18%
2 ... 16%
3 ... 16%
4 ... 17%
5 ... 16%
6 ... 17%
To me, this looks fantastically close. The cube
could hardly be more fair than it actually is.
Answer:
Step-by-step explanation:
From the question we are told that:
Length of each side 
Let the triangle be divide by two form a right angle triangle with base angles as 
(angle of perpendicularity) and 
(angle on each vertices of an equilateral triangle)
Generally the equation for the Altitude X is mathematically given by
Trigonometric Rule
Answer:
all work is pictured and shown
