ENGINEERING ASSIGNMENT - 5 HOURS

betoglan2017
Equations_Student_FirstName.xlsx

Tables

Effects of Fuel and Road Grade on Car Speed
Car Model XlR
Tire Pressure 30psi Reproduce this graph (exactly) using the Speed data
Air Temperature 70° F
Air Pressure 0.985 psi
Road Grade Fuel Rate Speed
(%) (gal/h) (mi/h)
0.00 1.00 38.2
2.00 64.3
3.00 81
4.00 93.4
5.00 99.2
5.00 1.00 32.3
2.00 54.5
3.00 68.4
4.00 78.1
5.00 84.8
10.00 1.00 25.8
2.00 43.6
3.00 54.7
4.00 62.5
5.00 67.8

Linear Equation

Linear Equation
y = m x + b y is the dependent variable
m is the slope
x is the independent variable
b is the y incertcept (x=0)
Plot the following equation
Example: y=3x - 6
x y
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
7
8
9
10

Power

Power Equation Step 1: Plot (y vs x) Step 3. Using the original data, use log/log scale
y = bxm m= 4
b= 1
x y log x log y
1 1
2 16
3 81
4 256
5 625
6 1296
7 2401
8 4096
9 6561
10 10000
11 14641
12 20736
13 28561 Step 2 : Calculate and plot log(y), log(x)
14 38416

Exponential

Exponential Equation Step 1: Plot (y vs x) Step 3. Using the original data, use semilog scale
y = b exp(mx)
m= 2
b= 1
x y X log y
1 7.3890560989
2 54.5981500331
3 403.4287934927
4 2980.9579870417
5 22026.4657948067
6 162754.791419004
7 1202604.28416478
8 8886110.52050787
9 65659969.1373305
10 485165195.40979
11 3584912846.13159 Step 2 : Calculate log(y) and plot log(y) vs. x
12 26489122129.8435
13 195729609428.839
14 1446257064291.48

Linear Regression

Regression
Student xi yi (xi - x) (yi - y) (xi - x)2 (yi - y)2 (xi - x)(yi - y)
1 95 85 17 8 289 64 136
2 85 95 7 18 49 324 126
3 80 70 2 -7 4 49 -14
4 70 65 -8 -12 64 144 96
5 60 70 -18 -7 324 49 126
Sum 390 385 730 630 470
Mean 78 77

Student data

95 85 80 70 60 85 95 70 65 70

Grade (100 scale)

GPA (100 scale)

Population

Year Population in Millions
1518 22
1520 20
1540 8
1560 4
1580 2
1600 1.1