Engr/Math/Physics 25
MS Excel
Tables/Plots
Bruce Mayer, PE
Licensed Electrical & Mechanical Engineer
BMayer@ChabotCollege.edu
Engineering/Math/Physics 25: Computational Methods
1
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
The 11 MS Excel Chart Types
Engineering/Math/Physics 25: Computational Methods
2
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Graph Construction Demo
 Given Vapor Pressure Data
TABLE I: Vapor Pressure Data
Vapor pressures (mm Hg) of less than one atmosphere as a function of temperature. (All temperatures are in degrees Celsius)
Chemical
1
5
10
20
40
60
100
200
400
760
Sodium, Na
439
511
549
589
633
662
701
758
823
892
oC
1,4-Dioxane C4H8O2
-35.8
-12.8
-1.2
12.0
25.2
33.8
45.1
62.3
81.8
101.1
oC
Acetone (CH3)2CO
-59.4
-40.5
-31.1
-20.8
-9.4
-2.0
7.7
22.7
39.5
56.5
oC
Butyric Acid, C4H8O2
25.5
49.8
61.5
74.0
88.0
96.5
108.0
125.5
144.5
163.5
oC
Stannic Chloride, SnCl4
-22.7
-1.0
10.0
22.0
35.2
43.5
54.7
72.0
92.1
113.0
oC
http://research.umbc.edu/~lkelly/DAExp.htm
 Construct a Scatter Chart to Find the
Clapeyron Eqn
1
Constants m & b ln Pv   m  b
T
for Stannic Chloride
Engineering/Math/Physics 25: Computational Methods
3
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
mmHg
Chart Construction Result
SnCl4Vapor Pressure
7
12%
ln(Pv)
(ln[Torr])
ln(Pv) = -4.7201(1000/T) + 18.958
2
R = 0.9992
6
10%
Fit Error
8%
5
ln(Pv) (ln[Torr])
6%
4
4%
3
2%
0%
2
-2%
1
-4%
0
-6%
2.5
2.75
3
3.25
3.5
3.75
1000/T (1/Kelvin)
Engineering/Math/Physics 25: Computational Methods
4
Demo_Excel_Table-n-Chart_Build_Fa06.xls
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
4
Fit Error = (Fit-Actual)/Actual
Linear (ln(Pv)
(ln[Torr]))
SnCl4 Vapor Press by Clapeyron Eqn
7
12%
ln(Pv) (ln[torr])
ln(Pv) = -4.7201*(1000/T) + 18.958
R² = 0.9992
Model Error
6
10%
Linear (ln(Pv) (ln[torr]))
8%
5
ln(Pv) (ln[Torr]
4
4%
2%
3
0%
2
-2%
1
-4%
0
-6%
2.5
2.75
3
3.25
Engineering/Math/Physics 25: Computational Methods 1000/T
5
(1/K)
3.5
3.75
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
4
Clapeyron Model Fit Error
6%
All Done for Today
Excel
Plotting
HbH Metering Tube P • Orifice Characteristic • 25Jan00
9
90
1-Hole Back Pressure (SQRT{Torr})
8
1-Hole Back Pressure (Torr)
[1-Hole Back Pressure] ( [Torr])
70
6
60
5
50
4
40
3
PARAMETERS
• Exhaust to Atmosphere
• 0.312" O.D. Tube
• 9.5 mil holes
• Rough, 1st-cut Test
• Re = 4q/(d) = 1400 @ q =
0.24 slpm
2
0
0.00
6
0.03
0.06
0.09
0.12
0.15
0.18
0.21
MFC Flow, q (slpm)
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
0.24
0.27
30
20
1-Hole Back Pressure, P ([Torr)
7
1
Engineering/Math/Physics 25: Computational Methods
80
P = 30.471q
2
R = 0.9996
Bernoulli Square Law Behavior
10
0
0.30
file = Tube-Test_00.xls
Engr/Math/Physics 25
Appendix
f x   2 x  7 x  9 x  6
3

2

5 y  3 y  7 y  f t 
Bruce Mayer, PE
Licensed Electrical & Mechanical Engineer
BMayer@ChabotCollege.edu


Pslave1n  hx j   Pmaster
Engineering/Math/Physics 25: Computational Methods
7
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (1)
 Start
• Open File
Demo_Excel_TablenChart_Build_0511.xl
s
 Copy from Table
from Slide-22 →
Paste into Demo
Sheet
 Horizontal table
starting in Col-H
 Copy Table Cells
and EDIT → PASTE
SPECIAL →
transpose
• Need Vertical Data
Engineering/Math/Physics 25: Computational Methods
8
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (2)
 Result after
Transpose Paste
Engineering/Math/Physics 25: Computational Methods
9
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (3)
 Archive Data
• Make Scratch
WorkSheet; Xfer
horizontal Table to
to this sheet
 Edit Worksheet
• Adjust Headings
• Delete Cols other
Than SnCl4
• Move Remaining to
Right
Engineering/Math/Physics 25: Computational Methods
10
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (4)
 Place in cols A & B
 After Filling A & B
• 1000/T; T in Kelvins
• Ln(Pv)
 Formula for Col-B
• =LN(E8)
Engineering/Math/Physics 25: Computational Methods
11
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (5)
 Now need to Sort
the Data with the
indep var (1000/T)
in ASCENDING
ORDER
• DATA → SORT
Engineering/Math/Physics 25: Computational Methods
12
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (6)
 Highlight/Select
Data to Plot
 Invoke Chart
Wizard
Engineering/Math/Physics 25: Computational Methods
13
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (7)
 Continue with
Chart Wizard
Engineering/Math/Physics 25: Computational Methods
14
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (8)
 Add X-Grid Lines
 Insert As NEW
Sheet
• Give Descriptive
Name
 Remove Legend
Engineering/Math/Physics 25: Computational Methods
15
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (9)
 Chart Wizard Result
Stannic Chloride (SnCl4) Vapor Pressure
(ln[Torr])
7
 Change
6
• X-axis Scale: 2.5-4
• Shorten Title
ln(Pv) (ln[Torr])
5
4
• Clear BackGround
• Lager, Sq Data Markers
• GridLine & Text Colors
3
2
1
0
0
0.5
1
1.5
2
2.5
3
3.5
1000/T (1/Kelvin)
Engineering/Math/Physics 25: Computational Methods
16
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
4
4.5
Chart Construction Demo (10)
 Select Chart Area
Then
Right-Clik
Engineering/Math/Physics 25: Computational Methods
17
 Select X-axis, Ther
Right-Clik
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (11)
 Select Grid Lines,
Rt-Clik, Chg Colors
Engineering/Math/Physics 25: Computational Methods
18
 Select Data Series,
Rt-Clik,
Chg Marker
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (12)
 Position Labels at Page Edges → Stretch-Out
Plot Area
Engineering/Math/Physics 25: Computational Methods
19
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (13)
 Chart Fine-Tuning Result
SnCl4Vapor Pressure
7
 Add TrendLine to find
Clapeyron m &b
Constants
6
ln(Pv) (ln[Torr])
5
4
3
2
1
0
2.5
2.75
3
3.25
3.5
3.75
1000/T (1/Kelvin)
Engineering/Math/Physics 25: Computational Methods
20
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
4
Chart Construction Demo (14)
 Select Data Series,
Rt-Clik,
Add TrendLn
Engineering/Math/Physics 25: Computational Methods
21
 Select: Linear,
Display Parameters
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (15)
 Fine Tune TrendLine Form & Display
SnCl4Vapor Pressure
SnCl4Vapor Pressure
8
8
7
7
6
6
5
5
ln(Pv) (ln[Torr])
ln(Pv) (ln[Torr])
ln(Pv) = -4.7201(1000/T) + 18.958
2
R = 0.9992
4
3
4
3
2
2
1
1
0
2.5
2.75
3
3.25
1000/T (1/Kelvin)
3.5
y = -4.7201x + 18.958
R2 = 0.9992
3.75
4
0
2.5
2.75
3
3.25
3.5
1000/T (1/Kelvin)
 Done with Plot; and have
determined m & b by Trendline
• Note that the Fit is Excellent;
2 = 99.92%
R
Bruce Mayer, PE
Engineering/Math/Physics 25: Computational Methods
22
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
3.75
4
Chart Construction Demo (16)
 Add Fitted Data to table
Calc Error
=(G4-E4)/E4
Calc Using m & b
Analysis of Fit Characteristics
Copy & Paste from Chart
Engineering/Math/Physics 25: Computational Methods
23
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
 Put Fitted Data on Chart
• On Table: Select & Copy
Data
• On chart: EDIT → PASTE
SPECIAL → dialog Box
above
Engineering/Math/Physics 25: Computational Methods
24
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (17)
 Fine Tune Two-Variable Display
SnCl4Vapor Pressure
8
ln(Pv) = -4.7201(1000/T) + 18.958
2
R = 0.9992
7
6
ln(Pv) (ln[Torr])
5
4
 To Make Error Data
More Visible Show
using SECONDARY
Axis at Right
3
2
Error Data Series
1
0
2.5
2.75
3
3.25
3.5
3.75
4
-1
1000/T (1/Kelvin)
Engineering/Math/Physics 25: Computational Methods
25
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (18)
SnCl4Vapor Pressure
8
12.0%
7
10.0%
ln(Pv) = -4.7201(1000/T) + 18.958
2
R = 0.9992
8.0%
6
ln(Pv) (ln[Torr])
6.0%
5
4.0%
4
2.0%
3
0.0%
2
-2.0%
1
-4.0%
0
-6.0%
2.5
2.75
3
3.25
3.5
3.75
1000/T (1/Kelvin)
Engineering/Math/Physics 25: Computational Methods
26
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
4
Chart Construction Demo (19)
 Fine Tune Two-Axes Display
Engineering/Math/Physics 25: Computational Methods
27
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Chart Construction Demo (20)
SnCl4Vapor Pressure
7
12%
ln(Pv)
(ln[Torr])
ln(Pv) = -4.7201(1000/T) + 18.958
2
R = 0.9992
6
10%
Fit Error
8%
5
ln(Pv) (ln[Torr])
6%
4
4%
3
2%
0%
2
-2%
1
-4%
0
-6%
2.5
2.75
3
3.25
3.5
3.75
1000/T (1/Kelvin)
Engineering/Math/Physics 25: Computational Methods
28
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
4
Fit Error = (Fit-Actual)/Actual
Linear (ln(Pv)
(ln[Torr]))
Nice Chart
Engineering/Math/Physics 25: Computational Methods
29
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Coefficient of Correlation
 The coefficient of correlation is an
indication of how well the linear
relationship determined by the method
of least squares fits the data set.
 The equation for the coefficient of
correlation is:
R 
n(xi yi )  (xi )(yi )
n(xi )  (xi )
2
Engineering/Math/Physics 25: Computational Methods
30
2
n(yi )  (yi )2
2
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Interpretation of R
 If R is 0, the points are so scattered that
the regression line does not help predict
y for a given x.
 If R is +1 (positive slope) or –1
(negative slope), the points actually lie
on a straight line so almost perfect
predictions of y for a given x can be
made using the regression line.
Engineering/Math/Physics 25: Computational Methods
31
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Goodness of Fit
R Value
0.9 to 1.0
0.7 to 0.9
0.5 to 0.7
0.3 to 0.5
-0.3 to 0.3
-0.5 to -0.3
-0.7 to -0.5
-0.9 to -0.7
-1.0 to -0.9
Engineering/Math/Physics 25: Computational Methods
32
Correlation
Very high positive
High positive
Moderate positive
Low positive
Little, if any
Low negative
Moderate negative
High negative
Very high negative
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt
Engineering/Math/Physics 25: Computational Methods
33
Bruce Mayer, PE
BMayer@ChabotCollege.edu • ENGR-25_Lec-29_MS_Excel-2.ppt