Excel power users! Are you looking to expand your knowledge in MS Excel?? If so, you need to know how to use array formulas, which can perform calculations that you can\'t do by using non-array formulas. Join Forrest Kovach and I in conference room D1528 to learn how to use array formulas in MS Excel!!
Have you ever wonder how Excel sets the upper limit and the lower limit on th...Jennifer ChiaYu Lin
#Data Visualization #algorithm #Infographic
Have you ever wonder how Excel sets the upper limit and the lower limit on the vertical axis of a chart? And how this may lead to a misleading chart?
In my own case, I have not, until one day I found an obvious mistake on Excel’s dual vertical axes chart.
The mistake is resulted from that Excel does not have an algorithm that can address the most important and inevitable question for dual vertical axes charts: “How to set the upper limits and the lower limits on the TWO vertical axes?”. In fact, Excel simply adopts the same algorithm used for its single vertical axis chart on each vertical axis separately. And thus the elongations of the two axes are not coordinated to be the same, which leads to its misleading dual vertical axes charts.
To solve this critical mistake, Graphician invented a patented algorithm that can create 100% correct dual vertical axes chart. And we have also created a trial Excel Add-in which can adjust any dual vertical axes chart created by Excel 2007 or an advanced version with one single click.
You can now download the Add-in at http://www.graphician.com/patent-01.html. We hope you find the Add-in interesting and useful, and we would love to hear your comment about it if any. You may contact us at graphician1122@gmail.com or visit our website: "www.graphician.com" to find more information.
Using Monte Carlo Simulation in Project Estimates by Akram Najjar
The PMI Lebanon is glad to announce that Akram Najjar is the speaker for the a lecture titled “Using Monte Carlo Simulation in Project Estimates” delivered on Thursday, 28 July 2016
Lecture Outline
* Why are single point estimates unreliable and what is the alternative?
* What are distributions and how do we extract random samples from them (using Excel)? Two costing examples.
* How to setup a Monte Carlo Simulation model in a spreadsheet?
* Two PM examples (in detail)
* How to statistically analyze the thousands of runs to reach reliable estimates?
Lecture Objectives
* A Project Manager usually knows how certain parameters (such as duration, resource rates or quantities) behave. However, the PM can almost never define reliable single point estimates for these parameters. The result: many projects fail due to unreliable estimates. The alternative? The PM has to use his/her knowledge of how specific parameters behave statistically. For example, the PM knows that a specific task’s duration is distributed according to the bell shaped curve OR that another is uniformly distributed (flat variation), or triangular, or Beta-PERT, etc. The PM can then use Monte Carlo Simulation (MCS) to arrive at statistically significant and robust results. Monte Carlo Simulation (MCS) is a technique that relies on two processes. Process 1 aims at developing a spreadsheet model that calculates the critical path or the total cost, etc. The calculation is setup in a single row (or Run). This row is then duplicated a large number of times (thousands). Process 2 aims at inserting Excel functions in each of the parameters (durations, costs). In each row (or Run), such functions will provide a sample drawn from a statistical distribution that properly describes the behavior of that parameter. For example, a specific duration follows a Normal (Bell) distribution with an Average A and a Standard Deviation S. The model will then generate for each run and for that duration a different value that conforms with the bell shaped curve as defined (A and S). Each of these thousands of runs will provide the PM with a different “simulation” of the duration or the total cost, etc. By statistically analyzing the thousands of results, the PM can arrive at a robust and reliable estimate. Proprietary Add On’s for Monte Carlo Simulation in Microsoft Project are available. However, it is easy, free and more flexible to use native Microsoft functions to carry out the full simulation. The talk covered all the steps needed for such simulations giving several examples
Have you ever wonder how Excel sets the upper limit and the lower limit on th...Jennifer ChiaYu Lin
#Data Visualization #algorithm #Infographic
Have you ever wonder how Excel sets the upper limit and the lower limit on the vertical axis of a chart? And how this may lead to a misleading chart?
In my own case, I have not, until one day I found an obvious mistake on Excel’s dual vertical axes chart.
The mistake is resulted from that Excel does not have an algorithm that can address the most important and inevitable question for dual vertical axes charts: “How to set the upper limits and the lower limits on the TWO vertical axes?”. In fact, Excel simply adopts the same algorithm used for its single vertical axis chart on each vertical axis separately. And thus the elongations of the two axes are not coordinated to be the same, which leads to its misleading dual vertical axes charts.
To solve this critical mistake, Graphician invented a patented algorithm that can create 100% correct dual vertical axes chart. And we have also created a trial Excel Add-in which can adjust any dual vertical axes chart created by Excel 2007 or an advanced version with one single click.
You can now download the Add-in at http://www.graphician.com/patent-01.html. We hope you find the Add-in interesting and useful, and we would love to hear your comment about it if any. You may contact us at graphician1122@gmail.com or visit our website: "www.graphician.com" to find more information.
Using Monte Carlo Simulation in Project Estimates by Akram Najjar
The PMI Lebanon is glad to announce that Akram Najjar is the speaker for the a lecture titled “Using Monte Carlo Simulation in Project Estimates” delivered on Thursday, 28 July 2016
Lecture Outline
* Why are single point estimates unreliable and what is the alternative?
* What are distributions and how do we extract random samples from them (using Excel)? Two costing examples.
* How to setup a Monte Carlo Simulation model in a spreadsheet?
* Two PM examples (in detail)
* How to statistically analyze the thousands of runs to reach reliable estimates?
Lecture Objectives
* A Project Manager usually knows how certain parameters (such as duration, resource rates or quantities) behave. However, the PM can almost never define reliable single point estimates for these parameters. The result: many projects fail due to unreliable estimates. The alternative? The PM has to use his/her knowledge of how specific parameters behave statistically. For example, the PM knows that a specific task’s duration is distributed according to the bell shaped curve OR that another is uniformly distributed (flat variation), or triangular, or Beta-PERT, etc. The PM can then use Monte Carlo Simulation (MCS) to arrive at statistically significant and robust results. Monte Carlo Simulation (MCS) is a technique that relies on two processes. Process 1 aims at developing a spreadsheet model that calculates the critical path or the total cost, etc. The calculation is setup in a single row (or Run). This row is then duplicated a large number of times (thousands). Process 2 aims at inserting Excel functions in each of the parameters (durations, costs). In each row (or Run), such functions will provide a sample drawn from a statistical distribution that properly describes the behavior of that parameter. For example, a specific duration follows a Normal (Bell) distribution with an Average A and a Standard Deviation S. The model will then generate for each run and for that duration a different value that conforms with the bell shaped curve as defined (A and S). Each of these thousands of runs will provide the PM with a different “simulation” of the duration or the total cost, etc. By statistically analyzing the thousands of results, the PM can arrive at a robust and reliable estimate. Proprietary Add On’s for Monte Carlo Simulation in Microsoft Project are available. However, it is easy, free and more flexible to use native Microsoft functions to carry out the full simulation. The talk covered all the steps needed for such simulations giving several examples
Elementary Data Analysis with MS Excel_Day-4Redwan Ferdous
This event took place on 12th September 2020. This was arranged by EMK Center (Makerlab). The title was 'Elementary Data Analysis with MS Excel', where very basic data analysis with MS excel was discussed.
In Day-4, the MS Excel Data Tab, View and Review tab as well as Developer Tab of Horizontal top ribbon was discussed. As well as different Quick analysis tools, What-if Analysis, Data Table, Scenario Manager, Pareto Chart was also discussed.
A presentation to provide an overview of one of the important heading in MS-Excel; Formula Tab .
In particular i have presented the here in these slides , 2-sub Categories ;(a) Function Library (b) Formula Auditing
Note: Useful for students of CA fraternity.
Get the insider’s tour of the implementation and the technologies used to enable Interactive Charts to plot hundreds of thousands data points and interact with them in real time. The Accelrys R&D Team will explain how the popular Interactive Charts were revamped to meet needs to handle Big Data visualization.
A Powerpoint Presentation designed to provide beginners to MATLAB an introduction to the MATLAB environment and introduce them to the fundamentals of MATLAB including matrix generation and manipulation, Arrays, MATLAB Graphics, Data Import and Export, etc
Learn VBA Training & Advance Excel Courses in Delhiibinstitute0
Investment Banking Institute (IBI) is the one of the most accepted & highly reputed institute of investment banking education which offers both online and corporate training of basic & advance excel 2010, financial modeling & company valuation, VBA training. Weekend classes of financial modeling & advance excel training in Delhi are provided by this reputed corporate banking institute to professionals & students at an outstanding level.
The art of querying – newest and advanced SQL techniquesZohar Elkayam
Presentation from Oracle Week 2017.
Agenda:
Aggregative and advanced grouping options
Analytic functions, ranking and pagination
Hierarchical and recursive queries
Regular Expressions
Oracle 12c new rows pattern matching
XML and JSON handling with SQL
Oracle 12c (12.1 + 12.2) new features
SQL Developer Command Line tool (if time allows)
Oracle 18c
(Slides) Efficient Evaluation Methods of Elementary Functions Suitable for SI...Naoki Shibata
Naoki Shibata : Efficient Evaluation Methods of Elementary Functions Suitable for SIMD Computation, Journal of Computer Science on Research and Development, Proceedings of the International Supercomputing Conference ISC10., Volume 25, Numbers 1-2, pp. 25-32, 2010, DOI: 10.1007/s00450-010-0108-2 (May. 2010).
http://www.springerlink.com/content/340228x165742104/
http://freshmeat.net/projects/sleef
Data-parallel architectures like SIMD (Single Instruction Multiple Data) or SIMT (Single Instruction Multiple Thread) have been adopted in many recent CPU and GPU architectures. Although some SIMD and SIMT instruction sets include double-precision arithmetic and bitwise operations, there are no instructions dedicated to evaluating elementary functions like trigonometric functions in double precision. Thus, these functions have to be evaluated one by one using an FPU or using a software library. However, traditional algorithms for evaluating these elementary functions involve heavy use of conditional branches and/or table look-ups, which are not suitable for SIMD computation. In this paper, efficient methods are proposed for evaluating the sine, cosine, arc tangent, exponential and logarithmic functions in double precision without table look-ups, scattering from, or gathering into SIMD registers, or conditional branches. We implemented these methods using the Intel SSE2 instruction set to evaluate their accuracy and speed. The results showed that the average error was less than 0.67 ulp, and the maximum error was 6 ulps. The computation speed was faster than the FPUs on Intel Core 2 and Core i7 processors.
More Related Content
Similar to Knowledge Area By Project Phase Excel Array Formulas
Elementary Data Analysis with MS Excel_Day-4Redwan Ferdous
This event took place on 12th September 2020. This was arranged by EMK Center (Makerlab). The title was 'Elementary Data Analysis with MS Excel', where very basic data analysis with MS excel was discussed.
In Day-4, the MS Excel Data Tab, View and Review tab as well as Developer Tab of Horizontal top ribbon was discussed. As well as different Quick analysis tools, What-if Analysis, Data Table, Scenario Manager, Pareto Chart was also discussed.
A presentation to provide an overview of one of the important heading in MS-Excel; Formula Tab .
In particular i have presented the here in these slides , 2-sub Categories ;(a) Function Library (b) Formula Auditing
Note: Useful for students of CA fraternity.
Get the insider’s tour of the implementation and the technologies used to enable Interactive Charts to plot hundreds of thousands data points and interact with them in real time. The Accelrys R&D Team will explain how the popular Interactive Charts were revamped to meet needs to handle Big Data visualization.
A Powerpoint Presentation designed to provide beginners to MATLAB an introduction to the MATLAB environment and introduce them to the fundamentals of MATLAB including matrix generation and manipulation, Arrays, MATLAB Graphics, Data Import and Export, etc
Learn VBA Training & Advance Excel Courses in Delhiibinstitute0
Investment Banking Institute (IBI) is the one of the most accepted & highly reputed institute of investment banking education which offers both online and corporate training of basic & advance excel 2010, financial modeling & company valuation, VBA training. Weekend classes of financial modeling & advance excel training in Delhi are provided by this reputed corporate banking institute to professionals & students at an outstanding level.
The art of querying – newest and advanced SQL techniquesZohar Elkayam
Presentation from Oracle Week 2017.
Agenda:
Aggregative and advanced grouping options
Analytic functions, ranking and pagination
Hierarchical and recursive queries
Regular Expressions
Oracle 12c new rows pattern matching
XML and JSON handling with SQL
Oracle 12c (12.1 + 12.2) new features
SQL Developer Command Line tool (if time allows)
Oracle 18c
(Slides) Efficient Evaluation Methods of Elementary Functions Suitable for SI...Naoki Shibata
Naoki Shibata : Efficient Evaluation Methods of Elementary Functions Suitable for SIMD Computation, Journal of Computer Science on Research and Development, Proceedings of the International Supercomputing Conference ISC10., Volume 25, Numbers 1-2, pp. 25-32, 2010, DOI: 10.1007/s00450-010-0108-2 (May. 2010).
http://www.springerlink.com/content/340228x165742104/
http://freshmeat.net/projects/sleef
Data-parallel architectures like SIMD (Single Instruction Multiple Data) or SIMT (Single Instruction Multiple Thread) have been adopted in many recent CPU and GPU architectures. Although some SIMD and SIMT instruction sets include double-precision arithmetic and bitwise operations, there are no instructions dedicated to evaluating elementary functions like trigonometric functions in double precision. Thus, these functions have to be evaluated one by one using an FPU or using a software library. However, traditional algorithms for evaluating these elementary functions involve heavy use of conditional branches and/or table look-ups, which are not suitable for SIMD computation. In this paper, efficient methods are proposed for evaluating the sine, cosine, arc tangent, exponential and logarithmic functions in double precision without table look-ups, scattering from, or gathering into SIMD registers, or conditional branches. We implemented these methods using the Intel SSE2 instruction set to evaluate their accuracy and speed. The results showed that the average error was less than 0.67 ulp, and the maximum error was 6 ulps. The computation speed was faster than the FPUs on Intel Core 2 and Core i7 processors.
Similar to Knowledge Area By Project Phase Excel Array Formulas (20)
2. Why Me?
• What is in it for you?
• What is in it for me?
• Get what you can out the presentation, we will progress from
simple to more advanced, if you learn anything we both are
successful.
• Per Microsoft Documentation “To become an Excel power
user, you need to know how to use array formulas, which
can perform calculations that you can't do by using non-
array formulas.”
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3. Two Generations ago
• 1980-2000 - Generation Y
• 1965-1979 - Generation X
• 1946-1964 - Baby Boom
• High Tech Existed
• Completed Bachelor of Science in 1986
• I share the Same Nick Name with Rene
• “Daddy”
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4. Mute the phone during presentation.
Cell Phones on Vibrate
Give name before speaking.
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5. Excel Array
Formulas
Array formulas are a great tool in Excel. An array formula is a
formula that works with an array, or series, of data values rather than
a single data values.
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6. Better than sliced bread!
Excel Array Formulas
Quick, Easy and Fast
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7. What is an Excel Array Formula?
• A formula that performs multiple calculations on sets of
values, and then returns either a single result or multiple
results.
• Array formulas are enclosed between braces { } and are Excel
created by pressing CTRL+SHIFT+ENTER.
• You could see array formulas denoted to as "CSE formulas,"
since you press CTRL+SHIFT+ENTER to enter them into
workbooks.
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8. Two Types of Array Formulas
• Aggregate: typically using SUM, AVERAGE, or COUNT, to
return a single cell
• Multiple Result: returns a result in to two or more cells. These
types of array formulas return an array of values as their result.
• Limited to two dimensions
Our focus will be single result array formulas
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9. Why use Excel Array Formulas?
• Allows more complex calculations than standard formulas.
• In some cases a spreadsheet solution is not possible without
using array formulas.
• Faster calculating and more flexible thank Visual Basic
Applications
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10. Array Formula Users
• How many folks have used array formulas with Ctrl-Shift-Enter
{}?
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11. Single Result Array Formula
• Simplifies a worksheet by replacing several formulas with a
single array formula.
• For example, the following calculates the total value of an
array of stock prices and shares, without using a column of
cells to calculate the individual values for each stock.
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12. Non-Array Method
Stock Shares Price Value
A 100 $10 $1,000
B 200 $20 $4,000
C 200 $25 $5,000
D 100 $8 $800
E 200 $90 $18,000
$28,800
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13. Single Result Array Formula
Stock Shares Price • How does a single
A
B
100 $10
200 $20
formula create the
C
D
200 $25
100 $8
individual totals and a
E 200 $90 comprehensive total?
$28,800
• The secret is in Ctrl+Shift+Enter and
Excel responds with {}
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14. Single Result Array Formula
=SUM(B2*C2,B3*C3,B4*C4,B5*C5,B6*C6)
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15. Single Result Array Formula
• Formula from the stock sheet
{=SUM(B2:B6*C2:C6)}
Says Take each B and multiply by each C
Then Sum all results
Array formulas have imbedded functions
Enter with Ctrl+Shift+Enter
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16. Operator Precedence
• () Parentheses
• : (colon) Note Array Range is First
• , (comma)
• ^ Exponentiation
• * and / Multiplication and division
• + and – Addition and subtraction
• = < > <= >= <> Comparison
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17. Multiple Result Array Formula
• Even trickier to enter • Output is one for one
with array data
• We will look at the
Trend Function
• Enter formula in last
output cell while the
out put range is
highlighted
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22. Dell OPAS Example
Notification Contains Count
DISK 713
CPU 8
APPLICATION 786
5000 lines of OPAS Incidents
=SUM(IF(ISNUMBER(SEARCH(A3,Data!Y2:Data!Y5001)),1, 0))
New Functions
• ISNUMBER = Does cell contain a number? IF true jump to 0
• SEARCH for text A3 in Array, Count 1 for each hit.
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26. Hot Stuff!
• Using multiple windows edit the production details and see
the aggregate results instantaneously!
• Sorting and counting is for Chumps!
Use the Power of Array Formulas.
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29. Formula Breakdown
• {=SUM(IF('RPCM-HRL'!$N$10:$N$297>=E$1,
Datasheet name Delivery forecast dates Greater or
$ for fixed range equal to
date
And
header
IF('RPCM-HRL'!$N$10:$N$297<F$1, Less than
next
Delivery forecast dates column
$ for fixed range header
And
Count 1, else 0
IF('RPCM-HRL'!$D$10:$D$297=$B3,1,0))))}
Flight Number from Equals
data sheet Row label =2
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30. Metrics
• Reveal the health of a project where there is too much data to
comprehend
• Can lead to cause and effect analysis
• May give clues to solutions
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31. Instant Metrics from MSP Data
• Set-up a table in MSP
(Usually non-summary records)
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32. Instant Metrics from MSP Data
• Copy data from MSP table to Excel
Pasted data from project will show date format based
on default settings, that is time included.
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33. Schedule Trend
3900
Schedule Trend Completions
3850
3800
3750
3700
3650 Cum Baseline Schedule
3600
Cum Estimate
Cum Actuals thru Status Date
3550
3500
Actuals in
01May08
08May08
15May08
22May08
29May08
13Mar08
20Mar08
27Mar08
05Jun08
12Jun08
19Jun08
03Apr08
10Apr08
17Apr08
24Apr08
Future
Weeks (Thursday
End)
Weekly Baseline
11 7 13 16 6 9 9 20 25 31 17 15 25 11 30
Schedule
Weekly Estimate 8 20 74 7 10 5 10 16 17 17 20 20 19 14 24
Weekly Actual 10 7 13 15 6 8 6
Cum Baseline
3559 3566 3579 3595 3601 3610 3619 3639 3664 3695 3712 3727 3752 3763 3793
Schedule
Cum Estimate 3513 3533 3569 3585 3593 3600 3611 3631 3655 3673 3696 3716 3738 3752 3780
Cum Actuals thru
3513 3533 3569 3585 3593 3600
Status Date
Cum Late to
46 33 10 10 8 10 8 8 9 22 16 11 14 11 13
Baseline
Cum Late to
0 0 0 0 0 0
Estimate
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34. Schedule Trend
3900
Schedule Trend Starts
3850
3800
3750
3700
Cum Baseline Schedule
3650 Cum Estimate
Cum Actuals thru Status Date
3600
3550
3500
Actuals in
01May08
08May08
15May08
22May08
29May08
13Mar08
20Mar08
27Mar08
05Jun08
12Jun08
19Jun08
03Apr08
10Apr08
17Apr08
24Apr08
Future
Weeks (Thursday
End)
Weekly Baseline
5 5 8 17 5 20 9 18 24 38 12 19 23 8 13
Schedule
Weekly Estimate 10 6 46 13 6 10 13 16 18 22 17 23 22 10 13
Weekly Actual 4 5 8 17 3 16 2
Cum Baseline
3599 3604 3612 3629 3634 3654 3663 3681 3705 3743 3755 3774 3797 3805 3818
Schedule
Cum Estimate 3586 3592 3605 3621 3627 3642 3656 3674 3698 3721 3740 3764 3788 3798 3813
Cum Actuals thru
3586 3592 3605 3621 3627 3642
Status Date
Cum Late to
13 12 7 8 7 12 7 7 7 22 15 10 9 7 5
Baseline
Cum Late to
0 0 0 0 0 0
Estimate
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36. Baseline Count Formula
3900
Schedule Trend Completions
3850
3800 {=SUM
3750
3700
3650 Cum Baseline Schedule
Cum Estimate
3600
3550
Cum Actuals thru Status Date Baseline Finish Dates
(IF(Data!$G$2:$G$5257<=I$19,
3500
Actuals in
01May08
08May08
15May08
22May08
29May08
13Mar08
20Mar08
27Mar08
05Jun08
12Jun08
19Jun08
03Apr08
10Apr08
17Apr08
24Apr08
Future
Weeks (Thursday
End)
Weekly Baseline
11 7 13 16 6 9 9 20 25 31 17 15 25 11 30
Schedule
Weekly Estimate 8 20 74 7 10 5 10 16 17 17 20 20 19 14 24
Weekly Actual
Cum Baseline
10
3559 3566
7 13
3579
15
3595 3601
6
3610
8
3619 3639 3664 3695 3712 3727 3752 3763 3793
6
Date is greater than 0 i.e. not NA
Schedule
IF(Data!$G$2:$G$5257>0,1,0)))
Cum Estimate 3513 3533 3569 3585 3593 3600 3611 3631 3655 3673 3696 3716 3738 3752 3780
Cum Actuals thru
3513 3533 3569 3585 3593 3600
Status Date
Cum Late to
}
46 33 10 10 8 10 8 8 9 22 16 11 14 11 13
Baseline
Cum Late to
Estimate
0 0 0 0 0 0
Cum 1 or 0
3610
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37. One More Formula
3900
Schedule Trend Completions
3850
3800
3750
3700
3650 Cum Baseline Schedule
3600
Cum Estimate
Cum Actuals thru Status Date
3550
3500
Actuals in
01May08
08May08
15May08
22May08
29May08
13Mar08
20Mar08
27Mar08
05Jun08
12Jun08
19Jun08
03Apr08
10Apr08
17Apr08
24Apr08
Future
Weeks (Thursday
End)
Weekly Baseline
11 7 13 16 6 9 9 20 25 31 17 15 25 11 30
Schedule
Weekly Estimate 8 20 74 7 10 5 10 16 17 17 20 20 19 14 24
Weekly Actual 10 7 13 15 6 8 6
Cum Baseline
3559 3566 3579 3595 3601 3610 3619 3639 3664 3695 3712 3727 3752 3763 3793
Schedule
Cum Estimate 3513 3533 3569 3585 3593 3600 3611 3631 3655 3673 3696 3716 3738 3752 3780
Cum Actuals thru
3513 3533 3569 3585 3593 3600
Status Date
Cum Late to
46 33 10 10 8 10 8 8 9 22 16 11 14 11 13
Baseline
Cum Late to
0 0 0 0 0 0
Estimate
8
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38. Another Formula
Test if data is less than Test if greater than Check if Base line
upper boundary prior period date exists
{=SUM(IF(Data!$G$2:$G$5257<=I$19,IF(Data!$G$2:$G$5257>H$19,IF(Data!$I$2:$I$5257<>"NA",1,0))))}
Accumulate 1 for every true condition, 0 for false condition
Close Parenthesis Count Must Match Open Parenthesis Count
Do not enter Brackets, Excel will add Bracket Automatically
Remember Enter Formula with
Ctrl-Shift-Enter Simultaneously
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39. Drag and Fill
• When the initial column or row of array formulas are entered
with Crtl-Shift Enter the formula may be dragged filled to
other cells without Crtl-Shift Enter
• Be careful the array has absolute cell references ($) and the
formula arguments have $ and relative arguments suitable for
a drag fill.
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40. Drag and Fill
• Also you may wish to
turn Tools – Option –
Calculation to Manual
while creating or using
Array Formulas
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41. Do you have any Applications in Mind?
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