Advanced Excel Data Analysis Template

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Dell Inc Source: YahooDate Open High Low Close Volume Adj. Close*18-Apr-05 35.36 35.85 35.29 35.37 13937600 35.3715-Apr-05 35.46 36.06 35.34 35.56 22655500 35.5614-Apr-05 36.95 37.03 36.08 36.18 23239200 36.1813-Apr-05 37.53 37.69 36.89 36.91 15228600 36.9112-Apr-05 37.85 37.92 37.21 37.61 21964300 37.6111-Apr-05 38.27 38.34 37.73 37.89 11249700 37.8908-Apr-05 38.69 38.7 38.1 38.18 13330900 38.1807-Apr-05 38.41 38.56 37.92 38.5 18571500 38.506-Apr-05 39.1 39.15 37.92 38.15 27468700 38.1505-Apr-05 38.65 39.16 38.65 39.13 12251700 39.1304-Apr-05 38.04 38.95 38.01 38.68 16324600 38.6801-Apr-05 38.53 38.61 38.02 38.03 15541500 38.0331-Mar-05 38.47 38.95 38.29 38.42 13003300 38.4230-Mar-05 38.13 38.73 37.85 38.55 10980200 38.5529-Mar-05 38.13 38.45 37.99 38.14 10815000 38.1428-Mar-05 38.5 38.62 38.12 38.18 10304100 38.1824-Mar-05 38.47 38.9 38.3 38.38 12037500 38.3823-Mar-05 38.05 38.62 38.04 38.43 12613600 38.4322-Mar-05 38.32 38.7 38.04 38.04 13137500 38.0421-Mar-05 38.51 38.57 37.96 38.42 14381500 38.4218-Mar-05 38.21 38.66 38.02 38.5 19067000 38.517-Mar-05 38.65 38.73 38.14 38.2 16566800 38.216-Mar-05 38.95 39.2 38.6 38.7 15539000 38.715-Mar-05 39.51 39.58 39 39.06 14045600 39.0614-Mar-05 39.68 39.8 39.16 39.5 18208700 39.511-Mar-05 40.46 40.46 39.5 39.71 17618200 39.7110-Mar-05 40.16 40.3 39.81 40.17 12563200 40.1709-Mar-05 40.21 40.48 39.99 40.16 11660300 40.1608-Mar-05 40.3 40.61 40.2 40.22 11266300 40.2207-Mar-05 40.63 40.85 40.33 40.49 16400500 40.4904-Mar-05 40.44 40.93 40.32 40.87 18794200 40.8703-Mar-05 40.23 40.39 39.95 40 17142700 4002-Mar-05 40.32 40.75 40.19 40.29 11323600 40.2901-Mar-05 40.16 40.53 40.09 40.4 14001200 40.428-Feb-05 40.15 40.29 39.75 40.09 20046900 40.0925-Feb-05 40.13 40.33 39.88 40.2 10759300 40.2


Alternatives and Examples of Switches

OPTIONS and SYNTAX: Pros Cons

if =IF(logical_test,value_if_true,value_if_false) easy for 2 caseschoose =CHOOSE(index_num,value1,value2,...) easy to understand limited to 29 optionsoffset =OFFSET(reference,rows,cols) unlimited cases tedious to code, harder to check

ScenariosCase Growth Margin

1 10% 5%2 15% 6%3 20% 7%

Select Case: 1

IF FUNCTION OFFSET FUNCTIONGrowth Margin Example: # of columns across

1) 10% NA need to anchor the case number Reference Cell: 0 1 2 3 4 52) 10% 5% slightly more transparent 1 1,1 1,2 1,3 1,4 1,5

# of 2 2,1 2,2 2,3 2,4 2,5IF function is not as transparent when you exceed 2 options. rows 3 3,1 3,2 3,3 3,4 3,5It is more difficult to follow, but makes more intuitive sense. down 4 4,1 4,2 4,3 4,4 4,5

5 5,1 5,2 5,3 5,4 5,5

3 rows down, 2 columns across from the reference cell: 3,2CHOOSE FUNCTION

Growth Margin Growth Margin10% 5% 10% 5% use the label as the reference cell

and the case number as the offset variableCHOOSE function is transparent and easy to follow.Best tradeoff between power and ease of use. OFFSET function is the most versatile, but more difficult to code and to check.

But once it's coded, it is extremely powerful.

For switches that require only a "Yes" or "No", the easiest alternative is not an IF, CHOOSE or OFFSET statement, but simply to multiply by 0 or 1.A 0 signifies "No" or "Off" (lack of) and a 1 signifies "Yes" or "On".For example:

Refinance Existing Debt? 1 New Debt $2,000.0

Total Existing Debt: $1,000.0 Existing Debt 1,000.0 Total New Debt Raised $3,000.0

This removes the need for an if statement or any other function, greatly eases coding and is transparent and easy to follow.

limited to 7 nested if loops, non transparent for more than 2 logical tests


LEAST SQUARES REGRESSION

QUESTIONA five year growth rate could be determined by calculating the growth betweenEPS 6 years ago and the current fiscal year EPS. I have noticed however, that some firms use a least squares method to calculate growth, which provides a growth rate that better fits the increase in EPS values over each year within a 5 year period.

Do you know how to calculate this least squares growth rate using Excel? Are there any sources that you may know about that describes this calculation in a form that can be easily translated into an Excel format?

RESPONSEy = mx + b is the equation that minimizes the squared differences.In general you always want to calcualte average growth anyway and that can be done thru a CAGR approach which, in effect, sort of proxies aleast square approach already. Think of the straight line in the chart If you refer to a statistics textbook or Excel help, you will see the following:at the right – it doesn't really matter how eps got from $1.00 to $1.70,but it got there with an "average" growth of 11.2% each year.

Don't forget your end goal: to calculate forecasted EPS!

In general, I would calculate EPS growth in one of the following ways:1) Growth from internal mgmt projections – this is probably the bestgrowth rate to use. Without this, use analyst estimates.2) Analyst Estimates – this is ideal since you can point and say,this is what Wall Street says. Who better than to refer to, unlessyou are research analyst in charge of estimating a 5-yr growth, but then it's a moot point because you would have access to mgmt.If you are the research analyst without access to mgmt, you would Also, you may have Excel generate an ANOVA table: TOOLS => DATA ANALYSIS => ANOVA SINGLEbe doing your own research and building your own financial model that will provide you with numeric descriptives on least squares (or sum of squared differences) to verify.anyway and therefore would have your own estimate already.3) Historical CAGR Note:4) Industry projections (be sure to adjust for firm specific differences) If you don't believe that the growth is linear, but rather, logarithmic or exponential, then clearly y = mx +b

would not suit your purposes. You would use another power - To illustrate, select the above chart with yourPeriod EPS Growth CAGR Check mouse and then click on CHARTS => ADD TRENDLINE => TYPE and select different types of trendlines.

1 $ 1.00 To show the equation, swith to OPTIONS tab and click on Display Equation on Chart.2 1.20 20.0%3 1.30 8.3% To directly address your question, regardless of what power you use to trend out growth or4 1.45 11.5% forecasts, it is always calculated using least squares method.5 1.62 11.7%6 1.70 4.9% 11.2% Again, keep your end goal in mind and that is to calculate forecasted EPS!7 1.87 10.0% $ 1.87 8 2.01 7.5% 8.7% 2.01

actual slope interceptforecast 14.03% 0.887

LINEST Function: Calculates the statistics for a line by using the "least squares" method to calculate a straight line that best fits your data, and returns an array that describes the line.

In regression analysis, Microsoft Excel calculates for each point the squared difference between the y-value estimated for that point and its actual y-value. The sum of these squared differences is called the residual sum of squares. Microsoft Excel then calculates the sum of the squared differences between the actual y-values and the average of the y-values, which is called the total sum of squares (regression sum of squares + residual sum of squares). The smaller the residual sum of squares is, compared with the total sum of squares, the larger the value of the coefficient of determination, r2, which is an indicator of how well the equation resulting from the regression analysis explains the relationship among the variables.

0 1 2 3 4 5 6 7

$ 0.80

$ 1.00

$ 1.20

$ 1.40

$ 1.60

$ 1.80

f(x) = 0.140285714285714 x + 0.887333333333333f(x) = 0.140285714285714 x + 0.887333333333333R² = 0.989422346865488


DATA TABLEA range of cells that shows the results of substituting different values in one or more formulas. There are two types of data tables: one-input tables and two-input tables.) Go to DATA => TABLE and enter in either ROW or COLUMN INPUT CELL

Data Table with One Input a b coutput cell that you want to sensitize

input a 2 1 inputs that you want to use as driversoutput b=a+2 4 2 bold = current matching outputoutput c=a*3 6 3

45

Data Table with Two Inputs a1 2 3 4 5

input a 1

b

1input b 2 2output c c=a*2+b*3 8 3

45

Example 1:Given certain Revenue growth and EBITDA margins,what is the value of the company in Year 2 assuming Value of Company in Year 2:it is worth 7x Year 2's EBITDA? YoY Revenue Growth

0.0% 5.0% 10.0% 15.0%Year 0 Year 1 Year 2

Ma

rgin

20.0%Revenue $ 100.0 $ 110.0 $ 121.0 25.0%

Growth 10% 10% 30.0%EBITDA 30.0 33.0 36.3 35.0%

Margin 30.0% 30.0% 30.0% 40.0%

Value of Company: 7.0x EBITDAin Year 2: = $ 254.1

Example 2:Estimate an asset management firm's revenue given Estimated Revenuea range of AUM (Assets Under Management) and Fees charged AUM ($MM's)

$ 250.0 $ 500.0 $ 750.0 $ 1,000.0 AUM ($MM's) $ 500.0

Fe

e (

BP

S) 75.0

Fee (BPS) 100.0 100.0 Revenue ($MM's) $ 5.0 125.0

150.0 175.0


VLOOKUP EXPLANATIONSearches for a value in the leftmost column of a table, and then returns a value in the same row from a column you specify in the table.The V in VLOOKUP stands for "Vertical."

1st 2nd Look up the 1st and 2nd corresponding number for ID Number:Corresponding Corresponding 327666

ID Number Number Number142319 756096 2123214099 622747 1334222279 813299 971292039 429388 2699327666 234559 985618840 620124 2555715908 205941 1293831016 761369 375835463 134530 1128841424 445161 4422881937 209245 2941


Dell IncDate Open High Low Close Volume Adj. Close* PROBLEM:

1/3/2000 51.38 51.88 48.31 50.88 35931600 50.88 Look up month end closing price and volume1/4/2000 48.06 49.25 46.5 46.63 36143700 46.631/5/2000 47 50.06 46.88 49.94 51134200 49.94 SOLUTION:1/6/2000 47.56 49.13 47.06 48 28913700 48 Date Price Volume1/7/2000 47.06 47.98 44.88 46.19 45193000 46.19 1/31/2000

1/10/2000 46.44 46.5 43.75 44.13 41094800 44.13 2/29/20001/11/2000 43.56 44.63 42.5 42.81 33892500 42.81 3/31/20001/12/2000 43 44 41.75 41.81 30608900 41.81 4/30/20001/13/2000 43.06 43.69 42.63 43.13 33030000 43.13 5/31/20001/14/2000 44.31 46.06 43.88 44 41192000 44 6/30/20001/18/2000 43.88 44 41.94 42.06 32465000 42.06 7/31/20001/19/2000 41.75 42.97 41 42.5 28433400 42.5 8/31/20001/20/2000 43.69 44.44 42.5 43.75 27533900 43.75 9/30/20001/21/2000 43.88 44.75 43.44 43.75 22001700 43.75 10/31/20001/24/2000 42.55 43.13 41.31 41.56 30987500 41.56 11/30/20001/25/2000 41.5 42.63 40.75 42.13 22614500 42.13 12/31/20001/26/2000 41.06 42 39.5 40.38 22359500 40.38 1/31/20011/27/2000 39.55 41 37.44 37.56 22770500 37.56 2/28/20011/28/2000 37.88 39.56 37.06 37.25 50129400 37.25 3/31/20011/31/2000 37.5 38.56 37 38.44 34099800 38.44 4/30/2001

2/1/2000 38.56 39.13 37.5 38.94 28727000 38.94 5/31/20012/2/2000 38.88 39.19 38 38.13 24821900 38.13 6/30/20012/3/2000 38.38 38.88 38.13 38.5 28688100 38.5 7/31/20012/4/2000 38.56 39 38.31 38.5 18617000 38.5 8/31/20012/7/2000 38.5 38.63 37.48 37.63 20531100 37.63 9/30/20012/8/2000 36.94 37.81 35 37.06 69018896 37.06 10/31/20012/9/2000 36.31 37.17 35.5 35.56 30260300 35.56 11/30/2001

2/10/2000 36.25 39.25 36.13 38.8 44485800 38.8 12/31/20012/11/2000 39.38 39.38 36.81 36.88 43769400 36.88 1/31/20022/14/2000 37.13 37.5 36.25 36.44 24443400 36.44 2/28/20022/15/2000 36.44 38.06 36 37.88 28243700 37.88 3/31/20022/16/2000 37.75 38.63 37.13 38 29807200 38 4/30/20022/17/2000 38.31 40.69 37.45 40.69 44101900 40.69 5/31/20022/18/2000 40.06 40.5 39.69 40.06 28486600 40.06 6/30/20022/22/2000 39.63 40.13 38 39.81 23891600 39.81 7/31/20022/23/2000 39 42.06 39 41.38 38281700 41.38 8/31/20022/24/2000 41.5 43.44 41.06 42.38 61460000 42.38 9/30/20022/25/2000 43.63 43.81 41 41.25 29408900 41.25 10/31/20022/28/2000 40.25 41.13 39.5 41 28549100 41 11/30/20022/29/2000 40.69 41 39.63 40.81 26957500 40.81 12/31/2002

3/1/2000 40.19 43.19 39.94 43.02 56355200 43.02 1/31/20033/2/2000 42.19 45 41.88 44.94 53104100 44.94 2/28/2003


List of institutions that have invested in certain alternative asset classesSummarize results in a coherent manner=> CREATE PIVOT TABLE

Count Name of Institution Type Region Product Type AUM ($MM)1 XYZ Company Foundation Europe Private Equity $ 158,865 3.5%2 XYZ Company Public Asia HFOF $ 138,042 12.3%3 XYZ Company Foundation Asia Real Estate $ 155,570 3.0%4 XYZ Company Foundation N. AmericaAlternatives $ 96,905 11.5%5 XYZ Company Corporate Asia PE FOF $ 148,483 6.7%6 XYZ Company Endowment Asia Hedge Fund $ 93,160 19.5%7 XYZ Company Endowment N. AmericaReal Estate $ 166,681 4.2%8 XYZ Company Foundation N. AmericaPE FOF $ 14,171 2.6%9 XYZ Company Corporate N. AmericaPE FOF $ 16,018 10.2%

10 XYZ Company Foundation N. AmericaReal Estate $ 151,393 13.3%11 XYZ Company Corporate Europe PE FOF $ 76,621 7.6%12 XYZ Company Foundation Europe Real Estate $ 138,571 23.9%13 XYZ Company Public Europe Alternatives $ 143,151 9.6%14 XYZ Company Corporate Europe Hedge Fund $ 132,701 12.5%15 XYZ Company Corporate N. AmericaReal Estate $ 102,919 17.3%16 XYZ Company Foundation N. AmericaAlternatives $ 8,307 6.4%17 XYZ Company Foundation Asia Real Estate $ 28,279 20.2%18 XYZ Company Endowment Europe PE FOF $ 166,449 19.4%19 XYZ Company Corporate N. AmericaPE FOF $ 138,669 1.7%20 XYZ Company Corporate N. AmericaHFOF $ 112,476 19.5%21 XYZ Company Foundation Europe Private Equity $ 64,438 21.7%22 XYZ Company Public Asia HFOF $ 85,761 7.2%23 XYZ Company Foundation Asia Private Equity $ 98,000 2.1%24 XYZ Company Public N. AmericaHedge Fund $ 96,798 0.4%25 XYZ Company Public Europe Alternatives $ 94,869 8.3%26 XYZ Company Public N. AmericaHFOF $ 149,255 24.4%27 XYZ Company Corporate N. AmericaHedge Fund $ 76,673 22.5%28 XYZ Company Endowment Europe PE FOF $ 50,751 0.2%29 XYZ Company Endowment Asia HFOF $ 66,476 8.0%30 XYZ Company Corporate N. AmericaReal Estate $ 105,983 8.8%31 XYZ Company Public N. AmericaPE FOF $ 97,941 16.0%32 XYZ Company Endowment N. AmericaPE FOF $ 124,394 18.9%33 XYZ Company Endowment Europe PE FOF $ 117,920 19.4%34 XYZ Company Foundation N. AmericaHFOF $ 138,994 7.6%35 XYZ Company Corporate N. AmericaAlternatives $ 104,866 17.1%36 XYZ Company Corporate Asia PE FOF $ 127,641 5.7%37 XYZ Company Endowment N. AmericaPE FOF $ 8,469 17.3%38 XYZ Company Corporate N. AmericaPE FOF $ 14,655 20.4%39 XYZ Company Foundation Europe Private Equity $ 173,175 13.5%40 XYZ Company Foundation Europe PE FOF $ 197,882 4.2%41 XYZ Company Foundation Europe Hedge Fund $ 37,794 23.3%42 XYZ Company Corporate N. AmericaReal Estate $ 13,264 4.0%43 XYZ Company Corporate Europe Alternatives $ 108,544 16.4%44 XYZ Company Endowment Europe Hedge Fund $ 49,763 6.4%45 XYZ Company Corporate Asia PE FOF $ 164,980 7.3%46 XYZ Company Public N. AmericaHedge Fund $ 109,337 21.0%47 XYZ Company Corporate N. AmericaHFOF $ 36,990 14.0%48 XYZ Company Endowment Asia Alternatives $ 123,511 13.7%49 XYZ Company Public Asia HFOF $ 44,777 12.3%50 XYZ Company Public Asia Private Equity $ 199,874 21.1%51 XYZ Company Endowment Asia Alternatives $ 7,417 4.0%52 XYZ Company Public Asia Private Equity $ 80,390 15.5%53 XYZ Company Public Asia Private Equity $ 149,029 16.4%54 XYZ Company Foundation Asia Alternatives $ 60,311 19.0%55 XYZ Company Public Asia Alternatives $ 155,056 21.0%56 XYZ Company Public Europe Hedge Fund $ 42,571 7.3%57 XYZ Company Endowment Asia Real Estate $ 128,182 5.5%58 XYZ Company Endowment Asia Private Equity $ 120,617 6.2%59 XYZ Company Corporate N. AmericaHedge Fund $ 20,957 7.8%60 XYZ Company Endowment Europe Private Equity $ 65,607 8.5%61 XYZ Company Public Asia HFOF $ 173,286 12.1%62 XYZ Company Public N. AmericaHFOF $ 80,680 9.0%63 XYZ Company Foundation Europe Private Equity $ 75 4.7%64 XYZ Company Corporate Asia Real Estate $ 174,673 12.2%65 XYZ Company Foundation Asia HFOF $ 106,069 3.1%66 XYZ Company Corporate Asia PE FOF $ 147,350 3.5%67 XYZ Company Public N. AmericaAlternatives $ 170,086 16.5%68 XYZ Company Foundation Europe PE FOF $ 59,631 12.2%69 XYZ Company Endowment Asia Real Estate $ 81,193 24.3%70 XYZ Company Corporate Asia Private Equity $ 41,811 3.2%

% AUM in Product


PIVOT TABLE WITH BUILT IN CALCULATIONSYou have been keeping track of various client engagements throughout the last year, specifically revenue per project and hours spent on each project.You would like to summarize the following by Client: Total Revenue, % of Revenue, Total Hours, % of Total Hours and Revenue per Hour

Notes:1) Calculate % Total field using built-in function

for % of Revenue and % of Total hours2) Create a "calculated field" to automate calculation

of Rev per Hour for each client

Client Project Code Revenue HoursABC 10034 $ 11,651.0 2 DEF 18663 19,825.0 23 XYZ 15629 2,907.0 5 ABC 9033 15,722.0 22 DEF 9963 8,644.0 8 XYZ 3986 965.0 49 ABC 13068 5,134.0 30 DEF 7067 7,312.0 2 XYZ 10855 16,865.0 44 ABC 12268 12,962.0 8 DEF 19475 8,124.0 20 XYZ 144 12,678.0 22 ABC 6441 10,457.0 29 DEF 7105 521.0 49 XYZ 90 5,348.0 47 ABC 18592 7,901.0 41 DEF 19643 4,784.0 38 XYZ 10499 4,659.0 38 ABC 18927 16,157.0 40 DEF 19409 2,521.0 22 XYZ 276 3,399.0 26 ABC 12591 7,363.0 47 DEF 12853 19,565.0 10 XYZ 9018 14,717.0 17 ABC 9044 18,699.0 18

5403 $ 4,299.0 47


SUMIFSum up the entry column for each different Dept & Account

KEY Approach 1 Approach 2 Approach 3Dept Account Entry Combined Acct No. Dept Account Manual SUMIF SUM+IF

101 21008 810,934.65 101 21008 101 21406 264,766.71 101 21406 101 26072 113,175.60 101 26072 101 26088 580,883.87 101 26088 101 26139 253,057.11 101 26139 101 21008 97,976.89 101 21406 104,899.18 101 26072 30,869.15 101 26088 198,465.56 101 26139 72,114.37 101 21008 108,099.79 101 21406 39,030.03 101 26072 3,049.75 101 26088 1,968.65 101 26139 21,563.14 101 21008 9,585.66 101 21406 7,359.43 101 26072 28,038.71 101 26088 163.38 101 26139 58,116.72 101 21008 4,382.54 101 21406 405,467.32 101 26072 132,383.35 101 26088 56,587.80 101 26139 290,441.93 101 21008 126,528.55 101 21406 48,988.45 101 26072 52,449.59 101 26088 15,434.57 101 26139 99,232.78 101 21008 36,057.18 101 21406 54,049.90 101 26072 19,515.01 101 26088 1,524.87 101 26139 984.33 101 21008 10,781.57 101 21406 4,792.83 101 26072 3,679.72 101 26088 14,019.36 101 26139 81.69

4,181,501.69

A B C D E F G H I J K L123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051


SUBTOTAL and AUTOFILTER ILLUSTRATION

Multi-Family REIT Acquisitions1997-98 YTD

Company Name Ticker Property Name City State Region Occupancy Cap RateAmli Residential Properties AML Amli at Clairmont Atlanta GA SE 1/21/98 18,400 No 100 288 NA NAAmli Residential Properties AML Amli at Conner Farms Indianapolis IN MW 12/22/97 21,700 Yes 100 300 93 NAAmli Residential Properties AML Amli at Regents Crest Kansas City KS MW 12/22/97 25,600 Yes 25 368 93 NAAmli Residential Properties AML Amli at Town Center Kansas City KS MW 12/22/97 13,750 Yes 100 156 86 NAAmli Residential Properties AML Amli at Poplar Creek Schaumburg IL MW 12/18/97 12,500 No 100 196 91 NAAmli Residential Properties AML Amli at Bent Tree Dallas TX SW 10/17/97 19,000 No 100 300 94 NAAmli Residential Properties AML Amli at Bishop's Gate Plano TX SW 10/17/97 23,000 No 100 266 92 NAAmli Residential Properties AML Amli at Lantana Ridge Austin TX SW 9/30/97 23,838 No 100 354 87 NAAmli Residential Properties AML Amli at Verandah Arlington TX SW 3/25/97 25,400 No 35 538 94 NAAmli Residential Properties AML Amli at Danada Farms Wheaton IL MW 2/28/97 48,400 No 10 600 92 NAApartment Investment and Mgmt AIV Heather Ridge II Arlington TX SW 4/30/98 2,000 No 100 72 NA NAApartment Investment and Mgmt AIV Arbor Station Montgomery AL SE 4/15/98 11,400 No 100 264 NA NAApartment Investment and Mgmt AIV Casa Anita Phoenix AZ WE 3/30/98 8,587 Yes 100 224 NA NAApartment Investment and Mgmt AIV Cobble Creek Tucson AZ WE 3/30/98 11,539 Yes 100 301 NA NAApartment Investment and Mgmt AIV Rio Cancion Tucson AZ WE 3/30/98 14,529 Yes 100 379 NA NAApartment Investment and Mgmt AIV San Marina Phoenix AZ WE 3/30/98 15,295 Yes 100 399 NA NAApartment Investment and Mgmt AIV Sundown Village Tucson AZ WE 3/30/98 12,650 Yes 100 330 NA NAApartment Investment and Mgmt AIV Crossings at Bell Amarillo TX SW 1/1/98 3,250 No 100 160 NA NAApartment Investment and Mgmt AIV Steeplechase Tyler TX SW 1/1/98 9,750 No 100 484 NA NAApartment Investment and Mgmt AIV Fisherman's Landing Bradenton FL SE 12/1/97 8,500 No 100 200 NA NAApartment Investment and Mgmt AIV Foxchase Alexandria VA SE 12/1/97 107,700 No 100 2113 96 NAApartment Investment and Mgmt AIV Forest Place-100 Oak Park IL MW 11/15/97 23,122 No 72.05 234 NA NAApartment Investment and Mgmt AIV Point West Lenexa KS MW 11/15/97 6,527 No 61.88 NA NA NAApartment Investment and Mgmt AIV Arbors Tempe AZ WE 10/31/97 6,446 Yes 100 200 NA NAApartment Investment and Mgmt AIV Beacon Hill Chamblee GA SE 10/31/97 3,868 Yes 100 120 NA NAApartment Investment and Mgmt AIV Blossomtree Scottsdale AZ WE 10/31/97 4,029 Yes 100 125 NA NAApartment Investment and Mgmt AIV Brant Rock Houston TX SW 10/31/97 2,708 Yes 100 84 NA NAApartment Investment and Mgmt AIV Colonnade Gardens Phoenix AZ WE 10/31/97 6,318 Yes 100 196 NA NAApartment Investment and Mgmt AIV Foothills Tucson AZ WE 10/31/97 8,703 Yes 100 270 NA NAApartment Investment and Mgmt AIV Foxbay Tucson AZ WE 10/31/97 7,478 Yes 100 232 NA NAApartment Investment and Mgmt AIV Foxtree Tempe AZ WE 10/31/97 15,697 Yes 100 487 NA NAApartment Investment and Mgmt AIV Freedom Place Club Jacksonville FL SE 10/31/97 11,346 Yes 100 352 NA NAApartment Investment and Mgmt AIV Hazeltree Phoenix AZ WE 10/31/97 9,992 Yes 100 310 NA NAApartment Investment and Mgmt AIV Hiddentree East Lansing MI MW 10/31/97 8,413 Yes 100 261 NA NAApartment Investment and Mgmt AIV Hills Austin TX SW 10/31/97 10,604 Yes 100 329 NA NAApartment Investment and Mgmt AIV Islandtree Whitemarsh Island GA SE 10/31/97 6,962 Yes 100 216 NA NAApartment Investment and Mgmt AIV Olmos Club San Antonio TX SW 10/31/97 4,319 Yes 100 134 NA NAApartment Investment and Mgmt AIV Orchidtree Scottsdale AZ WE 10/31/97 8,961 Yes 100 278 NA NAApartment Investment and Mgmt AIV Pine Creek Clio MI MW 10/31/97 7,510 Yes 100 233 NA NAApartment Investment and Mgmt AIV Polo Park Midland TX SW 10/31/97 5,931 Yes 100 184 NA NAApartment Investment and Mgmt AIV Quailtree Phoenix AZ WE 10/31/97 5,931 Yes 100 184 NA NAApartment Investment and Mgmt AIV Rivercrest Tucson AZ WE 10/31/97 6,769 Yes 100 210 NA NA

Acquisition Date

Acquisition Price ($000)

Portfolio Acquisition?

Percent Owned

# of Units


AUTOMATED ROW SHADING

Count Name of Institution Type Region Product Type AUM ($MM)1 XYZ Company Foundation Europe Private Equity $ 158,865 3.5%2 XYZ Company Public Asia HFOF $ 138,042 12.3%3 XYZ Company Foundation Asia Real Estate $ 155,570 3.0%4 XYZ Company Foundation N. AmericaAlternatives $ 96,905 11.5%5 XYZ Company Corporate Asia PE FOF $ 148,483 6.7%6 XYZ Company Endowment Asia Hedge Fund $ 93,160 19.5%7 XYZ Company Endowment N. AmericaReal Estate $ 166,681 4.2%8 XYZ Company Foundation N. AmericaPE FOF $ 14,171 2.6%9 XYZ Company Corporate N. AmericaPE FOF $ 16,018 10.2%

10 XYZ Company Foundation N. AmericaReal Estate $ 151,393 13.3%11 XYZ Company Corporate Europe PE FOF $ 76,621 7.6%12 XYZ Company Foundation Europe Real Estate $ 138,571 23.9%13 XYZ Company Public Europe Alternatives $ 143,151 9.6%14 XYZ Company Corporate Europe Hedge Fund $ 132,701 12.5%15 XYZ Company Corporate N. AmericaReal Estate $ 102,919 17.3%16 XYZ Company Foundation N. AmericaAlternatives $ 8,307 6.4%17 XYZ Company Foundation Asia Real Estate $ 28,279 20.2%18 XYZ Company Endowment Europe PE FOF $ 166,449 19.4%19 XYZ Company Corporate N. AmericaPE FOF $ 138,669 1.7%20 XYZ Company Corporate N. AmericaHFOF $ 112,476 19.5%21 XYZ Company Foundation Europe Private Equity $ 64,438 21.7%22 XYZ Company Public Asia HFOF $ 85,761 7.2%23 XYZ Company Foundation Asia Private Equity $ 98,000 2.1%24 XYZ Company Public N. AmericaHedge Fund $ 96,798 0.4%25 XYZ Company Public Europe Alternatives $ 94,869 8.3%

% AUM in Product


TRANSPOSE, INDIRECTYou have a block of data and you would like to transpose the data, but maintaining references in case of updates to the data

Source DataDate WMT Retailer Index S&P 500

4/11/2005 100.0 100.0 100.0 4/12/2005 100.2 100.8 100.6 4/13/2005 100.1 99.4 99.4 4/14/2005 98.9 97.5 98.4 4/15/2005 98.3 95.2 96.7 4/18/2005 98.7 95.9 97.0 4/19/2005 98.1 95.5 97.6 4/20/2005 97.6 93.0 96.3 4/21/2005 98.5 95.3 98.2 4/22/2005 96.5 91.6 97.5 4/25/2005 96.9 93.4 98.4 4/26/2005 96.9 93.5 97.5 4/27/2005 97.5 93.2 97.9 4/28/2005 97.0 92.5 96.8 4/29/2005 97.2 92.1 97.9

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SEPARATING NAMES ILLUSTRATIONProblem: Separate a list of names between First Name and Last Name using Excel functionsNote: One could use Text to Columns but many times, that is not an option especially if youhave to work within the file

Example: Challenge:John Doe First and last names are different lengthsJonathan SmithJolly Jane

Solution:Use combination of the following Excel functions:FINDLENLEFTRIGHT

Step 1 Step 2 Step 3 Step 4 Step 5John DoeJonathan SmithJolly Jane


DROP BOX ALTERNATIVES

Question AnswerQuestion 1Question 2Question 3 SUMMARIZE YOUR RESULTSQuestion 4 A BQuestion 5 ExcellentQuestion 6 GreatQuestion 7 GoodQuestion 8 OKQuestion 9 Source List: PoorQuestion 10 Please Select Total # AnswersQuestion 11 ExcellentQuestion 12 Great In Column A, use sumif formulaQuestion 13 Good In Column B, use countif formulaQuestion 14 OKQuestion 15 PoorQuestion 16Question 17Question 18Question 19Question 20Question 21Question 22Question 23Question 24Question 25 c 1 wQuestion 26Question 27Question 28 Source List:Question 29 a 1 qQuestion 30 b 2 wQuestion 31 c 3 eQuestion 32 d 4 rQuestion 33 e 5 tQuestion 34 f 6 yQuestion 35 g 7 uQuestion 36 h 8 iQuestion 37Question 38Question 39Question 40Question 41Question 42Question 43Question 44Question 45Question 46Question 47Question 48Question 49Question 50

Documents

Advanced Excel Data Analysis Template