P. T. NG 33

StatTools®, UNISTAT®, and XLSTAT©. With the ex-

ception of PopTools, which is written specifically to

analyze ecological models, these add-ins are commercial

products that have an annual single user license fee that

ranges from $40.00 for statistiXL© to $300.00 for UNI-

STAT®. In light of the ever rising textbook prices and

costs of attending colleges/universities, it will be valu-

able to the students, instructors and researchers to have

the freedom of using an Excel add-in that utilizes the

familiar interface of Excel, and offers a reliable and an

extended range of statistical procedures without having

to be burdened with the licensing cost.

XLR intends to serve this purpose by being a free

software version of an Excel add-in that includes a fuller

range of statistical procedures that are commonly cov-

ered in a typical Introductory Business Statistics course

and free the users from the constraints that come with

proprietary software. It attempts to achieve this by har-

nessing the power of th e popular free sof twar e R [14 ] -- a

language and environment for statistical computing and

graphics.

2. Design Approach and Philosophy

Reference [15] provides a utility, R-Excel interface, to

connect Excel to R. The R-Excel interface uses DCOM

to embed R into Excel. Component object model (COM)

is a technology used on Microsoft Windows platforms

for server applications (e.g., R) to expo se functionality o f

a component (set of objects, e.g., R functions) to client

applications (e.g., Excel). DCOM is the distributed ver-

sion of COM that makes COM objects (e.g., a set of R

functions) transparently available across a network of

computers.

Specifically, R-Excel provides three interface modes:

(1) scratchpad and data transfer mode, (2) macro mode,

and (3) spreadsheet mode. The first scatchpad and data

transfer mode is designed for power users who have a

reasonable amount of knowledge in R. We did not adopt

this interface mode in XLR. We want to shield the users

from all the details of R computations and coding so that

the users think that they are working in Excel not R. The

macro mode allows us to put any statistical procedures

written in R on an Excel menu or button via VBA for

Excel. This is the pre-dominant interface design in XLR.

The spreadsheet mode, which retains the automatic re-

calculation feature in Excel, is adop ted to rewrite a list of

commonly used Excel functions by making functional

calls to the corresponding R functions and, hence, enable

us to solve the notorious problems of incorrect handling

of delicate numerical problems in Excel as reported in

[5,7-10].

R has an extensive collection of statistical (linear and

nonlinear modeling, classical statistical tests, time-series

analysis, classification, clustering, etc.) and graphical

(box and whisker plots, pie charts, pairs plot, coplot, 3D

plot, forest plot, etc.) procedures and is highly extensible

through the add-on packages, which number more than

4,000 to date. This makes it perfectly suitable to act as

the computational engine for Excel in the COM para-

digm so that we do not have to be concerned about rein-

venting the wheels of statistical computing procedures.

In our XLR implementation, Excel (client application)

utilizes R (server application) as a computational com-

ponent object. The users are not expected to know any

programming in R. Our goal is that they should not even

be aware that R is involved at all. The distributed version

of COM will be explored in a future proj ect.

Whenever possible, we adhere to the feel and look of

the input dialogue box and output format of the various

tools in Excel’s Analysis ToolPak. This will help make

users feel more at home in their familiar Excel comput-

ing environment. Figure 1 and Figure 2 show the dia-

logue box and output for the Simple Linear Regression in

XLR. Users can see that they look very much like the

dialogue box and output of the Regression tool in EX-

CEL’s Analysis ToolPak.

Figure 1. Dialogue box for the Simple Linear Regression

command in XLR.

Copyright © 2013 SciRes. OJAppS