Can Excel do most things a Stats program can?

Can Excel do most things a stats program can do? E.g. SPSS, SAS?

Sum of squares easy to use?

Can a reasonably small number of covariates be used without problems?

Where can I find tutorials on such areas?

I saw a discussion on a stats group about what someone wanted to do,
and would like to play around with that in a different field.

TIA,

Nev.

LINEST will do multiple linear regression, but Excel versions prior to
2003 can have numerical difficulties. Stats packages will include a
number of diagnostic tests for linear models that are not native to Excel.

Fitting a polynomial trendline on an "XY (Scatter)" chart is incredibly
good (numerically) in all versions of Excel. It is more accurate than
SAS, S-PLUS, R, Minitab, etc. (sorry, I don't use SPSS). If all you
need are the coefficients, and not the diagnostics, ...

You can do ANOVA with LINEST, but only if you know enough about the
underlying linear algebra to force it.

Beyond Linear Models, Excel has very little capability that you would
find in stats packages.

Excel's probability functions are probably adequate for simple
hypothesis testing, but neither as accurate nor as robust (working over
a broad range of input parameters) as what is provided in stats
programs. Excel 2003 is a big improvement, but didn't go far enough.
Ian Smith's VBA library of probability functions
http://members.aol.com/iandjmsmith/examples.xls
is actually better than what is provided in any stats package.

Excel is a reasonable choice to distribute specific calculations (that
are within its capabilities) to a number of users that have Excel, but
do not have (or do not know how to use) stats packages.

If you want to do a variety of analyses and have access to a stats
package, that would be a better choice. If you don't have access to a
stats package, and the cost is prohibitive, consider R,
http://www.r-project.org
which is a free-ware implementation of the S language.

Jerry

Nev. wrote:

Can Excel do most things a stats program can do? E.g. SPSS, SAS?

Sum of squares easy to use?

Can a reasonably small number of covariates be used without problems?

Where can I find tutorials on such areas?

I saw a discussion on a stats group about what someone wanted to do,
and would like to play around with that in a different field.

TIA,

Nev.

Excel is a very friendly and convenient platform for displaying data
tables and performing simple summary statistics and graphs. Second
moment statistics like VAR, STDEV, etc. do not have a numerically good
implementation in Excel versions prior to 2003, but you can substitute
DEVSQ(data)/(COUNT(data)-1) for VAR(data), ... to get around this.
Moreover, the numerical problems with older versions will rarely be an
issue in univariate calculations unless you have a very large data set,
or a very small coefficient of variation (called relative standard
deviation in some circles).

LINEST will do multiple linear regression, polynomial fits, etc., but
Excel versions prior to 2003 can have numerical difficulties. Stats
packages will include a number of diagnostic tests for linear (in the
unknowns) models that are not native to Excel.

Fitting a polynomial trendline on an "XY (Scatter)" chart is incredibly
good (numerically) in all versions of Excel. It is more accurate than
SAS, S-PLUS, R, Minitab, etc. (sorry, I don't use SPSS). If all you
need are the coefficients, and not the diagnostics, Excel is great for
this purpose.

You can do ANOVA with LINEST, but only if you know enough about the
underlying linear algebra to force it.

Beyond Linear Models, Excel has very little capability that you would
find in stats packages.

Excel's probability functions are probably adequate for simple
hypothesis testing, but neither as accurate nor as robust (working over
a broad range of input parameters) as what is provided in stats
programs. Excel 2003 is a big improvement, but didn't go far enough.
Ian Smith's VBA library of probability functions
http://members.aol.com/iandjmsmith/examples.xls
is actually better than what is provided in any stats package I know of.

Overall, Excel is a reasonable choice to distribute specific statistical
calculations (that are within its capabilities) to a number of users
that have Excel, but do not have (or do not know how to use) stats packages.

If you want to do a variety of analyses and have access to a stats
package, that would be a better choice. If you don't have access to a
stats package, and the cost is prohibitive, consider R,
http://www.r-project.org
which is a free-ware implementation of the S language.

Jerry

Nev. wrote:

Can Excel do most things a stats program can do? E.g. SPSS, SAS?

Sum of squares easy to use?

Can a reasonably small number of covariates be used without problems?

Where can I find tutorials on such areas?

I saw a discussion on a stats group about what someone wanted to do,
and would like to play around with that in a different field.

TIA,

Nev.

can excel plot a graph with the actual data and the data
plus and minus the standard deviation.
thanks
-----Original Message-----
Excel is a very friendly and convenient platform for
displaying data
tables and performing simple summary statistics and
graphs. Second
moment statistics like VAR, STDEV, etc. do not have a
numerically good
implementation in Excel versions prior to 2003, but you
can substitute
DEVSQ(data)/(COUNT(data)-1) for VAR(data), ... to get
around this.
Moreover, the numerical problems with older versions will
rarely be an
issue in univariate calculations unless you have a very
large data set,
or a very small coefficient of variation (called relative
standard
deviation in some circles).

LINEST will do multiple linear regression, polynomial
fits, etc., but
Excel versions prior to 2003 can have numerical
difficulties. Stats
packages will include a number of diagnostic tests for
linear (in the
unknowns) models that are not native to Excel.

Fitting a polynomial trendline on an "XY (Scatter)" chart
is incredibly
good (numerically) in all versions of Excel. It is more
accurate than
SAS, S-PLUS, R, Minitab, etc. (sorry, I don't use SPSS).
If all you
need are the coefficients, and not the diagnostics, Excel
is great for
this purpose.

You can do ANOVA with LINEST, but only if you know enough
about the
underlying linear algebra to force it.

Beyond Linear Models, Excel has very little capability
that you would
find in stats packages.

Excel's probability functions are probably adequate for
simple
hypothesis testing, but neither as accurate nor as robust
(working over
a broad range of input parameters) as what is provided in
stats
programs. Excel 2003 is a big improvement, but didn't go
far enough.
Ian Smith's VBA library of probability functions
http://members.aol.com/iandjmsmith/examples.xls
is actually better than what is provided in any stats
package I know of.

Overall, Excel is a reasonable choice to distribute
specific statistical
calculations (that are within its capabilities) to a
number of users
that have Excel, but do not have (or do not know how to
use) stats packages.

If you want to do a variety of analyses and have access
to a stats
package, that would be a better choice. If you don't
have access to a
stats package, and the cost is prohibitive, consider R,
http://www.r-project.org
which is a free-ware implementation of the S language.

Jerry

Nev. wrote:

Can Excel do most things a stats program can do? E.g.
SPSS, SAS?

Sum of squares easy to use?

Can a reasonably small number of covariates be used
without problems?

Where can I find tutorials on such areas?

I saw a discussion on a stats group about what someone
wanted to do,
and would like to play around with that in a different
field.

TIA,

Nev.

.

Giulio -

If your points represent the average of several readings, and each point
has an associated pair of SDs, use this approach. Put X and Y into two
adjacent columns (X to the left) and put the SD(x) and SD(y) into two
more columns. Make a scatter chart with the X and Y data. Double click
on the series, select X error bars, click in the Custom Plus box and
select the range with the X standard deviation, then click in the Custom
Minus and select the same range. Repeat this for the Y error bars and
the Y standard deviation range.

If you have something like a run chart of individual measurements, you
can add error bars that depict ± N standard deviations from the mean
(you pick N), with the error bars all the same for all points, from mean
- N SD to mean + N SD. Or you could add error bars that show the
standard error in the data; with each point having the same length error
bars, centered on the point's value.

- Jon
-------
Jon Peltier, Microsoft Excel MVP
Peltier Technical Services
http://PeltierTech.com/Excel/Charts/
_______

giulio defeudis wrote:

can excel plot a graph with the actual data and the data
plus and minus the standard deviation.
thanks

-----Original Message-----
Excel is a very friendly and convenient platform for

displaying data

tables and performing simple summary statistics and

graphs. Second

moment statistics like VAR, STDEV, etc. do not have a

numerically good

implementation in Excel versions prior to 2003, but you

can substitute

DEVSQ(data)/(COUNT(data)-1) for VAR(data), ... to get

around this.

Moreover, the numerical problems with older versions will

rarely be an

issue in univariate calculations unless you have a very

large data set,

or a very small coefficient of variation (called relative

standard

deviation in some circles).

LINEST will do multiple linear regression, polynomial

fits, etc., but

Excel versions prior to 2003 can have numerical

difficulties. Stats

packages will include a number of diagnostic tests for

linear (in the

unknowns) models that are not native to Excel.

Fitting a polynomial trendline on an "XY (Scatter)" chart

is incredibly

good (numerically) in all versions of Excel. It is more

accurate than

SAS, S-PLUS, R, Minitab, etc. (sorry, I don't use SPSS).

If all you

need are the coefficients, and not the diagnostics, Excel

is great for

this purpose.

You can do ANOVA with LINEST, but only if you know enough

about the

underlying linear algebra to force it.

Beyond Linear Models, Excel has very little capability

that you would

find in stats packages.

Excel's probability functions are probably adequate for

simple

hypothesis testing, but neither as accurate nor as robust

(working over

a broad range of input parameters) as what is provided in

stats

programs. Excel 2003 is a big improvement, but didn't go

far enough.

Ian Smith's VBA library of probability functions
http://members.aol.com/iandjmsmith/examples.xls
is actually better than what is provided in any stats

package I know of.

Overall, Excel is a reasonable choice to distribute

specific statistical

calculations (that are within its capabilities) to a

number of users

that have Excel, but do not have (or do not know how to

use) stats packages.

If you want to do a variety of analyses and have access

to a stats

package, that would be a better choice. If you don't

have access to a

stats package, and the cost is prohibitive, consider R,
http://www.r-project.org
which is a free-ware implementation of the S language.

Jerry

Nev. wrote:


Can Excel do most things a stats program can do? E.g.

SPSS, SAS?

Sum of squares easy to use?

Can a reasonably small number of covariates be used

without problems?

Where can I find tutorials on such areas?

I saw a discussion on a stats group about what someone

wanted to do,

and would like to play around with that in a different

field.

TIA,

Nev.

.