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Statistics Refreshers and Glossaries of Terms

Beware the procrastination monster.  Statistical analysis takes time.

The help sections of the statistics packages are often helpful resources for refreshers on a concept you may have forgotten.  In particular, the help sections of StatPlus:Mac LE and SPSS have useful information.  The best resource available to you for a statistics refresher is Paula Lackie (x 5607, or email plackie). Helpful links to all-things-stats-related can be found (organized by category) at http://statlink.tripod.com/.

Additionally, there are online learning programs and tutorials available.

Helpful online glossaries of terms:

Additionally, there are links to guidance on choosing the right analysis method available:

For help with qualitative analysis, you can check out this website:

Below is a beginning list of file extensions & what they're usually associated with. 

File Extension
Type of File
Associated Software
Important Details
.sav
data file
SPSS

.spo
data output file SPSS

.xpt
portable data file
SAS
.spv
output file
SPSS

.por
portable data file
SPSS
Good for interoperability
.dta
data file
Stata

.txt
ASCII text file
anything.. but..
.txt files can have the data arranged many ways (comma or tab delimited, flat, rectangular, hierarchical, no delmiiters ...) It also may not have metadata associated with it. The metadata will need to come from someplace else (typically a "data dictionary" or "Codebook".)
.sps
syntax/program/code file
SPSS
 Creating syntax files makes it easy to reproduce your work in a matter of moments (without a lot of clicking around).  You usually need a syntax file to access “raw” (just a file full of numbers, not in any format) data.
.sas
syntax/program/code file SAS
We don't have any publicly available SAS licenses.  If this code is all you can get your hands on with bare text data, get it! Paula will help you translate it into something you can use in other stats packages.
.dct or .do
syntax/program/code file Stata

.csv comma separated values most packages This is the native version for R, and it's easily opened in most data packages. It is likely to have column headers (variable names) but no labels or other useful metadata.
.tsv tab separated values most packages This is easily opened in most data packages. It is likely to have column headers (variable names) but no labels or other useful metadata.  This is a good format to use when you export your file if *any* of your fields could have commas in them. (Surveys, for instance.)
.xls Excel® versions before 2007 Excel and many/most others This format is easily accessible to most stats packages. Like .tsv or .csv, there is likely to be column headers but no labels or other useful metadata.   Also, if any fields have special identifying characteristics, it's inconsistent how they will be translated into other programs. (eg: date, time and currency)