SPSS and ecology??

Question

SO i have gathered data for my ecology class. We have to anaylyze it using SPSS . We sampled on two different days and Our data consists of the species of invertebrates and fish found as well as their abundancies. We also have data on the water temp, ph, nitrate and phosphate contents in the water on the two different days. What kinds of tests can we run on SPSS? Our professor is teching for the first time and we have been left to feel this out on our own. I do know we can run a chi^2 test to determine the species abundance. Any help would be greatly appreciated.

Answer 1

SPSS (originally, Statistical Package for the Social Sciences) was released in its first version in 1968, and is among the most widely used programs for statistical analysis in social science. It is used by market researchers, health researchers, survey companies, government, education researchers, and others. In addition to statistical analysis, data management (case selection, file reshaping, creating derived data) and data documentation (a metadata dictionary is stored with the data) are features of the base software.

The many features of SPSS are accessible via pull-down menus (see image) or can be programmed with a proprietary 4GL command syntax language. Command syntax programming has the benefits of reproducibility and handling complex data manipulations and analyses. The pull-down menu interface also generates command syntax, though, by default, this is invisible to the user. Programs can be run interactively, or unattended using the supplied Production Job Facility. Additionally a "macro" language can be used to write command language subroutines and a Python programmability extension can access the information in the data dictionary and data and dynamically build command syntax programs. The Python programmability extension, introduced in SPSS 14, replaced the less functional SAX Basic "scripts" for most purposes, although SaxBasic remains available. From version 14 onwards SPSS can be driven externally by a Python or a VB.NET program using supplied "plug-ins".

SPSS places constraints on internal file structure, data types, data processing and matching files, which together considerably simplify programming. SPSS datasets have a 2-dimensional table structure where the rows typically represent cases (such as individuals or households) and the columns represent measurements (such as age, s*x or household income). Only 2 data types are defined, numeric and text (or "string"). All data processing occurs sequentially case-by-case through the file. Files can be matched one-to-one and one-to-many, but not many-to-many.

Different versions of SPSS are available for Windows, Mac OS X and Unix. The Windows version is updated more frequently, and has more features, than the versions for other operating systems. However, due to problems with the SPSS anti-p****y licensing features, SPSS 15.0 and prior versions are not compatible for Windows Vista. SPSS Inc. has announced that the 2007 release 15.1 of SPSS will run natively on Mac Intel x86 processors.

SPSS can read and write data from ASCII text files (including hierarchical files), other statistics packages, spreadsheets and databases. SPSS can read and write to external relational database tables via ODBC and SQL.

Statistical output is to a proprietary file format (*.spo file, supporting pivot tables) for which, in addition to the in-package viewer, a stand-alone reader is provided. Alternatively output can be made text-only (draft viewer) or captured as data (using the OMS command) as text, tab-delimited text, HTML, XML, SPSS dataset or a variety of graphic image formats (JPEG, PNG, BMP and EMF).

Statistics included in the base software:

Descriptive statistics: Cross tabulation, Frequencies, Descriptives, Explore, Descriptive Ratio Statistics

Bivariate statistics: Means, t-test, ANOVA, Correlation (bivariate, partial, distances), Nonparametric tests

Prediction for numerical outcomes: Linear regression

Prediction for identifying groups: Factor analysis, cluster analysis (two-step, K-means, hierarchical), Discriminant

Add-on modules provide additional capabilities. The available modules are:

SPSS Programmability Extension (added in version 14). Allows Python programming control of SPSS.

SPSS Data Validation (added in version 14). Allows programming of logical checks and reporting of suspicious values.

SPSS Regression Models - Logistic regression, ordinal regression, multinomial logistic regression, and mixed models (multilevel models).

SPSS Advanced Models - Multivariate GLM and repeated measures ANOVA (removed from base system in version 14).

SPSS Classification Trees. Creates classification and decision trees for identifying groups and predicting behaviour.

SPSS Tables. Allows user-defined control of output for reports.

SPSS Exact Tests. Allows statistical testing on small samples.

SPSS Categories

SPSS Trends™

SPSS Conjoint

SPSS Missing Value Analysis. Simple regression-based imputation.

SPSS Map

SPSS Complex Samples (added in Version 12). Adjusts for stratification and clustering and other sample selection biases.

SPSS Server is a version of SPSS with a client/server architecture. It has some features not available in the desktop version, one example is scoring functions.

Hope this helps...

Answer 2

We have to use that in my course at uni, BVetMed. Its a load of b*llucks. You can input data into a excel-style spread sheet. Then go to one of the menus, and there is a thing to work out means, and do ANOVA tests, and two-way and one-way tests, students-t test etc, but they are named funny things. I think try going to 'Tests' or 'Descriptives' as the menu.

Sorry, that was actually very little help at all was it, I'll submit it anyway,

PS do you know how to input data - put the column headings on one sheet, and the actual data on the other

Answer 3

i've used spss for social science, but stats are stats.

first, you should run and report your means, ranges and standard deviations for each DV, also your sample size ("descriptive statistics")

generally, you could do independent t-tests using your "day of collection" as the grouping variable. everything else is your DV. several t-tests. if you want, you could also run correlations between various DVs to see if there are any relationships between them, if they covary, that is.

you could run a one-way ANOVA instead of all the t-tests, that might be more fun, plus you could look for any interactions and main effects. i'm going to assume you can do this (it's been awhile, but i think it's under "general linear model"?) -- SPSS is pretty easy to get around in, or use the help feature, i can't remember how everything is called.

and the chi-square, as you said. was there a relationship btwn abundance and a given day...i could offer more suggestions if i saw what kind of data but i think that's pretty much it. i don't know how savvy you are as far as running regression models and stuff but you could always look into those as well.