You may install the software on up to two (2) computers. License is good for 6 months. Runs on Windows and Mac windows 7(service pack 2 or higher) 8, 10 and mac 10.10, 10,11, 10.12 or higher For a comparison of all IBM SPSS versions,. No need to worry about purchasing the right version. Exchanges are allowed!

Includes the following:. IBM SPSS Base 25. IBM SPSS Advanced Statistics. IBM SPSS Regression. No limitation on the number of variables or cases. Be sure you have all the add-ons needed for your course or dissertation! The Base version does not include any add-ons and you may not purchase them separately or at a later time.

Consider the Grad Pack Premium. New in Version 25. Analyze your data with new and advanced statistics.

The Advanced Statistics module offers a variety of new features within GENLINMIXED and GLM/UNIANOVA methods. Supports Bayesian inference, which is a method of statistical inference. Integrate better with third-party applications.

Crosstabulations - Counts, percentages, residuals, marginals, tests of independence, test of linear association, measure of linear association, ordinal data measures, nominal by interval measures, measure of agreement, relative risk estimates for case control and cohort studies. Frequencies - Counts, percentages, valid and cumulative percentages; central tendency, dispersion, distribution and percentile values. Descriptives - Central tendency, dispersion, distribution and Z scores. Descriptive ratio statistics - Coefficient of dispersion, coefficient of variation, price-related differential and average absolute deviance.

Compare means - Choose whether to use harmonic or geometric means; test linearity; compare via independent sample statistics, paired sample statistics or one-sample t test. ANOVA and ANCOVA - Conduct contrast, range and post hoc tests; analyze fixed-effects and random-effects measures; group descriptive statistics; choose your model based on four types of the sum-of-squares procedure; perform lack-of-fit tests; choose balanced or unbalanced design; and analyze covariance with up to 10 methods. Correlation - Test for bivariate or partial correlation, or for distances indicating similarity or dissimilarity between measures. Nonparametric tests - Chi-square, Binomial, Runs, one-sample, two independent samples, k-independent samples, two related samples, k-related samples. Explore - Confidence intervals for means; M-estimators; identification of outliers; plotting of findings.

Tests to Predict Numerical Outcomes and Identify Groups: IBM SPSS Statistics Base contains procedures for the projects you are working on now and any new ones to come. You can be confident that you’ll always have the analytic tools you need to get the job done quickly and effectively. Factor Analysis - Used to identify the underlying variables, or factors, that explain the pattern of correlations within a set of observed variables. In IBM SPSS Statistics Base, the factor analysis procedure provides a high degree of flexibility, offering:.

Seven methods of factor extraction. Five methods of rotation, including direct oblimin and promax for nonorthogonal rotations. Three methods of computing factor scores. Also, scores can be saved as variables for further analysis. K-means Cluster Analysis - Used to identify relatively homogeneous groups of cases based on selected characteristics, using an algorithm that can handle large numbers of cases but which requires you to specify the number of clusters.

Select one of two methods for classifying cases, either updating cluster centers iteratively or classifying only. Hierarchical Cluster Analysis - Used to identify relatively homogeneous groups of cases (or variables) based on selected characteristics, using an algorithm that starts with each case in a separate cluster and combines clusters until only one is left.

Analyze raw variables or choose from a variety of standardizing transformations. Distance or similarity measures are generated by the Proximities procedure.

Statistics are displayed at each stage to help you select the best solution. TwoStep Cluster Analysis - Group observations into clusters based on nearness criterion, with either categorical or continuous level data; specify the number of clusters or let the number be chosen automatically. Discriminant - Offers a choice of variable selection methods, statistics at each step and in a final summary; output is displayed at each step and/or in final form. Linear Regression - Choose from six methods: backwards elimination, forced entry, forced removal, forward entry, forward stepwise selection and R2 change/test of significance; produces numerous descriptive and equation statistics. Ordinal regression—PLUM - Choose from seven options to control the iterative algorithm used for estimation, to specify numerical tolerance for checking singularity, and to customize output; five link functions can be used to specify the model. Nearest Neighbor analysis - Use for prediction (with a specified outcome) or for classification (with no outcome specified); specify the distance metric used to measure the similarity of cases; and control whether missing values or categorical variables are treated as valid values.

IBM Advanced Statistics - More Accurately Analyze Complex Relationships Using Powerful Univariate and Multivariate Analysis Procedures Included: General linear models (GLM) – Provides you with more flexibility to describe the relationship between a dependent variable and a set of independent variables. The GLM gives you flexible design and contrast options to estimate means and variances and to test and predict means.

You can also mix and match categorical and continuous predictors to build models. Because GLM doesn't limit you to one data type, you have options that provide you with a wealth of model-building possibilities.

Linear mixed models, also known as hierarchical linear models (HLM). Fixed effect analysis of variance (ANOVA), analysis of covariance (ANOVA), multivariate analysis of variance (MANOVA) and multivariate analysis of covariance (MANCOVA). Random or mixed ANOVA and ANCOVA. Repeated measures ANOVA and MANOVA. Variance component estimation (VARCOMP) The linear mixed models procedure expands the general linear models used in the GLM procedure so that you can analyze data that exhibit correlation and non-constant variability. If you work with data that display correlation and non-constant variability, such as data that represent students nested within classrooms or consumers nested within families, use the linear mixed models procedure to model means, variances and covariances in your data. Its flexibility means you can formulate dozens of models, including split-plot design, multi-level models with fixed-effects covariance, and randomized complete blocks design.

You can also select from 11 non-spatial covariance types, including first-order ante-dependence, heterogeneous, and first-order autoregressive. You'll reach more accurate predictive models because it takes the hierarchical structure of your data into account. You can also use linear mixed models if you're working with repeated measures data, including situations in which there are different numbers of repeated measurements, different intervals for different cases, or both. Unlike standard methods, linear mixed models use all your data and give you a more accurate analysis. Generalized linear models (GENLIN): GENLIN covers not only widely used statistical models, such as linear regression for normally distributed responses, logistic models for binary data, and loglinear model for count data, but also many useful statistical models via its very general model formulation.

The independence assumption, however, prohibits generalized linear models from being applied to correlated data. Generalized estimating equations (GEE): GEE extend generalized linear models to accommodate correlated longitudinal data and clustered data.

General models of multiway contingency tables (LOGLINEAR) Hierarchical loglinear models for multiway contingency tables (HILOLINEAR) Loglinear and logit models to count data by means of a generalized linear models approach (GENLOG) Survival analysis procedures:. Cox regression with time-dependent covariates. Kaplan-Meier. Life Tables IBM SPSS Regression Overview, Features and Benefits IBM® SPSS® Regression enables you to predict categorical outcomes and apply a wide range of nonlinear regression procedures.

You can apply IBM SPSS Regression to many business and analysis projects where ordinary regression techniques are limiting or inappropriate: for example, studying consumer buying habits or responses to treatments, measuring academic achievement, and analyzing credit risks.

Filed Under Went to the “See it in SPSS” event at the Westin Bonaventure this week and, as always, it was well done. The two most interesting parts, based on a non-random sample of one, i.e., me, were:.

What’s new in SPSS (besides the fact that it is now called PASW and owned by IBM)?. And the PAWS Modeler. The new PASW 18 runs on Snow Leopard on the Mac (big plus for Mac people). Doesn’t run on the earlier Mac OS’s (big minus for Mac people).

There is a new boot-strapping option for some statistics, which is cool, but costs extra, (by which I mean a lot extra, according to the SPSS website) One interesting addition was better integration with R. This will get me thrown out of the “in-crowd” with statisticians, I know, but I have never had much need for R.

I have everything I can handle with SPSS, SAS and the occasional Stata, less occasional JMP and rarer S-plus. However, if you are not me (which I am fairly certain is the case) maybe you are interested in it, so there you R. There is a Direct Marketing module, which is also cool and has applications far broader than marketing, but also costs extra. According to the SPSS website they had this in 17 but I have never seen it before.

When I saw the multiple imputation option I thought that was part of PASW-18 but when I installed the faculty pack, there it was, as part of the Missing Values module. Speaking of the Faculty Pack – that is not new but it’s an awesome deal ($250 for a one year license for 12 modules – 13, if you have Windows). It’s an awesome deal compared to buying each module and if you teach using SPSS you should definitely get it. I am going to spend some of my weekend and the next two weeks when I am laid up in the hospital playing with it. Predictive Modeler I kept thinking looked a whole lot like Clementine and could not quite figure out the difference.

Then I read that PASW modeler was formerly Clementine. It has all of the pluses and minuses of data mining software in general. One question I asked the presenter which intrigued me was how long it took to install. He said an hour and a half.

I have NEVER been able to install SAS Enterprise Miner on any computer. Part of this is no doubt me.

I have an extremely long list of projects that really need to get done, like updating our statistical consulting website at the university, writing new courses, re-writing a program that creates static web pages to be dynamic, possibly using SAS IntrNet (which requires learning more about it), doing programming for consulting clients, re-designing client websites to have RSS feeds from their employee blogs, etc. It may only take 8 hours to install Enterprise Miner but I can’t see when in the foreseeable future I will ever have eight hours to spend installing something I really have no current need to use and am just interested in. This is an interesting barrier for technology products, I think. There are things like R and the open source qualitative analysis program that all of us at lunch remembered trying and no one could remember the name. These are free.

I know I won’t have time to learn either of those in the foreseeable future unless someone invents a machine to give you 48-hour days. (THAT I would buy!

A-95 Spss Pasw Statistics Grad Pack 17 For Mac Free Download

) There is S-plus which looks interesting and I can pretty much bet I will never have time to learn. I have had the new SPSS modules for a few months and am finally getting time to look at those. Get magic media marker (2.6.7 full version for mac. I have been meaning to learn JMP for a year and have opened it and spent an hour or so looking at it, as well as attending an event sponsored by the JMP folks. I could go on here is my point all of this stuff is free to me because the university pays for the licenses, or it is open source. If you can’t get people to use your stuff even if it is free well, that is a pretty tough market to penetrate. What’s the secret? If I ran the world, I would start more of these events with “Here is how you get it installed and working on your computer, connected to your server, etc.” Don’t get me wrong, I LOVED the stuff on Bayesian statistics that Bob Rodriguez talked about at WUSS and I really liked the person from SPSS whose name I so ungratefully forgot, who discussed using equal N’s in groups (e.g., died/ not died) in creating an equation, for the training set, but proportional groups in the validation set because it is one of those simple, brain-dead obvious things that is too often forgotten (including by me).

There needs to be a balance. I am busy and so is everyone else I know, except for my 18 month old granddaughter and my 76-year-old mother, and neither of them needs statistical software. Unfortunately, we don’t have a license for PASW Modeler, so I am not sure how to test the claim it can be set up in 90 minutes, including installation of PASW Statistics. I have to say that I am intrigued. My point is, even if your software is amazingly amazing, if it takes days to get it configured, no matter how great you are, people just won’t bother. It reminds me of years ago when a relatively young woman offered to work for a company where I was a partner. She presented herself to the only male partner and told him that she would be “willing” to work for us and named what I considered an astronomical sum, since it was more than any of the three partners made.

A-95 Spss Pasw Statistics Gradpack 17 For Mac 2017

(Whatever book she had been reading about job-hunting, I hope she got a refund.) I asked my partner, “You interviewed her. What did you think? Was she worth that kind of money.” He said, “Let me put it like this. I wouldn’t pay her that if she #$@%ed me with my morning coffee.” My point, and I do have one, is that no matter how awesome you might be, you can price yourself out of the market, whether it be in salary or just the pain in the ass of getting the thing to work. From what I saw of PASW 18 this week, the pain in the ass cost is really low.