Item: IBM SPSS Statistics
Rating: 9
Author: Verified User

Use Cases and Deployment Scope

I use SPSS to analyze survey data for my org. My analyses range from simple descriptive statistics to correlations and complex models. I'm able to compare means, run regression models and create graphs to understand relationships between variables.

Pros and Cons

No code, user friendly statistical analyses
Wide range of statistical methods offered
Intuitive graphs and tables

Offer HLM and latent growth curve modelling
Exportable, neatly formatted correlation matrices

Return on Investment

Analyzed survey data from 4,000 participants, computing means and correlations
Created regression models to determine predictors of monthly active usage of app

Operational Impact

Using SPSS has cut down on the amount of time spent writing queries, saving me several hours each month. Reporting efficiency and accuracy across my team has increased exponentially, as the no code SPSS interface leaves less room for error.

Business Impact

SPSS has definitely improved decision-making ability across my org. Increased efficiency and accuracy means that stakeholders have greater confidence in key performance indicators and are more confident and empowered to make business decisions.

Alternatives Considered

Python IDLE, Stata and MplusKASSA

Compared to Stata, python and MPlus, SPSS is more user friendly especially for beginners. It displays data and output in easily readable formats and makes statistics fun and easy. However, Stata, python and MPlus are more ideal for complex statistical methods like structural equation modeling, hierarchical linear models and writing algorithms.

Key Insights

Do you think IBM SPSS Statistics delivers good value for the price?

Yes

Are you happy with IBM SPSS Statistics's feature set?

Yes

Did IBM SPSS Statistics live up to sales and marketing promises?

Yes

Did implementation of IBM SPSS Statistics go as expected?

Yes

Would you buy IBM SPSS Statistics again?

Yes

Other Software Used

Snowflake, Microsoft Excel, Tableau Desktop

Likelihood to Recommend

SPSS is perfect for running quick analyses like correlations, t-test, chi square, regressions and ANOVA. You can also test mediation and moderation models if you have enough skill. But if you want to do really complex modelling like HLM or latent growth curve modeling you might have to turn to stata, SAS, MPlus etc. I much prefer the SPSS interface so would love if these became options in the future.

Usability

The point and click menu style interface makes it very easy to find the analyses you need. If anything is unclear a simple search of the help menu or a google search give immediate clarity. Analyses usually return output immediately and if there is an error, the error message explicitly spells out the problem so it is easy to fix.

Usability Pros and Cons

Pros	Cons
Like to use Relatively simple Easy to use Technical support not required Well integrated Consistent Quick to learn Convenient Feel confident using Familiar	None

User friendly analytics

Modules Used

Overall Satisfaction with IBM SPSS Statistics