SPSS vs Stata: All You Need to Know

spss-vs-stata

The difference between SPSS vs STATA is always a major concern for statistics students. SPSS and STATA both are the best statistics tools. But as a statistics student, you should know the actual difference between SPSS vs STATA.

Today, I am going to share with you the best and most effective difference between SPSS vs STATA. After having a look at this comparison, you will be more confident to compare this software.

What is SPSS?

SPSS stands for Statistical Package for Social Sciences. It was developed in the year 1968 at a university. After a few years, SPSS Inc. comes into existence the organization was completely based on the SPSS. Later on, SPSS was acquired by IBM in the year 2009. Nowadays SPSS is known as IBM SPSS.

It is a statistics software package that is used for interactive statistical analysis, it does the analysis in the form of batches. SPSS is licensed software, but you can use it as a trial version of SPSS with the help of SaaS (Software as a Service). We can run the SPSS programs on different operating systems such as Windows, Mac OS, UNIX and Linux.

IBM SPSS software is a leading statistics software in the world. It helps in finding the insights of the customer or end users’ data. (based on the organization’s operations). SPSS is quite an outstanding tool that contains a comprehensive set of statistical tools. It offers easier statistical analysis, and also you to do open source integration.

What is Stata?

Stata is a general-purpose statistics software package. It is widely used for statistical analysis. It was developed in the year 1985 by Stata Corp.  Stata is a proprietary licensed product. Besides, it also supports different operating systems such as Windows, Mac OS, and Linux. Stata is the best data analysis and statistical software.

It offers the best solution for data science needs. So if you need any help related to a data science assignment then you can contact us on the behalf of that. It is quite easy to retrieve and manipulate the data in Stata. Apart from that it also offers to visualize data models and generate useful reports. It is one of the most effective statistics software package tools for data management, data analysis, and graphics. On the other hand, if you have any pending data analysis assignments then you can talk to our expert on the behalf of it.

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Difference between SPPS vs Stata in tabular form

Terms for comparisonSPSSStata
Data VisualizationIt is used for complicated information management, such as the usual excel spreadsheet.It is beneficial in cutting-edge analysis, which is ideal for researchers or developers.
FunctionsIt can perform Bayesian Statistics functions, including t-tests, regression, and ANOVA.It has combined logit standards that give advanced option modelling.
Applications It is utilized in the social sciences and medical sectors.It is frequently utilized in econometrics.
Statistical AnalysisIt is more powerful in this section.It is comparatively weak in this section.
ChartsIt is used to create modern charts, and publications charts easily.It can be used for finite mixture models, which can customize with different estimators and combinations.
ProgrammingIt provides syntax editors, trims trailing, or leading spaces with shortcut tools.It has spatial autoregressive models that utilize observational units. 
Complexity It can utilize to create highly complex information.It is not fit for complicated analysis.
AnalysisIt can be utilized to achieve multi-variant analysis for huge quantities of information.It gives standard analysis methods.
AdvantagesIt can create the results in records.It has a documentation feature and command line that is extremely beneficial.
DevelopmentIt is utilized to develop the life cycle of agile development.It is utilized for large-scale development.

The Best Ever Comparison Between SPSS vs Stata

1. Key Features

SPSS offers a variety of features to the users. It includes forecasting and decision trees on data, base edition, advanced statistics and custom tables. Apart from that you will also have the add-on package for statistics and charting capabilities, complex sampling. You will also have the testing add-on in SPSS.

On the other hand, Stata has different add-on packages. These packages are latent class analysis, endogeneity, Spatial AR models, markdown, nonlinear multilevel models, finite mixture models, threshold regression etc.

2. Data Visualization

SPSS allows the data to be summarized. And it also displayed data and gives production ready analysis. We can export different types of documents from SPSS such as Excel, PDF etc. Get excel assignment help at a very affordable price.

On the other hand, Stata combines endogenous covariates. It also offers the sample selection and endogenous treatment models for continuous and positive outcomes.

3. Advanced Features

SPSS offers advanced features such as random effects with solution results. It also offers robust and standard error handling. Besides, it offers profile plots with error bars.

On the other hand,  Stata discovers and understands the unobserved data groups. Stata works on the basis of Latent Class Analysis (LCA).

4. Uses

We use SPSS to compute statistics and standard data errors from a complex sets of data sample designs. We also use it to analyse data on multi-stage designs too. However, statistics are very tough so, many students often look for the best statistics assignment help. Don’t worry you are at the right place, here at StatAnalytica our team of experts will help you.

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On the other  Stata allows you to create web pages, texts, regressions, results, reports, and graphs etc. All these features will automatically apply on the pages you created with Stata.

5. Statistics Functions

SPSS has become more powerful than ever before. The latest version of SPSS executes new Bayesian Statistics functions. This function contains regression, t-tests and ANOVA.

All these functions are becoming more popular. On the other hand, Stata has mixed logit models. This model provides advanced choice modelling that makes dozens of choices every single day to introduce random effects.

6. Charts

SPSS is the best software to create charts. You can quickly create modern charts attractively. After that, you can do their editing in Microsoft Office tools. This process is not easy process if you do it in the native methods. SPSS offers the chart builder feature to create the publication standard charts easily.

On the other hand, Stata is having the Finite mixture models. This model provides continuous, count, binary, categorical, censored, ordinal, and truncated outcomes. We can customize it with estimators and different combinations.

7. Programming

SPSS offers you to edit and edit syntax with editor shortcut tools. You can join the duplicate, delete, remove and move lines up and down with a simple keyboard shortcut. You can also trim trailing or leading spaces effectively with the help of some shortcuts.

On the other hand, Stata is having Spatial autoregressive models. It uses the observational units in this model.

8. Functions

SPSS has lots of functions it is having the SPSS Analytic Server, SPSS Modeler, and SPSS Statistics. Apart from that it also has different variable formats and types.

On the other hand, Stata has a unique word document. These documents are to be created to automate the reports more effectively. Apart from that it also generates results and graphs in tabular as well as text formats. If you want to learn more about statistics graphs then this blog will help you.

9. Special Functions

SPSS is the best statistics software that allows you to perform Simple Statistical comparison tests and the appropriate test.

On the other hand, Stata allows multi-level regression. This multi-level regression is used for interval-measured outcomes. These outcomes can be recorded into groupings, averages, aggregation, and thousands of other measures too.

10. Measurements

SPSS is having the classical approach for measurement levels. For this Nominal variable, an internal variable, and an Ordinal variable are the major parameter used by SPSS. All these variables are called metric variables.

On the other hand, Stata is the best tool to perform powerful linear regression models. Besides, we also use it to find out the most effective size, sample size, and power.

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11. Complexity

We use SPSS to model the high level of complex data. You can model any level of complexity of data using SPSS. Besides, it is quite easy to model complex data using SPSS. For this, we use multivariate analysis procedures for large amounts of data.

On the other hand, Stata is suitable for complex data analysis. It is quite overwhelming to analyze complex data using Stata. The reason is it provides normal analysis procedures. If your data complexity is high, then you should not use Stata.

12. Applications

Here are the few applications of SPSS:- 

  • Data Transformation.
  • Data Collection and Organization.
  • The output of data.

Here are some more applications of Stata:-

  • Statistics Analyze
  • Cutting-edge statistical methods.
  • Excellent built-in support for structural equation modelling.
  • Models can be built with syntax or with a path diagram.
  • Large, active online community.

This is the end of the differences between spss vs stata. Below is the graph of google trends of both software i.e spss vs stata

Spss vs Stata: Google Trends

The below figure shows the data in the form of lines of spss vs stata. Moreover, this graph shows the data for the past five years worldwide.

If we talk about SPSS, then it is represented as blue. On the other hand, STATA is represented as red. This graph shows that both the software fluctuates over time, but SPSS software stays at the top and STATA software stays at the bottom.

As per the google trends, we can see that SPSS software is at the top, but it doesn’t mean that nobody uses STATA software. Both the software have their own pros and cons. It depends on the user’s needs, where to use, how to use, and when to use.

Conclusion: SPSS vs Stata

As we are going to end the discussion on the comparison between SPSS vs Stata. Now we get the conclusion that both are excellent statistical analysis software. We use them to manage and operate a large amount of data or datasets.

In the end, we can say that we should choose SPSS, where we need the complex data analysis. On the other hand, Stata can be used in research areas when the data is not complex in nature.

SPSS and Stata are excellent tools and provide many benefits to the users as per the requirements. In contrast, I can say that SPSS is quite useful to analyze a large set of complex data. On the other hand, SPSS is quite useful to get high productivity data reports. 

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FAQs

Q1. What is SPSS?

Stata is a general-purpose statistics software package. It is widely used for statistical analysis. It was developed in the year 1985 by Stata Corp.  Stata is a proprietary licensed product. Besides, it also supports different operating systems such as Windows, Mac OS, and Linux. Stata is the best data analysis and statistical software.

Q2. What is Stata?

Stata is a general-purpose statistics software package. It is widely used for statistical analysis. It was developed in the year 1985 by Stata Corp.  Stata is a proprietary licensed product. Besides, it also supports different operating systems such as Windows, Mac OS, and Linux. Stata is the best data analysis and statistical software.

Q3. What are the Applications of SPSS and Stata?

Applications of SPSS are :
1. Data Transformation.
2. Data Collection and Organization.
3. Output of data.

Applications of Stata are :
1. Statistics Analyze
2. Cutting-edge statistical methods.
3. Excellent built-in support for structural equation modelling.
4. Models can be built with syntax or with a path diagram.
5. Large, active online community.

Q4. What is stata good for?

Stata is statistical software that allows users to manage, analyze, and create graphical visualizations of the given information. It is essentially utilized by researchers or developers in the areas of biomedicine, economics, and political science to analyze the trends of data patterns.