MAXQDA Description

Analyze all types of data, including text, images, audio/video files, websites and tweets. You can also analyze focus group discussions, survey results, and other data. MAXQDA is powerful, user-friendly, innovative, and intuitive. It is also the only QDA software that is 100% compatible on both Windows and Mac. MAXQDA will handle all files, no matter how you conduct interviews in the field. Handwritten notes, audio and visual recordings, transcripts from transcription companies, Word or PDF files with comments and highlighting can all be imported. You can assign colors to your documents and arrange them by topic, location, time, or category. The integrated MAXQDA transcription software makes it easy to transcribe audio and video files. To ensure that you capture all of your initial ideas, you can immediately begin to code, add memos and paraphrase your data while you transcribe.

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Pricing

Pricing Starts At:
$45 per user per month

Integrations

No Integrations at this time

Reviews - 1 Verified Review

Total
ease
features
design
support
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Company Details

Company:
VERBI Software
Year Founded:
1989
Headquarters:
Germany
Website:
www.maxqda.com

Media

Play Video MAXQDA Screenshot 1 MAXQDA Screenshot 2
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Product Details

Platforms
Windows
Mac
Type of Training
Documentation
Webinars
Customer Support
Phone Support
Online

MAXQDA Features and Options

Qualitative Data Analysis Software

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

MAXQDA Lists

MAXQDA User Reviews

Write a Review
  • Name: DANIEL P.
    Job Title: Manager TI
    Length of product use: Free Trial
    Used How Often?: Yearly
    Role: Administrator, Deployment
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Statics Software

    Date: Nov 07 2024

    Summary: Interface and Usability
    Ease of Use: A well-designed interface makes the software easy to navigate. This includes clear menus, logical workflows, and accessible options for importing, processing, and analyzing data.
    Graphical Interface vs. Command Line: GUI-based software like SPSS, Stata, and Excel allows users to perform statistical analysis without needing to write code, making it more accessible for people who prefer visual interaction. On the other hand, software like R, Python, or MATLAB relies heavily on code, offering more flexibility and control but at the cost of requiring programming knowledge.
    Customization: Advanced users appreciate the ability to customize analyses through scripts or functions. However, some software platforms can be restrictive in this regard, limiting users to pre-built analysis templates or models.

    Positive: A good statistics software should have an intuitive and easy-to-navigate interface, allowing both beginners and experts to use it efficiently. Clear menus, well-organized toolbars, and comprehensive help options are essential.
    Comprehensive Statistical Tools:

    It should offer a wide range of statistical functions, from basic descriptive statistics (mean, median, standard deviation) to more complex inferential statistics (hypothesis testing, regression analysis, ANOVA, etc.).
    Specialized methods such as time-series analysis, multivariate analysis, and Bayesian statistics are also valuable.
    Data Import and Export Capabilities:

    The software should support importing data from various formats (e.g., Excel, CSV, SPSS, SAS, and databases) and exporting results into formats like PDF, Excel, or image files for easy reporting.
    Data Visualization:

    Strong data visualization features, such as customizable charts, histograms, scatter plots, and heatmaps, help users better understand and present their data.
    The ability to create high-quality, publication-ready visuals is a plus.
    Advanced Analytical Features:

    Advanced tools like machine learning algorithms, multivariate analysis, and time-series forecasting can greatly enhance the software's capabilities for complex data analysis.

    Negative: Limited Support for Unstructured Data
    Problem: Traditional statistical software may struggle to handle unstructured data, such as free text, images, or sensor data.
    Impact: This limits the application of the software in areas like sentiment analysis, natural language processing (NLP), or image analysis.

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