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Number Analytics

Number Analytics is a statistical software for advanced statistical tests, regression analysis, text analysis, and survival analysis

Number Analytics is a statistical software for advanced statistical tests, regression analysis, text analysis, and survival analysis

Number Analytics

by Number Analytics LLC
Number Analytics
Number Analytics
Number Analytics

What is it about?

Number Analytics is a statistical software for advanced statistical tests, regression analysis, text analysis, and survival analysis. It supports multiple data formats like SPSS, Minitab, Excel, CSV, STATA and SAS. The software provides powerful graphs and tables for mean difference tests (T-test, ANOVA), linear regression, logistic regression, K-means clustering, and survival analysis (Kaplan-meier plot). Text cloud visualization enables you to analyze unstructured customer feedback text data in seconds. Easily analyze your data anytime, anywhere with smartphones and tablets.

Number Analytics

App Details

Version
1.0.7
Rating
(3)
Size
16Mb
Genre
Productivity Business
Last updated
February 18, 2025
Release date
October 20, 2023
More info

App Screenshots

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App Store Description

Number Analytics is a statistical software for advanced statistical tests, regression analysis, text analysis, and survival analysis. It supports multiple data formats like SPSS, Minitab, Excel, CSV, STATA and SAS. The software provides powerful graphs and tables for mean difference tests (T-test, ANOVA), linear regression, logistic regression, K-means clustering, and survival analysis (Kaplan-meier plot). Text cloud visualization enables you to analyze unstructured customer feedback text data in seconds. Easily analyze your data anytime, anywhere with smartphones and tablets.
Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

Statistical analysis is critical to improving business, society, and how we live. Market research for new product development, social science research at universities, and medical research at hospitals are all looking for statistically significant data patterns based on actual, experimental, or survey data. Number Analytics is designed for users who are not good at coding and statistics, but need to easily analyze various types of data for their research on their mobile devices.

In the past, analyzing data meant spending hours preparing data, summarizing summary statistics, performing numerous statistical analyses based on hypotheses, and finding statistically significant relationships between variables. Especially for beginners, selecting the right statistical models and interpreting the results are the pain points and require considerable time and effort. Now it can be done with clicks and automation that can speed up the process at least 10 times.

With Number Analyzer, the computer will automatically apply these statistical models and explain the statistical results in plain English. Because the computer knows which statistical models to use, you can run more than 100 statistical analyses at once. The statistical results, such as linear regression and ANOVA, show not only statistical test results, but also graphs with confidence intervals and marginal effects, and tables coded with statistical differences between subgroups.

To upload your own data, first download or move your data to iCloud storage. Then click the Upload button in the Data section. You can easily upload and use the data. Various data formats are supported including labelled survey data (SPSS).

Supported data file formats
- SPSS, Excel, CSV, Minitab, STATA, SAS

Currently the upload file size is limited to 2Mb.

Descriptive statistics
-Summary Statistics
-Frequency Table
-Crosstab (Chi-sq. Test)
-Pivot table
-Correlation
-Text analysis

Mean Difference test
-One Sample T-test
-Paired Sample T-test
-Independent Samples T-test
-ANOVA (Analysis of Variance) test

Regression Analysis
- Linear Regression
- Fixed Effect Regression
- Logistic Regression

Clustering Analysis
- K-Means Clustering

Survival Analysis
-Kaplan Meier plot

Disclaimer:
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