Number Analytics

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. With powerful graphs and tables, we provide commonly used statistical analysis such as ANOVA, linear regression, K-means clustering and survival analysis (Kaplan-meier plot). Text cloud visualization lets you analyze unstructured text data in seconds. 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 the right statistical models and explain the statistical results in plain English. Also you can run more than 100 statistical analyses at once. The statistical results like linear regression and ANOVA show not only statistical test results but also graphs with confidence intervals and marginal effects and tables coded with statistical difference among 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). The supported data file formats are listed below. Supported data file formats - SPSS, Excel, CSV, STATA, SAS Currently the upload file size is limited to 2Mb. Descriptive analysis -Descriptive statistics -Frequency Table -Crosstab (Chi-sq. Test) -Pivot table -Correlation -Text analytics 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