Statistical Data Management is a systematic process that transfers raw data to intelligent data and requires the application of an integrated process. At a time when companies in many industries offer similar products and services and use comparable technologies, in variety of business problems, the use of predictive analysis is the remaining key process of differentiation. As a result, organizations that effectively implement this emerging use of extensive analytics and fact-based decision-making from the top down are staying ahead of their competition.

What we can do for you?

• Data Summarization: - Cross Tabs, Correlation etc
• Data Visualization: - Bar Plots, Bubble Plots, Control Charts, Histograms, Pareto Charts, Pie Charts, Q-Q Plots etc
• Comparing Samples: - Binomial Tests, Fishers Tests, Chi-Square Tests etc
• Regression Analysis: - Linear, Ordinal, Log-Linear models, and Non-Linear Regression etc
• ANOVA: - Mixed Models, Multiple Comparisons, Random Effects etc
• Nonparametric Tests: - Signed Rank Tests, Chi-Square GOF, Non-Parametric Anova etc
• Multivariate Analysis: - Discriminant Analysis, Factor Analysis, Cluster Analysis etc
• QC Charts and Analysis: - Simple Control Charts, Process and Quality Control Analysis, Pareto Chart Analysis, Six Sigma DMAIC Tools etc
• Survival Techniques: - Parametric Survival Models, Cox Regression etc
• Time Series: - Auto Correlation, Seasonal Variation Analysis, Lag and Spectrum Plots, ARIMA etc
• Data and Text Mining: - Visualizations, CRISP-DM, Text and web Mining
• Missing Value Analysis: - MCAR, MAR, Multiple Imputation
• Bootstrapping: - Bootstrap Methods, Jack Knifing, Custom Simulations

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