Statistical analysis and reporting. Address the entire analytical process: planning, data collection, analysis, reporting, and deployment.
Predictive modeling and data mining. Use powerful model-building, evaluation, and automation capabilities.
Decision management and deployment….
Big data analytics.
- Duration: 35 – 40 hrs
- Timings: Week days 1-2 Hours per day (or) Weekends: 2-3 Hours per day
- Method: Online/Classroom Training
- Study Material: Soft Copy
- Data Entry, Data Editor
- Basic Calculations
- Recoding, Missing values
- Split file
- Weighted Cases
- Using External Source Data (Import/Export)
- Frequencies, Descriptives, Cross Tabs, Exploratory
- Custom Tables
- Visual Statistics
- Chart Builder, Histograms, Box Plots, Bar Charts
- Cluster Bar, Stacked Bar
- Error bar
- Line charts, Pie charts
- Editing graphs and Axes
- Statistical Testing: Parametric vs. Non parametric
- Confidence Intervals, Power of the test
- Normal Curve, Normality Test
- Homogeneity of variance
- T-Test: One Sample, Independent Sample, Paired Sample
- Analysis of variance
- General linear Model
- Non Parametric Tests: Mann Whitney U test, Wilcoxon Signed ranks test, Kruskal Wallis Test, Friedman Test
- Chi-Square Test: Test of Independence, 2x2 Cross tabulation, Layered cross tab, Goodness of fit
- Linear Correlation and Regression: Pearson Correlation, Spearman Correlation, Kendall Tau B, Scatter Plots, Partial correlation
- Linear Regression
- Logistic Regression
- Time Series : Seasonal Indices, Forecasting using ARIMA Modeling
- Factor Analysis
- Cluster Analysis
- Decision Trees / Random Forests
** All the Concepts will be explained using appropriate data and business examples
- Career oriented training.
- One to One live interaction with a trainer.
- Demo project end to end explanation.
- Interview guidence with resume preparation.
- Support with the trainer through E-mail.