• support@conveytechlabs.com

Analytics using IBM SPSS

35 – 40 hrs

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)
    Descriptive Statistics
    • 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 Inference
    • Statistical Testing: Parametric vs. Non parametric
    • Confidence Intervals, Power of the test
    • Normal Curve, Normality Test
    • Homogeneity of variance
    • Bootstrapping
    • 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
    Predictive Modeling/Forecasting
    • Linear Regression
    • Logistic Regression
    • Time Series : Seasonal Indices, Forecasting using ARIMA Modeling
    Advanced Analytics
    • 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.

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