Master Statistical Analysis with ENCODE-IT's SPSS Analytics Training

Course Introduction: In today’s data-driven world, organizations rely heavily on statistical analysis to
drive informed decision-making. SPSS (Statistical Package for the Social Sciences) is one of the most
powerful and widely-used tools for performing advanced statistical analysis, making it an essential
skill for professionals working in fields such as research, marketing, healthcare, social sciences, and
more.
ENCODE-IT's SPSS Analytics Training provides comprehensive instruction in using SPSS to analyze
data, perform statistical tests, and interpret results effectively. This course is designed for individuals
looking to enhance their data analytics skills and leverage the full potential of SPSS to analyze large
datasets, create insightful reports, and make data-driven decisions.

Throughout this course, you will gain hands-on experience with the SPSS software and learn how to
conduct various statistical analyses, including descriptive statistics, hypothesis testing, regression
analysis, factor analysis, and more. By the end of the course, you will be equipped with the
knowledge and skills to become a proficient user of SPSS for statistical and predictive analytics.

Salary Scale in India: SPSS-trained professionals are highly sought after in various industries,
including healthcare, education, marketing, and finance. Here’s an overview of the salary scale for
SPSS Analytics professionals in India:
 Entry-Level SPSS Analyst: ₹4 Lakhs to ₹7 Lakhs per annum
 Mid-Level Data Analyst (SPSS): ₹7 Lakhs to ₹12 Lakhs per annum
 Senior Data Scientist/Statistician (SPSS): ₹12 Lakhs to ₹20 Lakhs+ per annum

As organizations continue to focus on leveraging data for strategic decision-making, SPSS expertise is
increasingly valuable, ensuring competitive salaries and career growth.

Placement Assistance & Certification: Upon successful completion of the SPSS Analytics Training
course, you will receive an ENCODE-IT Certification, demonstrating your proficiency in SPSS and
statistical analysis. Our dedicated Placement Assistance team will help you with resume
preparation, interview coaching, and job placement opportunities, enabling you to land your ideal
role in the analytics field.

Course Curriculum:

1. Introduction to SPSS
o What is SPSS? Overview and Features
o Understanding the SPSS Interface and Workspace
o Importing and Exporting Data in SPSS
o Data Types and Variables in SPSS
o Working with Data Editor and Viewer

2. Descriptive Statistics
o Introduction to Descriptive Statistics
o Measures of Central Tendency: Mean, Median, Mode

o Measures of Dispersion: Range, Variance, Standard Deviation
o Frequency Distribution and Categorical Data Analysis
o Creating and Interpreting Graphs: Histograms, Boxplots, Bar Charts

3. Data Preparation and Cleaning
o Data Cleaning Techniques: Handling Missing Data and Outliers
o Data Transformation: Recoding Variables, Creating Dummy Variables
o Merging and Aggregating Datasets in SPSS
o Sorting, Filtering, and Selecting Data for Analysis
o Ensuring Data Quality: Identifying and Correcting Errors

4. Hypothesis Testing
o Introduction to Hypothesis Testing in SPSS
o One-Sample t-Test, Independent and Paired t-Tests
o Chi-Square Tests for Categorical Data
o Analysis of Variance (ANOVA) for Comparing Multiple Groups
o Interpreting p-Values, Confidence Intervals, and Test Results

5. Correlation and Regression Analysis
o Introduction to Correlation: Pearson’s and Spearman’s Correlation Coefficient
o Simple Linear Regression Analysis
o Multiple Linear Regression: Model Building and Interpretation
o Assumptions of Regression and Model Diagnostics
o Evaluating Model Fit: R-Squared, Adjusted R-Squared, and Residuals

6. Factor Analysis
o Understanding Factor Analysis and Its Applications
o Exploratory Factor Analysis (EFA) and Principal Component Analysis (PCA)
o Determining the Number of Factors and Interpreting Results
o Rotating Factors for Better Interpretation
o Validating Factor Models and Testing for Reliability

7. Time Series Analysis
o Introduction to Time Series Data and Its Components
o Decomposition of Time Series: Trend, Seasonality, Noise
o Time Series Forecasting with ARIMA Models

o Evaluating Forecast Accuracy: Mean Absolute Error, RMSE
o Working with Moving Averages and Exponential Smoothing

8. Advanced Statistical Techniques in SPSS
o Multivariate Analysis of Variance (MANOVA)
o Logistic Regression for Binary Outcomes
o Survival Analysis: Kaplan-Meier Estimator and Cox Proportional Hazards Model
o Cluster Analysis: K-Means and Hierarchical Clustering
o Discriminant Analysis: Classifying Data Based on Predictor Variables

9. Data Visualization in SPSS
o Introduction to Data Visualization Principles
o Creating Graphs and Charts in SPSS
o Customizing Graphs: Titles, Legends, and Axes
o Advanced Visualization: Scatter Plots, Line Graphs, and 3D Plots
o Exporting Visualizations for Reporting

10. SPSS for Predictive Analytics
o Introduction to Predictive Analytics with SPSS
o Building Predictive Models Using Regression and Classification Techniques
o Model Evaluation: Cross-Validation and Performance Metrics
o Implementing Predictive Modeling in Real-World Scenarios
o Using SPSS for Market Basket Analysis and Customer Segmentation

11. SPSS Macros and Automation
o Introduction to SPSS Macros for Automating Repetitive Tasks
o Writing and Running Macros for Data Analysis
o Automating Report Generation and Data Export
o Using Syntax for Advanced Data Manipulation
o Customizing SPSS to Suit Your Analysis Needs

12. Real-World SPSS Analytics Projects
o Market Research Analysis: Analyzing Survey Data
o Healthcare Analytics: Analyzing Patient Data and Outcomes
o Customer Behavior Analysis: Predicting Purchasing Patterns
o Social Science Research: Statistical Analysis of Survey Results

o Financial Modeling: Risk and Return Analysis

13. Final Project and Certification Exam
o Final Project: End-to-End Data Analysis and Reporting Using SPSS
o Project Evaluation: Demonstrating Your SPSS Analytics Skills
o Final Exam: Comprehensive Test on SPSS Concepts and Techniques
o Certification of Completion from ENCODE-IT and Job Placement Assistance

Key Features of the Course:
 Tools & Platforms: SPSS, Microsoft Excel, R, Python for Advanced Analysis
 Real-World Projects: Work on real-life projects involving market research, healthcare data,
customer analytics, and more
 Certification & Placement Support: ENCODE-IT certification and job placement assistance to
help you land your desired role in analytics
 Expert Instructors: Learn from industry professionals with deep expertise in statistical
analysis and SPSS tools
 Career Advancement: Enhance your data analysis skills and unlock career opportunities in
fields like market research, healthcare analytics, finance, and education

By completing the SPSS Analytics Training course at ENCODE-IT, you will develop a deep
understanding of statistical methods and learn how to apply them using SPSS software. Whether you
are interested in data analysis, market research, or academic studies, this course will equip you with
the tools you need to excel in statistical analysis and predictive modeling.