Course Overview
SPSS is used extensively in business, government and academia. It is a statistical analysis package and so allows any organization or individual that holds large amounts of data to analyze it and understand it more deeply. At its most simple it is very useful for discovering correlations between different variables. At its most powerful it can be used to make statistically valid forecasts for future events or results. Everything in our course is aimed at making you a faster and more relaxed SPSS user. Our courses are deliberately hands-on including lots of small exercises and examples to ensure that you spend time working with SPSS. We believe that software skills that are developed in this way are deeper than those developed from classroom explanations. Our exercises are carefully chosen to emphasis the key aspects of each lesson.
Duration
10 days
Target Audience
- Data Analysts and Scientists
- Researchers
- Statisticians
- Business Analysts
- Market Researchers
- Healthcare Analysts
- Quality Control Analysts
- Consultants
Organizational Impact
- Enhanced data visualization and reporting capabilities.
- Improved accuracy and efficiency in statistical analysis.
- Better decision-making through advanced graphical representations.
- Streamlined data tabulation and interpretation processes.
- Increased proficiency in handling complex datasets and analyses.
Personal Impact
- Master advanced graphical techniques and statistical analysis methods.
- Develop expertise in using SPSS for comprehensive data analysis.
- Enhance your ability to present and interpret complex data insights.
- Boost your professional skill set and career opportunities in data analysis.
- Gain confidence in applying advanced SPSS techniques to real-world problems.
Course Level:
Course Objectives
- Understand and apply advanced graphical techniques in SPSS.
- Perform complex data tabulations and summarizations.
- Conduct sophisticated statistical analyses using SPSS tools.
- Interpret and present data effectively with advanced graphics.
- Develop practical skills through hands-on exercises and case studies.
Course Outline
Module 1: Introduction to Advanced SPSS Features
- Custom Tables and Output Management
- Advanced Data Transformation Techniques
- Syntax and Script Automation
- Handling Large Datasets
- Case Study: Analyzing survey data from a large-scale customer satisfaction study
Module 2: Advanced Descriptive Statistics
- Measures of Central Tendency and Dispersion
- Frequency Distributions and Cross-tabulations
- Percentiles and Quartiles
- Descriptive Statistics for Complex Survey Data
- Case Study: Summarizing demographic data from a national health survey
Module 3: Advanced Graphical Techniques
- Creating Multi-layered Bar and Line Charts
- Customizing Pie Charts and Histograms
- Overlaying Graphs for Comparative Analysis
- Interactive and Dynamic Graphs
- Case Study: Visualizing sales performance across different regions over multiple years
Module 4: Statistical Testing and Comparisons
- Advanced T-tests and ANOVA
- Non-parametric Tests and Their Applications
- Post-hoc Analysis
- Testing Assumptions and Validity
- Case Study: Comparing the effectiveness of different marketing strategies
Module 5: Regression Analysis
- Multiple Linear Regression
- Interaction Effects and Polynomial Terms
- Logistic Regression and Model Fit
- Checking for Multicollinearity and Autocorrelation
- Case Study: Predicting employee performance based on various factors
Module 6: Factor Analysis
- Exploratory Factor Analysis (EFA)
- Confirmatory Factor Analysis (CFA)
- Interpreting Factor Loadings and Rotation
- Validating Factor Solutions
- Case Study: Identifying underlying factors in customer satisfaction surveys
Module 7: Cluster Analysis
- K-means and Hierarchical Clustering
- Evaluating Cluster Solutions
- Distance Metrics and Similarity Measures
- Visualizing Clusters and Profile Analysis
- Case Study: Segmenting customers based on purchasing behavior
Module 8: Survival Analysis
- Kaplan-Meier Estimator
- Log-Rank Test and Cox Proportional-Hazards Model
- Handling Censoring and Missing Data
- Interpreting Survival Curves
- Case Study: Analyzing time-to-event data in clinical trials
Module 9: Time Series Analysis
- Identifying Trends and Seasonal Patterns
- Autoregressive Integrated Moving Average (ARIMA) Models
- Forecasting Techniques and Model Evaluation
- Decomposition of Time Series Components
- Case Study: Forecasting quarterly sales based on historical data
Module 10: Data Management and Automation
- Data Cleaning and Validation Techniques
- Automating Repetitive Tasks with SPSS Syntax
- Integrating SPSS with Other Software (e.g., Excel, R)
- Managing and Merging Multiple Datasets
- Case Study: Automating data preparation and analysis for monthly financial reports
Related Courses
Course Administration Details:
Methodology
These instructor-led training sessions are delivered using a blended learning approach and include presentations, guided practical exercises, web-based tutorials, and group work. Our facilitators are seasoned industry experts with years of experience as professionals and trainers in these fields. All facilitation and course materials are offered in English. Participants should be reasonably proficient in the language.
Accreditation
Upon successful completion of this training, participants will be issued an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).
Training Venue
The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments, and lunch. All participants will additionally cater to their travel expenses, visa application, insurance, and other personal expenses.
Accommodation and Airport Transfer
Accommodation and Airport Transfer are arranged upon request. For reservations contact the Training Officer.
- Email: [email protected]
- Phone: +254715 077 817
Tailor-Made
This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location. For further inquiries, please contact us on:
- Email: [email protected]
- Phone: +254715 077 817
Payment
Payment should be transferred to the IRES account through a bank on or before the start of the course. Send proof of payment to [email protected]
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