Controlling and Analyzing Large Amounts of Data Using SPSS
Controlling and Analyzing Large Amounts of Data Using SPSS
$3500.00
Day One: Introduction to SPSS and Big Data
Objectives:
Introducing participants to the basic SPSS tools.
Understanding the importance of controlling and analyzing big data in the modern era.
Familiarizing oneself with the interactive environment of SPSS and how to use it.
Content:
Introduction to SPSS and its main tools.
Basics of big data analysis.
Interacting with data through SPSS.
Opening and importing big data.
Practical exercises: Importing data from Excel and CSV files and analyzing it in SPSS.
Learning Method:
Brief theoretical explanation.
Practical exercises on big data.
Day Two: Data Cleaning and Information Filtering
Objectives:
Teaching how to clean data before starting the analysis.
How to deal with missing or inconsistent values.
Data filtering and transformation techniques.
Content:
Definition of data cleaning and reasons for its importance.
Dealing with missing values.
Methods for correcting inconsistent data.
Data filtering and transformation techniques using SPSS.
Practical exercises: Cleaning and analyzing real data.
Learning Method:
Presenting live examples of complex data.
Interactive workshops.
Day Three: Statistical Analysis of Big Data
Objectives:
Learn how to use SPSS to conduct advanced statistical analysis.
Understanding multivariate and large variable analysis techniques.
Content:
Familiarization with advanced statistical analysis using SPSS.
Conducting t-test, ANOVA, and Regression tests.
How to analyze large multidimensional variables.
Practical exercises: Applying statistical analyses to real data.
Learning Method:
Interactive workshops.
Solving analytical exercises using real data.
Day Four: Forecasting and Decision-Making Using Big Data
Objectives:
Applying forecasting techniques and trend analysis using SPSS.
Understanding how to use the results to make data-driven decisions.
Content:
Introduction to predictive analysis using SPSS.
Analysis of trends and future forecasts.
Using data to make informed decisions.
Practical exercises: Building predictive models using SPSS.
Learning Method:
Practical exercises on building predictive models.
Data analysis to identify future trends.
Day Five: Improving Skills in Big Data and Performance Reporting
Objectives:
Improving report preparation skills and graphical interpretations using SPSS.
Learn how to present data results in written and visual reports.
Content:
Creating graphical and written reports using SPSS.
Visual analysis of the results (graphs, tables).
How to present the report to beneficiaries or decision-makers.
Practical exercises: Preparing graphical reports for big data.
Learning Method:
A practical application for report and chart preparation.
Presenting results and data analysis to colleagues.
Target Audience:
Analysts and data specialists.
Business managers who work with big data.
Students or researchers interested in statistical analysis and the use of SPSS tools.
Anyone working in fields that require processing and analyzing large amounts of data.
Learning Method:
Theory: A simplified explanation of big data analysis concepts using SPSS.
Practical application: Interactive work sessions and training projects using real data.
Group discussion: Discussing and analyzing case studies in groups.
Reports and evaluations: Preparing final reports that include solutions to big data-related problems.
