Research Courses

SPSS

Course Title:
Basic SPSS with Practical Demonstrations and AI Integration

Course Language:
Urdu

Course Duration:
10 classes

Schedule:

• Starts from September 13, 2024
• Held on weekends (Friday, Saturday, and Sunday)
• 2 classes per day

Course Fee:
5000 PKR

Get 40% discount if you get register till 10 September

Course Overview:
This course is designed for beginners in SPSS, covering the fundamental concepts and practical demonstrations of SPSS usage. In addition to SPSS basics, the course will introduce the use of OpenAI’s large language models (LLMs) to enhance SPSS capabilities and streamline the data analysis process.

Course Structure:

• Introduction to SPSS: Interface, basic functions, and data entry
• Data management and transformation in SPSS
• Descriptive statistics and visualizations
• Introduction to hypothesis testing using SPSS
• Basic regression analysis
• Integrating AI models to automate SPSS tasks
• How to use OpenAI for SPSS queries and advanced analysis
• Step-by-step practical demonstrations in each class
• Final project: Applying learned skills to a real dataset

Additional Benefits:

• Course materials will be provided.
• SPSS software with a licensed key will be shared with participants.
• Continuous guidance and assistance throughout the course.

Registration

To register for the course, please follow these steps:

1. Fill out the registration form https://docs.google.com/forms/d/e/1FAIpQLSdEt_EL8yMM2CxY4MGWhs6QAkUhyjd5K1nIFySS1rAhVi2bPg/viewform?usp=sf_link
2. Pay the registration fee in give account number 

Habib Bank Limited (HBL)

Account Title: MUDDSAR HAMEED

Account Number:
53307000115103

IBAN: PK20HABB0053307000115103

Swift code HABBPKKA

Branch KHAYABAN-E-SIR SYED

Rawalpindi Pakistan

Receiver contact
+923435696612

3. Once you have made the payment, submit the filled registration form along with the transaction slip as proof of payment.

Course Outline 

Class 1: Introduction to Data Types and SPSS Setup

Overview of data types: nominal, ordinal, ratio, interval
   Installing SPSS and basic setup
   Basic operations: Opening files, entering data, and navigating the software

Class 2: Handling and Transforming Data

Handling missing data techniques
   Data transformation and recoding
   Creating and modifying variables

Class 3: Descriptive Statistics and Testing for Normality

Calculating mean, median, mode, and standard deviation
   Generating frequency distributions and histograms
   Testing for normality and its importance in statistical analysis

Class 4: Correlation and Basic Regression Analysis

Introduction to correlation analysis (Pearson, Spearman)
   Interpreting correlation coefficients
   Basics of regression analysis

Class 5: Advanced Regression Techniques and Assumptions

Detailed exploration of regression assumptions
   Discussion on multiple regression analysis
   AI integration to assess model fit and selection

Class 6: Basics of ANOVA

One-way ANOVA: Understanding between-group comparisons
   Assumptions of ANOVA
   Conducting post-hoc tests when assumptions are met

Class 7: Advanced ANOVA Techniques

Repeated measures ANOVA
   Two-way ANOVA: Understanding interactions and their implications

Class 8: t-Tests

Independent and paired sample t-tests
   Assumptions of t-tests and interpretation of results

Class 9: Non-Parametric Tests

When and why to use non-parametric tests
   Key tests: Chi-square, Mann-Whitney U
   AI tools to determine the appropriateness of parametric vs. non-parametric tests

Class 10: AI Integration in SPSS for Enhanced Data Analysis

Review and reinforcement of AI concepts in statistical testing
   AI-driven decision-making for choosing appropriate statistical tests
   Review session and Q&A

This streamlined course outline ensures that each class is packed with essential content