Basics of Scientific Data analysis

St-George-s-College-Aruvithura
  • Course Type: Certificate Course


PROGRAMME: Certificate Course in Basics of Scientific Data analysis

2023-2024

COURSE

DETAILS

CODE

SGC/ADPHY/COM/2024

TITLE

Basics of Scientific Data analysis

TOTAL NO OF HOURS

30

 

 

 

                             COURSE   OUTCOMES

1

Statistical Proficiency: Students can proficiently summarize and interpret data using descriptive statistics. They can apply inferential statistics for hypothesis testing and construct confidence intervals.

2

Data Visualization Skills: Students can choose and create appropriate data visualizations to effectively communicate insights.

3

Data Preprocessing Competency: Students can clean and preprocess data, ensuring it is ready for analysis.

4

Programming for Data Analysis: Students gain basic programming skills and can use them for data manipulation and analysis. They can apply regression analysis techniques to model relationships between variables and make predictions.

 

 

SYLLABUS

Module I.                                                                                    (10 hours)

 Introduction to Scientific Data Analysis

Overview of Scientific Data Analysis

Importance and Applications.

Descriptive Statistics

Inferential Statistics

Module 2.                                                                                      (6 hours)

Data Visualization and Data Preprocessing

Introduction to data visualization tools

Types of charts and graphs

Data cleaning and handling missing values

Data transformation and scaling

Module 3.                                                                                     (8 Hours)

Data Preprocessing and  Introduction to Programming

Data cleaning and handling missing values

Data transformation and scaling.

Basics of a programming language (Python)

Data types and structures

Univariate and bivariate analysis

Correlation and causation

Multiple linear regression

Model evaluation and interpretation

Module 4.                                                                                    (6 Hours)

Regression Analysis

Simple linear regression

Multiple linear regression

Model evaluation and interpretation

 

 

 

 

Theory / Lecture Hours:

20 hrs

 

Practical / Tutorial / Lecture Hours:

10 hrs

 

Total Hours:

30 hrs