Data Analysis

By Dr Jaspreet Kaur, Assistant Professor of Economics | | Bathinda College of Law, Bathinda, Punjab

Learners enrolled: 3983

This course begins with some basic concepts and terminology that are fundamental to data analysis and inference. This course introduces the student to collection and presentation of data. It also discusses how data can be summarized and analysed for drawing statistical inferences. The students will be introduced to important data sources that are available and will also be trained in the use of statistical software to analyse data.

The main objectives of this course are:

To know about the process of data collection and presentation.
To learn the way of obtaining secondary data from various sources.
To discover the technique of processing and analysing the data for drawing statistical inferences.

Learning Outcomes

After completing this course you shall be able to:

Understand the data, its types of measurement and collection.
Know the procedure of determining the sample size and distribution.
Outline the designing of questionnaire and procedure of pre – testing.
Perform the coding, editing, classification, tabulation and graphical representation of data.
Analyse the univariate and bivariate frequency distributions.
Understand the theoretical foundations of different tests and their role in hypothesis testing.
Design the composite index numbers.

Summary

Course Status :	Completed
Course Type :	Not Applicable
Language for course content :	English
Duration :	15 weeks
Category :	Mathematics
Credit Points :	4
Level :	Undergraduate
Start Date :	31 Jul 2023
End Date :	31 Oct 2023
Enrollment Ends :	31 Aug 2023
Exam Date :

Page Visits

Course layout

Course Content

Module No.	Title of Lesson/Module
	Introduction and overview
1	Data and Types of Measurement
2	Primary and Secondary Data: Merits and Demerits
3	Methods of Collecting Primary Data
4	Population and Sample: Merits and Demerits
5	Sampling Methods: Random and Non-Random
6	Sampling Size and Distribution
7	Sampling and Non - Sampling Errors
8	Designing a Questionnaire: Editing and Pretesting
9	Types of Interview Techniques
10	Methods of Collecting Secondary Data
11	Data Processing - Editing and Coding
12	Data Processing - Classification and Tabulation
13	Cross Tabulation and its Significance
14	Practical Problems
15	Graphical Representation of Data - Line Graph, Bar Diagram and Pie Chart
16	Graphical Representation of Data – Histograms and Ogives
17	Practical Problems of Graphical Representation
18	Univariate Frequency Distribution-Measures of Central Tendency
19	Univariate Frequency Distribution-Measures of Dispersion
20	Univariate Frequency Distribution- Skewness, Moments and Kurtosis
21	Numerical Problems: Univariate Frequency Distribution
22	Bivariate Frequency Distribution-Correlation, Various Methods
23	Bivariate Frequency Distribution-Regression Analysis
24	Numerical Problems: Bivariate Frequency Distribution
25	Estimation of Population Parameters
26	Methods of Estimation
27	Unbiased Estimator of Population Mean
28	Unbiased Estimator of Population Variance
29	Basic concepts of inference
30	Testing of hypothesis-types, uses
31	Testing of hypothesis: t test
32	Testing of hypothesis: F test
33	Testing of hypothesis: Z test
34	Testing of hypothesis: Chi Square test
35	ANOVA- one way and Interpretation
36	ANOVA- two way and Interpretation
37	Numerical Problems
38	Basics of Index Numbers
39	Price and Quantity Indices and their Properties
40	Numerical Problems of Index Numbers