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 OutcomesAfter 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.
Overview
Syllabus
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
Taught by
Dr Jaspreet Kaur, Assistant Professor of Economics |
