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ECO154Social Sciences2 Unitsintermediate

Introduction To Quantitative Methods Ii

This course introduces students to quantitative methods in economics. It covers basic statistical definitions, data collection, measures of central tendency and dispersion. Students will learn to compute and interpret moments, skewness, kurtosis, and probability distributions. The course also explores index numbers and their applications in economic analysis, business, and finance. Emphasis is placed on applying statistical techniques to solve real-world economic problems.

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156h
Study Time
13
Weeks
12h
Per Week
intermediate
Math Level
Course Keywords
StatisticsCentral TendencyDispersionProbabilityIndex Numbers

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level
Builds on foundational knowledge
65%
intermediate
📊
Math Level
Moderate Math
🔬
Learning Type
Hands-on Practice

Course Topics

Key areas covered in this course

1

Descriptive Statistics

2

Inferential Statistics

3

Data Collection and Organization

4

Measures of Central Tendency

5

Measures of Dispersion

6

Probability Theory

7

Random Variables

8

Index Numbers

Total Topics8 topics

Ready to Start

No specific requirements needed

This course is designed to be accessible to all students. You can start immediately without any prior knowledge or specific preparation.

Assessment Methods

How your progress will be evaluated (3 methods)

Assignments

Comprehensive evaluation of course material understanding

Written Assessment

Tutor-Marked Assignments

Comprehensive evaluation of course material understanding

Written Assessment

Final Examination

Comprehensive evaluation of course material understanding

Computer Based Test

Career Opportunities

Explore the career paths this course opens up for you

Data Analyst

Apply your skills in this growing field

Market Researcher

Apply your skills in this growing field

Economist

Apply your skills in this growing field

Financial Analyst

Apply your skills in this growing field

Business Analyst

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

EconomicsBusinessFinanceMarketingGovernment

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: Basic Introduction

4h

Unit 1: Meaning and Relevance of Statistics

2 study hours
  • •Read Unit 1: Meaning and Relevance of Statistics.
  • •Define statistics and its relevance.
  • •Outline the steps in statistical inquiry.
  • •Discuss the uses of statistics in various fields.

Unit 2: Types/Branches of Statistics

2 study hours
  • •Read Unit 2: Types/Branches of Statistics.
  • •Identify and explain descriptive and inferential statistics.
  • •Understand the differences between inductive and deductive statistics.
Week
2

Module 1: Basic Introduction

4h

Unit 3: Basic Concepts in Statistics

2 study hours
  • •Read Unit 3: Basic Concepts in Statistics.
  • •Define data, array, variable, sample, and population.
  • •Distinguish between primary and secondary data.
  • •Understand sampling techniques and sampling errors.

Unit 4: Collection of Data

2 study hours
  • •Read Unit 4: Collection of Data.
  • •Identify and explain various methods of data collection.
  • •Discuss the problems associated with data collection.
Week
3

Module 1: Basic Introduction

3h

Unit 5: Organization of Data

3 study hours
  • •Read Unit 5: Organization of Data.
  • •Distinguish between grouped and ungrouped data.
  • •Construct frequency distribution tables for grouped and ungrouped data.
Week
4

Module 2: Representation o Data

4h

Unit 1: Tables

2 study hours
  • •Read Unit 1: Tables.
  • •Define table and its components.
  • •Explain the properties of a good table.
  • •Understand the importance of tables in statistics.

Unit 2: Graphs

2 study hours
  • •Read Unit 2: Graphs.
  • •Define graphs and their features.
  • •Outline the importance of graphs in statistics.
  • •Construct line graphs.
Week
5

Module 2: Representation o Data

6h

Unit 3: Charts

3 study hours
  • •Read Unit 3: Charts.
  • •Define different forms of charts.
  • •Present data in bar charts, pie charts, and Z-charts.

Unit 4: Histogram and Curves

3 study hours
  • •Read Unit 4: Histogram and Curves.
  • •Construct histograms and frequency polygons.
  • •Construct cumulative frequency curves.
  • •Use Lorenz curves and pictograms to represent data.
Week
6

Module 3: Basic Statistical Measures of Estimates

6h

Unit 1: Measures of Central Tendency Ungrouped Data

3 study hours
  • •Read Unit 1: Measures of Central Tendency Ungrouped Data.
  • •Explain the meaning and scope of measures of central tendency.
  • •Calculate mean, median, and mode for ungrouped data.

Unit 2: Measures of Central Tendency of Grouped Data

3 study hours
  • •Read Unit 2: Measures of Central Tendency of Grouped Data.
  • •Compute measures of central tendency for grouped data.
  • •Estimate measures of central tendency from curves and histograms.
Week
7

Module 3: Basic Statistical Measures of Estimates

6h

Unit 3: Measures of Dispersion

3 study hours
  • •Read Unit 3: Measures of Dispersion.
  • •Define range, mean deviation, standard deviation, and variance.
  • •Compute and interpret measures of dispersion for different forms of data.

Unit 4: Measures of Partition

3 study hours
  • •Read Unit 4: Measures of Partition.
  • •Define quartiles, deciles, and percentiles.
  • •Calculate measures of partition for both grouped and ungrouped data.
Week
8

Module 4: Moment, Skewness and Kurtosis

3h

Unit 1: Moments

3 study hours
  • •Read Unit 1: Moments.
  • •Define the concept of moments.
  • •Compute first, second, third, and fourth moments for ungrouped and grouped data.
  • •Apply Charlier's check and Sheppard's correction.
Week
9

Module 4: Moment, Skewness and Kurtosis

3h

Unit 2: Skewness

3 study hours
  • •Read Unit 2: Skewness.
  • •Define skewness.
  • •Identify features of skewness.
  • •Describe, compute, and interpret measures of skewness.
Week
10

Module 4: Moment, Skewness and Kurtosis

3h

Unit 3: Kurtosis

3 study hours
  • •Read Unit 3: Kurtosis.
  • •Define kurtosis.
  • •State and explain types of kurtosis.
  • •Identify measures of kurtosis and their interpretations.
Week
11

Module 5: Basic Statistical Measures of Estimates

3h

Unit 1: Basic Concept in Probability

3 study hours
  • •Read Unit 1: Basic Concept in Probability.
  • •Distinguish between events, experiments, sample space, and probability.
  • •Differentiate mutually exclusive, conditional, and independent events.
Week
12

Module 5: Basic Statistical Measures of Estimates

6h

Unit 2: Use of Diagram in Probability

3 study hours
  • •Read Unit 2: Use of Diagram in Probability.
  • •Solve probability problems using tree diagrams.
  • •Solve probability problems using Venn diagrams.

Unit 3: Experimental Probability Rules

3 study hours
  • •Read Unit 3: Experimental Probability Rules.
  • •State and apply basic probability rules.
  • •Demonstrate the practicability of probability rules.
Week
13

Module 5: Basic Statistical Measures of Estimates

6h

Unit 4: Experimental Probability

3 study hours
  • •Read Unit 4: Experimental Probability.
  • •Compute probability values with different forms of selection.
  • •Use tabular data to solve probability problems.

Unit 5: Random Variable and Mathematics of Expectation

3 study hours
  • •Read Unit 5: Random Variable and Mathematics of Expectation.
  • •Define and explain the concept of random variables.
  • •Describe random variable distribution with respect to probabilities, mean, variance, and standard deviation.
  • •Carry out mathematical problems involving expectation.

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Review all definitions and formulas from Units 1-5 in Modules 3 and 5.

2

Practice calculating measures of central tendency and dispersion for both grouped and ungrouped data.

3

Focus on understanding the differences between various sampling techniques.

4

Create diagrams illustrating probability concepts like mutually exclusive and independent events.

5

Work through all examples in the study units and attempt similar problems from textbooks.

6

Pay special attention to the application of Bayes' theorem and index number calculations.

7

Review all Tutor-Marked Assignments (TMAs) and address any areas of weakness identified by your tutor.

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