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ECO253Social Sciences3 Unitsintermediate

Statistics for Economist I

This course introduces fundamental statistical concepts and techniques essential for economists. It covers probability distributions, hypothesis testing, correlation, and regression analyses. Students will learn to gather and manipulate economic data, perform basic statistical tests, and apply statistical models to real-world scenarios. The course also explores non-parametric methods, sampling theory, and the central limit theorem, equipping students with the skills to solve problems using statistical software and interpret economic data effectively.

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120h
Study Time
13
Weeks
9h
Per Week
intermediate
Math Level
Course Keywords
StatisticsEconometricsProbabilityRegressionHypothesis Testing

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

Probability Distributions

2

Hypothesis Testing

3

Correlation Analysis

4

Regression Analysis

5

Sampling Theory

6

Central Limit Theorem

7

Index Numbers

Total Topics7 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 Assessments

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

Economist

Apply your skills in this growing field

Data Analyst

Apply your skills in this growing field

Market Research Analyst

Apply your skills in this growing field

Financial Analyst

Apply your skills in this growing field

Statistician

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

FinanceEconomicsMarket ResearchGovernmentConsulting

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: Probability and Statistic Distribution Functions

2h

Unit 1: Bernoulli Distribution

2 study hours
  • •Define Bernoulli distribution and its properties.
  • •Differentiate between discrete and continuous probability distributions.
  • •Solve problems related to Bernoulli trials and processes.
Week
2

Module 1: Probability and Statistic Distribution Functions

2h

Unit 2: Binomial Distribution

2 study hours
  • •Compute probabilities using the binomial probability distribution.
  • •Calculate the mean and standard deviation of binomial random variables.
  • •Apply binomial distribution to economic scenarios.
Week
3

Module 1: Probability and Statistic Distribution Functions

2h

Unit 3: Normal Distribution

2 study hours
  • •State the characteristics of normal probability distribution.
  • •Compute values for normal probability distribution using z-scores.
  • •Compute probabilities from normal distribution tables.
Week
4

Module 1: Probability and Statistic Distribution Functions

2h

Unit 4: Poisson Distribution

2 study hours
  • •State the characteristics of Poisson distribution.
  • •Compute probabilities from Poisson distribution.
  • •Apply Poisson distribution to real-world problems.
Week
5

Module 2: Statistical Hypothesis Test

2h

Unit 1: T- test

2 study hours
  • •Conduct a t-test for a single mean.
  • •Interpret the results of a t-test.
  • •Differentiate between one-tailed and two-tailed tests.
Week
6

Module 2: Statistical Hypothesis Test

2h

Unit 2: F- test

2 study hours
  • •List the characteristics of the F distribution.
  • •Conduct a test of hypothesis to determine whether the variances of two populations are equal.
  • •Interpret the results of an F-test.
Week
7

Module 2: Statistical Hypothesis Test

2h

Unit 3: Chi square test

2 study hours
  • •List the characteristics of the chi-square distribution.
  • •Conduct a chi-square test for goodness of fit.
  • •Compute a chi-square test for independence of attributes.
Week
8

Module 2: Statistical Hypothesis Test

2h

Unit 4: ANOVA

2 study hours
  • •Organize data into a one-way ANOVA table.
  • •Conduct a test of hypothesis among three or more treatment means.
  • •Interpret the results of an ANOVA test.
Week
9

Module 2: Statistical Hypothesis Test

2h

Unit 5: Parametric and Non-Parametric test Methods

2 study hours
  • •Explain the meaning of non-parametric statistics.
  • •Compute the Sign test.
  • •Compute the Kruskal-Wallis test.
Week
10

Module 3: Correlation and Regression Coefficient Analyses

4h

Unit 10: Pearson's Correlation Coefficient

2 study hours
  • •Explain the types of correlation.
  • •Calculate the Pearson's coefficient of correlation.
  • •Interpret the coefficient of correlation.

Unit 11: Spearman's Rank Correlation Coefficient

2 study hours
  • •Explain the meaning of Spearman's Rank Correlation.
  • •Calculate the Spearman's rank correlation coefficient.
  • •Interpret the Spearman's rank correlation coefficient.
Week
11

Module 3: Correlation and Regression Coefficient Analyses

4h

Unit 12: Methods of Curve and Eye Fitting of Scattered Plot and the Least Square Regression Line

2 study hours
  • •Apply methods of curve fitting to scattered plots.
  • •Understand the concept of the least square regression line.
  • •Analyze scattered plots and determine the best-fit curve.

Unit 12: Methods of Curve and Eye Fitting of Scattered Plot and the Least Square Regression Line

2 study hours
  • •Apply the least square regression line.
  • •Understand the concept of the least square regression line.
  • •Analyze regression line.
Week
12

Module 3: Correlation and Regression Coefficient Analyses

2h

Unit 13: Forecasting in Regression

2 study hours
  • •Apply regression models for forecasting.
  • •Understand the concept of forecasting in regression.
  • •Analyze regression for forecasting.
Week
13

Module 5: Index Numbers and Introduction to Research Methods in Social Sciences

6h

Unit 18: Index Number

2 study hours
  • •Review Index Number.
  • •Review Statistical Data.
  • •Review Sample and Sampling Techniques.

Unit 19: Statistical Data

2 study hours
  • •Review Index Number.
  • •Review Statistical Data.
  • •Review Sample and Sampling Techniques.

Unit 20: Sample and Sampling Techniques

2 study hours
  • •Review Index Number.
  • •Review Statistical Data.
  • •Review Sample and Sampling Techniques.

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 module objectives and key concepts from each unit.

2

Practice solving numerical problems from the examples in the study units.

3

Create concept maps linking probability distributions, hypothesis tests, and regression techniques.

4

Focus on understanding the assumptions and limitations of each statistical method.

5

Practice interpreting statistical results and drawing economic conclusions.

6

Review all Tutor Marked Assignments (TMAs) and their solutions.

7

Allocate study time proportionally to the weight of each module in the final examination.

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