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ECO726

Applied Statistics

This course introduces students to statistical tools applicable in economic analysis, building upon elementary statistics and economics foundations. It covers basic sampling and survey techniques, including sampling distributions and parameter estimation. Students will learn hypothesis testing, regression analysis, and time series analysis. The course aims to equip students with the ability to apply statistical tools to real-life economic problems and interpret calculated coefficients effectively.

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About this course

Difficulty
Intermediate
Study hours
45 hours
Maths
Intermediate
Content
Theoretical, problem solving, case study
Practical work
No
How it is assessed
  • Assignments
  • Tutor marked assignments
  • Final examination

What you'll read

The real module and unit structure of ECO726, taken from the course material NOUN publishes.

One paragraph, so you can see how it reads

ECO726 · UNIT 1: SAMPLING, SURVEY AND SAMPLING DISTRIBUTION

Statistical inference is the process by which conclusions are drawn on the basis of sample about the population from which sample is drawn. In order words, it is a process by which conclusion are drawn about some measure or attribute of a population based upon analysis of sample.

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What you should be able to do

  1. Apply statistical tools in economic problems.
  2. Interpret calculated coefficients in economic contexts.
  3. Conduct hypothesis tests using appropriate statistical methods.
  4. Perform regression analysis to model economic relationships.
  5. Analyze time series data to identify trends and patterns.

What it prepares you for

Careers
  • Economist
  • Data Analyst
  • Market Research Analyst
  • Financial Analyst
  • Statistician
Where it is applied
  • Finance
  • Economics
  • Market Research
  • Government
  • Consulting

Where it gets hard

The units students slow down on, and what makes each one heavy.

  • Module 2: ESTIMATION AND STATISTICAL TEST OF SIGNIFICANCE

    Unit 7: ANOVA/F-test

    ANOVA/F-test requires understanding of statistical distributions and hypothesis testing, and the ability to interpret results in context.

  • Module 3: TEST OF HYPOTHESIS AND REGRESSION ANALYSIS

    Unit 11: Multiple Regression

    Multiple Regression involves understanding of several variables and their relationships, requiring strong analytical skills.

A suggested way through it

Suggested

13 weeks, about 45 hours in total. Yours will differ.

  1. Week 1Module 1: BASIC SAMPLING AND SURVEY

    • Unit 1: Sampling Survey and Sampling Distribution · 3 hours

      Define population and sample.. Differentiate between probability and non-probability sampling.. Discuss parameter estimation..

  2. Week 2Module 1: BASIC SAMPLING AND SURVEY

    • Unit 2: Sampling Distribution of the Mean · 3 hours

      Calculate sampling distribution of sample mean.. Explain the properties of sample distribution.. Solve problems related to the sampling distribution of the mean..

  3. Week 3Module 1: BASIC SAMPLING AND SURVEY

    • Unit 3: Sampling Distribution of Difference of Two Means and Sum · 3 hours

      Calculate the sampling distribution of the difference of two means.. Calculate the sampling distribution of the sum of two means.. Apply these concepts to practical problems..

  4. Week 4Module 1: BASIC SAMPLING AND SURVEY

    • Unit 4: Sampling Distribution of Proportion · 3 hours

      Calculate sampling distribution of proportion.. Calculate standard error.. Apply sampling distribution of proportion to real-world scenarios..

  5. Week 5Module 2: ESTIMATION AND STATISTICAL TEST OF SIGNIFICANCE

    • Unit 5: Estimation: Point and Interval Estimation · 3 hours

      Differentiate between point estimation and interval estimation.. Calculate point estimates.. Calculate interval estimates..

  6. Week 6Module 2: ESTIMATION AND STATISTICAL TEST OF SIGNIFICANCE

    • Unit 6: Z-test and T-test · 3 hours

      Apply Z-test to test hypotheses.. Apply T-test to test hypotheses.. Compare and contrast Z-test and T-test..

  7. Week 7Module 2: ESTIMATION AND STATISTICAL TEST OF SIGNIFICANCE

    • Unit 7: ANOVA/F-test · 3 hours

      Conduct ANOVA tests.. Conduct F-tests.. Interpret ANOVA and F-test results..

  8. Week 8Module 2: ESTIMATION AND STATISTICAL TEST OF SIGNIFICANCE

    • Unit 8: Chi-Square · 3 hours

      Apply Chi-Square tests.. Interpret Chi-Square test results.. Understand the applications of Chi-Square analysis..

  9. Week 9Module 3: TEST OF HYPOTHESIS AND REGRESSION ANALYSIS

    • Unit 9: Hypothesis Testing · 3 hours

      Formulate null and alternative hypotheses.. Conduct hypothesis testing.. Interpret the results of hypothesis tests..

  10. Week 10Module 3: TEST OF HYPOTHESIS AND REGRESSION ANALYSIS

    • Unit 10: Simple Regression · 3 hours

      Perform simple regression analysis.. Interpret simple regression results.. Understand the assumptions of simple regression..

  11. Week 11Module 3: TEST OF HYPOTHESIS AND REGRESSION ANALYSIS

    • Unit 11: Multiple Regression · 6 hours

      Perform multiple regression analysis.. Interpret multiple regression results.. Understand the assumptions of multiple regression..

  12. Week 12Module 3: TEST OF HYPOTHESIS AND REGRESSION ANALYSIS

    • Unit 11: Multiple Regression · 6 hours

      Perform multiple regression analysis.. Interpret multiple regression results.. Understand the assumptions of multiple regression..

  13. Week 13Module 3: TEST OF HYPOTHESIS AND REGRESSION ANALYSIS

    • Unit 12: Time Series · 3 hours

      Analyze time series data.. Identify trends and patterns in time series.. Apply time series models to forecasting..

Preparing for the exam

What to do
  • Review all unit objectives and ensure you can meet them.
  • Practice solving problems from each unit, focusing on application.
  • Create summaries of key concepts and formulas for quick reference.
  • Allocate specific time slots for revision each day in the weeks leading up to the exam.
  • Focus on understanding the assumptions and limitations of each statistical test.
  • Practice interpreting the results of statistical tests in economic contexts.

Questions students ask about this course

What is ECO726 about?

This course introduces students to statistical tools applicable in economic analysis, building upon elementary statistics and economics foundations. It covers basic sampling and survey techniques, including sampling distributions and parameter estimation. Students will learn hypothesis testing, regression analysis, and time series analysis. The course aims to equip students with the ability to apply statistical tools to real-life economic problems and interpret calculated coefficients effectively.

How many units does ECO726 have?

ECO726, Applied Statistics, has 11 units across 3 modules, over 125 pages of course material. You can read it one unit at a time.

How many credit units is ECO726?

ECO726 carries 2 credit units, at 700 level in Social Sciences.

Is ECO726 hard?

ECO726 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical, problem solving and case study work.

How long does ECO726 take to study?

About 45 hours of study, spread across its 11 units.

How is ECO726 assessed?

ECO726 is assessed by assignments, tutor marked assignments and final examination.

What can I do with ECO726?

Economist, Data Analyst, Market Research Analyst, Financial Analyst and Statistician.

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