Introducción a la Estadística con Aplicaciones en Stata

Introducción a la Estadística con Aplicaciones en Stata

Este curso proporciona una comprensión fundamental de la estadística esencial para estudiar econometría. Cubre la recolección de datos, el análisis, la probabilidad, las pruebas de hipótesis y el uso de software estadístico para aplicaciones del mundo real.

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360,00 €
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2 Days
Online via Teams
Stata

Overview

This intensive two-day course provides a foundational understanding of statistics with direct applications in Stata, preparing students for more advanced study in econometrics. The course balances theoretical knowledge with practical, hands-on data analysis skills.

Course Aims & Objectives

  • Develop a solid grounding in core statistical concepts essential for econometrics.

  • Acquire skills in data collection, analysis, presentation, and interpretation.

  • Explore descriptive statistics, probability theory, estimation, and hypothesis testing.

  • Gain practical experience using Stata for statistical analysis.

Key Skills Acquired

By the end of the course, students will be able to:

  • Summarise and analyse data using measures of location, variability, distribution, and association.

  • Understand and apply key probability concepts including conditional probability and Bayes’ theorem.

  • Employ sampling techniques and interpret sampling distributions.

  • Carry out interval estimation and hypothesis testing on real-world data.

  • Use Stata to apply statistical methods effectively.

Learning Outcomes

  • Statistical Literacy: Interpret and critically evaluate statistical information in real-world contexts.

  • Data Analysis Skills: Collect, organise, and analyse data using appropriate techniques.

  • Statistical Inference: Understand confidence intervals, p-values, and hypothesis testing to draw valid conclusions.

  • Applied Problem-Solving: Apply statistical reasoning to solve practical problems and make data-informed decisions.

Course Structure

Delivery Format: Two-Day Intensive

  • Lectures: 4 sessions (2 hours each)
  • Tutorials/Workshops: 2 sessions (2 hours each)

Agenda

Day 1:

Session 1: Descriptive Statistics and Probability, Part 1
  • Measures of Location: Mean, Median, Mode, Percentiles
  • Measures of Variability: Range, Variance, Standard Deviation
  • Distribution Shape: Z-scores, Chebyshev’s Theorem
Session 2: Descriptive Statistics and Probability, Part 2
  • Measures of Association: Covariance, Correlation
  • Probability Theory: Random Experiments, Events, Conditional Probability
  • Bayes’ Theorem
  • Introduction to Discrete and Continuous Distributions
Tutorial 1
  • Practical Applications in Stata
Day 2:

Session 3: Sampling, Estimation, and Hypothesis Testing, Part 1
  • Sampling Methods and Estimators
  • Central Limit Theorem
  • Properties of Estimators: Bias, Efficiency, Consistency
Session 4: Sampling, Estimation, and Hypothesis Testing, Part 2
  • Confidence Intervals for Means, Proportions, and Variance
  • Hypothesis Testing: Null and Alternative Hypotheses, Type I and II Errors, Power
  • Inference on Two Means, Proportions, and Variances
Tutorial 2
  • Applied Hypothesis Testing in Stata

Prerequisites

There are no specific prerequisites to attend the course but we reccomend viewing the below pre-course reading

 Reccomended Reading

 

Main Text 

  • Anderson, Sweeney, Williams, Camm and Cochran, (2019) “Statistics for Business & Economics”, Cengage 

 

Students may also find the following useful as further reading. 

  • Barrow, M. (2017) Statistics for economics, accounting, and business studies. Pearson. 
  • Newbold, P., W. Carlson and B. Thorne (2013) Statistics for Business and Economics. Pearson Education Edition. 
  • J.M. Wooldridge (2019) Introductory Econometrics: A Modern Approach, CENGAGE Learning Custom Publishing; 7th edition. 

Course Timetable

Subject to minor changes
Day Morning Session Afternoon Session (including Tutorial)
Day One 10am-12pm (London time) 1pm-5pm (London time)
Day Two 10am-12pm (London time) 1pm-5pm (London time)

Terms

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course.
  • Payment of course fees required prior to the course start date.
  • Registration closes 5-calendar days prior to the start of the course.
  • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
  • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
  • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

 

The number of delegates is restricted. Please register early to guarantee your place.

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