
Enrol Here
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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
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Develop a solid grounding in core statistical concepts essential for econometrics.
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Acquire skills in data collection, analysis, presentation, and interpretation.
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Explore descriptive statistics, probability theory, estimation, and hypothesis testing.
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Gain practical experience using Stata for statistical analysis.
Key Skills Acquired
By the end of the course, students will be able to:
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Summarise and analyse data using measures of location, variability, distribution, and association.
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Understand and apply key probability concepts including conditional probability and Bayes’ theorem.
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Employ sampling techniques and interpret sampling distributions.
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Carry out interval estimation and hypothesis testing on real-world data.
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Use Stata to apply statistical methods effectively.
Learning Outcomes
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Statistical Literacy: Interpret and critically evaluate statistical information in real-world contexts.
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Data Analysis Skills: Collect, organise, and analyse data using appropriate techniques.
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Statistical Inference: Understand confidence intervals, p-values, and hypothesis testing to draw valid conclusions.
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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
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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