Carleton University - ECON 2210: Introductory Statistics for Economics

This course is designed to provide students with a strong foundation in basic statistical methods for the study of economics. The course covers a wide range of topics, including data collection, describing data, probability, discrete and continuous probability distributions, sampling distributions, estimating single population parameters, introduction to hypothesis testing, estimation and hypothesis testing for two population parameters, and hypothesis testing for one and two population variances.

✔ Main topics to be covered:

• Data Collection: Focusing on the systematic process of gathering and measuring information on variables of interest, this subject aims to address research questions, test hypotheses, and evaluate outcomes.
• Describing Data: Emphasizing the importance of summarizing and describing data, this area explores methods such as graphical representations, measures of central tendency, and measures of variability.
• Probability: Centered around the basic principles of probability, this subject includes events, sample spaces, and probability rules.
• Discrete Probability Distributions: Delving into probability distributions for discrete random variables, this area examines variables that can assume a finite or countable number of values.
• Continuous Probability Distributions: Investigating probability distributions for continuous random variables, this subject covers variables that can assume an infinite number of values within a specified range.
• Sampling Distributions: The focal point of this area is sampling distributions, which are probability distributions of a statistic obtained from a large number of samples drawn from a population.
• Estimating Single Population Parameters: Concentrating on point and interval estimation of population parameters, this subject covers aspects such as the mean and proportion.
• Hypothesis Testing: This area introduces concepts such as null and alternative hypotheses, test statistics, and p-values.
• Estimation & Hypothesis Testing for Two Population Parameters: Exploring methods for estimating and testing hypotheses about differences between two population parameters, this subject covers means, proportions, and variances.
• Hypothesis Testing for One & Two Population Variances: Investigating hypothesis testing for variances in one and two populations, this area also examines tests for independence and correlation.