EC 285 - Tue Sep 15, 2026 - Lecture 02

Before class

• Read Chapter 2

In class

• Science of statistics: Collection, analysis, interpretation, and presentation of data
• Descriptive statistics deals with organizing and summarizing data
  • Graphing
  • Using numbers (e.g. finding an average)
• Inferential statistics deals with forming conclusions from "good data
  • We use probability to determine how confident we can be that our conclusions are correct

Probability

• A mathematical tool used to study randomness
• Deals with chance of something happening (e.g. what is the likelihood of getting heads four times in a row on a coin flip)
  • We want to look further - what happens after 4000 tosses? It should be close to 50% heads and 50% tails

Key Terms

• Population: Collection of persons, things, or objects
  • In order to study the population, we select a sample
• Sample: we select a portion of the larger population and study that portion to gain information about the population
  • Sampling is effective because studying a population takes LOTS of time, money, and energy
• Statistic: A number that represents a property of a sample
• Paramter: A numerical characteristic of a population estimated by a statistic

Real example: If we consider one math class to be a sample of the population, then the average grade of each student in that one math class is a statistic and the average grade per student over al math classes is a parameter.

• How do we know if our statistic accurately estimates a parameter? We look for a sample that is representative.
• Variables are usually denoted capitals
• A datum is a single value of all the data
  • Actual number values

1.f 2.g 3.e 4.d 5.b 6.c

After class

• Tutorial problems (graded: 0.5 submit / 1 correct)