Welcome to Intro to Statistics!

Hello everyone! In today's class, we took our first steps into the fascinating world of statistics. We discussed what statistics is all about and how it's used in various aspects of our lives. It's more than just numbers; it's about understanding the information around us. Let's dive into some of the key terms we covered:

  • Data: Data consist of information coming from observations, counts, measurements, or responses. Think of it as the raw material we use in statistics.
  • Statistics: Statistics is the science of collecting, organizing, analyzing, and interpreting data in order to make decisions. It's the toolbox we use to make sense of data.
  • Population: A population is the collection of all outcomes, responses, measurements, or counts that are of interest. It's the entire group we want to know something about.
  • Sample: A sample is a subset, or part, of a population. It's a smaller, manageable group that we collect data from.
  • Parameter: A parameter is a numerical description of a population characteristic. It's a value that describes something about the entire population (e.g., the average age of all students in a school).
  • Statistic: A statistic is a numerical description of a sample characteristic. It's a value that describes something about the sample (e.g., the average age of students in a sample of students from the school).

Remember the mnemonic device: population parameter and sample statistic!

Branches of Statistics

Statistics can be broadly divided into two main branches:

  • Descriptive Statistics: This branch involves the organization, summarization, and display of data. It's all about describing the data we have.
  • Inferential Statistics: This branch involves using a sample to draw conclusions about a population. We use data from a sample to make inferences or predictions about the larger population. A basic tool in the study of inferential statistics is probability.

Example

Imagine we want to know the average height of all students at State University. It's impossible to measure every single student, so instead, we take a random sample of 100 students and find their average height. The average height of those 100 students is a statistic. If we somehow knew the average height of *every* student at State University, that would be a parameter.

Homework

For tonight's homework, please do the following:

  1. Read page 5 of the textbook.
  2. Define Descriptive Statistics in your own words.
  3. Define Inferential Statistics in your own words.
  4. Find three real-world examples of how statistics is used in everyday life. Think about news articles, advertisements, or decisions you make based on data.

I am looking forward to exploring more about descriptive and inferential statistics in our next class!