🎉 Imagine this: You're a soccer coach. How do you decide which player goes where? Or wonder if players get slower with a ball after a 20-minute run? Let's take this fun journey to understand. 🎉

• 🤔 What is it?
  • A cool way to measure variation.
  • It's the ratio of the standard deviation to the mean (in %).
• 🌟 Why it's shiny
  • Percentages make it easy-peasy for many to grasp.

🌍 Real World Example: Let’s say you test how many push-ups your friends can do. If their average (mean) is 20, but they differ a lot (a high standard deviation), the coefficient will be high. It’s like saying, "Hey, we all average 20 push-ups, but some of us do WAY more or WAY less!"

• Why use t-tests?
  • Want to know if your soccer players run differently after resting vs. after exercising? Here's your tool!
  • Helps to determine if the difference you see (like in the speed of running) is due to some reason (like exercising) or just a fluke.

🌍 Real World Scenario: After 20 mins of exercising, a group of soccer players run with the ball for 60 seconds. Did they cover less distance because of the exercise, or was it just a random thing?

• 🎲 Results & P-Values
  • Found a value called t11 = 1.194. Huh?!
  • This value helps calculate a probability (p-value) which answers: "Is the result because of luck?"
  • Here, p = 0.205 or 20.5% chance it's by luck.
  • Rule of Thumb: If p ≤ 0.05, it's likely NOT just luck. (In our case, it's more than that so... maybe it's just a random result).