A T-Test checks if two averages (means) are really different, or if the difference is just due to random chance.

Find the Averages

You get some sales numbers:

• Region A: 210, 220, 215, 225, 230 → 👉 Average = 220

• Region B: 195, 200, 190, 205, 198 → 👉 Average = 197.6

There’s a difference. But is that difference big enough to matter?

🎯 Step 2: Check How Spread Out the Data Is (Variance)

• Are all sales close to the average? (Low variance)

• Or are they all over the place? (High variance)

More spread = more uncertainty.

🎯 Step 3: Use the T-Test Formula

Now the t-test combines:

• The difference in averages

• The amount of spread (variance)

• How many data points you have

And gives you a T-Value (a number like 2.5 or 5.1).

🎯 Step 4: Convert T-Value to P-Value

The computer or calculator turns the T-Value into a P-Value.

• If p < 0.05 → 🟢 There's a real difference

• If p > 0.05 → 🔴 The difference might be just by chance

🎉 Example Summary

RegionAverage SalesRegion A220Region B197.6

You run the test → p = 0.01 ✅ Since 0.01 < 0.05 → The difference is significant