Slstats

2.Using Insufficient data for making comparisons

📊 “Company Y earns more than Company X!”
Company X profit: Rs. 100,000
Company Y profit: Rs. 150,000
So… does that mean Company X performs worse? 🤔
Not necessarily.
❓ Ask the important question first:
📦 How large is each business?
A small scale company earning Rs. 100,000
vs
a large scale company earning Rs. 150,000
➡️ The smaller company might actually be more efficient and stronger.
⚠️ This is using insufficient data for comparison.
📉 Profit without business volume = incomplete picture
📊 Bigger numbers don’t always mean better performance
⚖️ Fair comparison needs proper context
🚨 Insufficient data = Misuse of statistics
✅ Real analysis looks at scale, volume, efficiency, and costs
❌ Comparing numbers alone can lead to false conclusions
💡 Statistics should inform decisions, not mislead them.
Always ask for the full story behind the numbers.

1. Falsely interpretation of the results of an analysis

📊 A statistic says: “This school has a 66% university entrance rate!” 🎉
Impressive… right? 🤔
Not always.
Ask the missing question:
👥 How many students sat for the exam?
🎓 The reality:
Only 3 students sat for the A/L exam.
✅ 2 got selected to university.
So yes… mathematically,
📈 2 out of 3 = more than 66%
But does this truly mean the school has a high university entrance rate? ❌
⚠️ This is false interpretation of results.
📉 Small numbers give big percentages
📊 Percentages without context mislead conclusions
⚖️ Results need proper explanation, not exaggeration
🚨 False interpretation = Misuse of statistics
✅ Statistics must be read with context and scale
❌ Percentages alone can distort reality
💡 Always look beyond the percentage.
Understanding numbers is more important than admiring them.

Advanced Level

Business Statistics

Medium-(English/Sinhala)

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