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So, test day is here...
You’ve made it. After all the studying, practice problems, late nights, and formula drills, it’s time to show what you’ve got on the AP Statistics exam.
Here’s a quick Test Day guide, so you’re calm, confident, and ready to crush the AP Stats Exam!
📅 The Night Before 📅
✅ Get 8+ hours of sleep.
✅ Pack your bag with all test essentials.
✅ Charge your calculator fully.
✅ Light review only — focus on formulas, key concepts, and calming your nerves.
🧠 Mental Game Tips 🧠
🎯 Pace yourself: Don’t rush, but don’t get stuck too long on one problem.
🧘 Stay calm: If something’s confusing, skip and come back.
⏱️ Use your time wisely: Leave time to check free responses.
✏️ Show your work: Especially for free-response — even partial steps can earn points!
🧳 What to Bring 🧳
✅ Required
Student ID or other photo ID
#2 Pencils (at least 2, sharpened, non-mechanical) – for multiple-choice.
Black or blue pens – for the free-response section.
Calculator:
Graphing calculator with statistical capabilities (TI-84, TI-83, etc.)
Make sure it’s fully charged or has fresh batteries.
Backup calculator or batteries if you have one.
✅ Optional/Recommended
Watch (no smartwatches) to track time
Water bottle & small snack (for break time)
Sweater/jacket – testing rooms can be cold
🚫 What NOT to Bring 🚫
❌ Phones, smartwatches, or fitness trackers (leave them off and in your bag)
❌ Notes or formula sheets – not allowed (formula sheets will be provided)
❌ Mechanical pencils
❌ Books or review materials
❌ Bluetooth headphones or electronic devices
🔋 Calculator Check 🔋
Stat features tested: 1-Var Stats, LinReg, residuals, boxplots, normalcdf, invNorm, etc.
Make sure you know how to:
Enter and edit data in lists
Perform regression and interpret output
Use normalcdf and invNorm
Do significance tests and confidence intervals with calculator shortcuts (if available)
📚 Quick Review Topics (Morning of or Night Before) 📚
- Sampling methods & biases
- Experimental design (control, randomization, replication)
- Describing distributions (center, spread, shape, outliers)
- Normal distribution (z-scores, percentiles)
- Confidence intervals (interpretation, conditions)
Hypothesis tests:
- Proportions, means, difference of means/proportions
- Type I & Type II Errors, power
- Chi-square tests (GOF, independence, homogeneity)
- Linear regression (residuals, r², interpreting slope/y-int)
- Random variables & expected value/SD
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