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Statistical Reasoning - Absolute-Beginner Level: core concept mastery Statistical Reasoning ABSOLUTE BEGINNER

This skill primer 🌟 worksheet focuses on Statistical Reasoning - a key topic in Strong Weak Arguments. You'll solve 20 absolute-beginner-level problems (Worksheet 1 of 10). The primary focus is on core concept mastery. Master statistical reasoning problems, statistical reasoning reasoning questions, and statistical reasoning practice through systematic practice.

📝 Worksheet 1 of 10 • 20 questions • ⏱️ Estimated time: 20 minutes • 🎯 Absolute Beginner level

What you'll learn in this worksheet:
Your progress through Statistical Reasoning
Worksheet 1 of 10 (0% complete)

Question 1

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 2

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 3

What is the primary weakness in this argument?
Small, non-random sample (n=5) cannot support population-wide conclusions regardless of unanimity.

Question 4

What is the primary weakness in this argument?
Small, non-random sample (n=5) cannot support population-wide conclusions regardless of unanimity.

Question 5

What is the primary weakness in this argument?
Small, non-random sample (n=5) cannot support population-wide conclusions regardless of unanimity.

Question 6

What is the primary weakness in this argument?
Small, non-random sample (n=5) cannot support population-wide conclusions regardless of unanimity.

Question 7

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 8

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 9

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 10

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 11

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 12

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 13

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 14

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 15

What is the primary weakness in this argument?
Small, non-random sample (n=5) cannot support population-wide conclusions regardless of unanimity.

Question 16

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 17

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 18

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 19

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.

Question 20

You test positive for a rare disease (1 in 10,000 prevalence). The test is 99% accurate (1% false positive rate). What is the approximate probability you actually have the disease?
With 10,000 people: 1 true case, but 100 false positives (1% of 9,999). So probability = 1/(1+100) ≈ 1%. This tests base rate neglect.
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