Transcript Ch8-6
Section 8.6 Testing a claim about a standard deviation Objective For a population with standard deviation σ, use a sample too test a claim about the standard deviation. Tests of a standard deviation use the c2-distribution 1 Notation 2 Notation 3 Requirements (1) The sample is a simple random sample (2) The population is normally distributed Very strict condition!!! 4 Test Statistic Denoted c2 (as in c2-score) since the test uses the c2 -distribution. n Sample size s Sample standard deviation σ0 Claimed standard deviation 5 Critical Values Right-tailed test “>“ Needs one critical value (right tail) Use StatCrunch: Chi-Squared Calculator 6 Critical Values Left-tailed test “<” Needs one critical value (left tail) Use StatCrunch: Chi-Squared Calculator 7 Critical Values Two-tailed test “≠“ Needs two critical values (right and left tail) Use StatCrunch: Chi-Squared Calculator 8 Example 1 Problem 14, pg 449 Statisics Test Scores Tests scores in the author’s previous statistic classes have followed a normal distribution with a standard deviation equal to 14.1. His current class has 27 tests scores with a standard deviation of 9.3. Use a 0.01 significance level to test the claim that this class has less variation than the past classes. What we know: σ0 = 14.1 n = 27 Claim: σ < 14.1 s = 9.3 using α = 0.01 Note: Test conditions are satisfied since population is normally distributed 9 Example 1 Using Critical Regions What we know: σ0 = 14.1 n = 27 s = 9.3 Claim: σ < 14.1 using α = 0.01 H0 : σ = 14.1 H1 : σ < 14.1 Left-tailed Test statistic: c2L = 12.20 Critical value: (df = 26) c2 = 11.31 c2 in critical region Initial Conclusion: Since c2 in critical region, Reject H0 Final Conclusion: Accept the claim that the new class has less variance than the past classes 10 Calculating P-value for a Variance Stat → Variance → One sample → with summary 11 Calculating P-value for a Variance Enter the Sample variance (s2) Sample size (n) NOTE: Must use Variance s2 = 9.32 = 86.49 Then hit Next 12 Calculating P-value for a Variance Select Enter the Select Hypothesis Test Null:variance (σ02) Alternative (“<“, “>”, or “≠”) σ02 = 14.12 = 198.81 Then hit Calculate 13 Calculating P-value for a Variance The resulting table shows both the test statistic (c2) and the P-value Test statistic (c2) P-value 14 Example 1 Using Critical Regions What we know: H0 : σ = 14.1 H1 : σ < 14.1 Using StatCrunch s2 = 86.49 σ02 = 198.81 σ0 = 14.1 n = 27 s = 9.3 Claim: σ < 14.1 using α = 0.01 Stat → Variance→ One sample → With summary Sample variance: Sample size: 86.49 27 ● Hypothesis Test Null: proportion= Alternative 198.81 < P-value = 0.0056 Initial Conclusion: Since P-value < α (α = 0.01), Reject H0 Final Conclusion: Accept the claim that the new class has less variance than the past classes We are 99.44% confident the claim holds 15 Example 2 Problem 17, pg 449 BMI for Miss America Listed below are body mass indexes (BMI) for recent Miss America winners. In the 1920s and 1930s, distribution of the BMIs formed a normal distribution with a standard deviation of 1.34. Use a 0.01 significance level to test the claim that recent Miss America winners appear to have variation that is different from that of the 1920s and 1930s. 19.5 20.3 19.6 20.2 17.8 17.9 19.1 18.8 17.6 16.8 Using StatCrunch: s = 1.1862172 What we know: σ0 = 1.34 n = 10 Claim: σ ≠ 1.34 s = 1.186 using α = 0.01 Note: Test conditions are satisfied since population is normally distributed 16 Example 2 Using Critical Regions What we know: σ0 = 1.34 n = 10 Claim: σ ≠ 1.34 s = 1.186 using α = 0.01 H0 : σ = 1.34 H1 : σ ≠ 1.34 two-tailed 0.005 Test statistic: c2L = 2.088 Critical values: (df = 26) c2R = 26.67 c2 = 7.053 c2 not in critical region Initial Conclusion: Since c2 not in critical region, Accept H0 Final Conclusion: Reject the claim recent winners have a different variations than in the 20s and 30s Since H0 accepted, the observed significance isn’t useful. 17 Example 2 Using P-value What we know: σ0 = 1.34 n = 10 Claim: σ ≠ 1.34 H0 : σ2 = 1.796 H1 : σ2 < 1.796 Using StatCrunch s2 = 1.407 σ02 = 1.796 s = 1.186 using α = 0.01 Stat → Variation → One sample → With summary Sample variance: Sample size: 1.407 10 ● Hypothesis Test Null: proportion= 1.796 Alternative < P-value = 0.509 Initial Conclusion: Since P-value ≥ α (α = 0.01), Accept H0 Final Conclusion: Reject the claim recent winners have a different variations than in the 20s and 30s Since H0 accepted, the observed significance isn’t useful. 18