Nonparametric Statistics Notes
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1 Nonparametric Statistics Notes Chapter 3: Some Tests Based on the Binomial Distribution Jesse Crawford Department of Mathematics Tarleton State University (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 1 / 29
2 Quantiles Definition Let X be a random variable and 0 p 1. x p is the quantile of order p of X if P(X < x p ) p, and P(X > x p ) 1 p. If more than one number satisfies these conditions, let x p be the midpoint of the interval of numbers satisfying these conditions. Also called the (100p)th percentile. Notation The pth quantile for the N(0, 1) distribution is z p, so P(Z < z p ) = p, and P(Z > z p ) = 1 p. (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 2 / 29
3 Outline 1 Section 3.1: The Binomial Test and Estimation of p 2 Section 3.2: The Quantile Test and Estimation of x p 3 Section 3.4: The Sign Test 4 Section 3.5: Some Variations on the Sign Test (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 3 / 29
4 The Binomial Test Example A machine manufactures parts. p = probability that a part is defective Assume parts are statistically independent. Take a sample of n = 10 parts. Sample contains 4 defective parts. Testing problem: H 0 : p 0.05 vs. H 1 : p > Test statistic T Null distribution of T Decision rule/critical region p-value Power Confidence intervals (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 4 / 29
5 The Binomial Test Data and Assumptions n statistically independent trials Each trial results in class 1 or class 2 p = P(class 1) for a single trial O 1 = number of observations in class 1 Hypothesis Tests H 0 : p = p vs. H 1 : p p H 0 : p p vs. H 1 : p < p H 0 : p p vs. H 1 : p > p (Two-tailed) (Lower-tailed) (Upper-tailed) Test Statistic and Null Distribution Test statistic: T = O 1 Null distribution: T binomial(n, p ) (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 5 / 29
6 Upper-Tailed Binomial Test H 0 : p p vs. H 1 : p > p Test statistic: T = O 1 Null distribution: T binomial(n, p ) Decision rule: Choose t such that P(T t p = p ) 1 α, (Use Table A3 or a normal approximation) Reject H0 if T > t Critical region: [T > t] (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 6 / 29
7 binomial(n = 10, p = 0.05) Significance level = P(T > 2 p = 0.05) = = (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 7 / 29
8 Upper-Tailed Binomial Test H 0 : p p vs. H 1 : p > p Test statistic: T = O 1 Null distribution: T binomial(n, p ) Decision rule: Choose t such that P(T t p = p ) 1 α, (Use Table A3 or a normal approximation) Reject H 0 if T > t Critical region: [T > t] Given T = t obs, the p-value is P(T t obs p = p ). (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 8 / 29
9 binomial(n = 10, p = 0.05) p-value = P(T 4 p = 0.05) = = (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 9 / 29
10 Upper-Tailed Binomial Test H 0 : p p vs. H 1 : p > p Test statistic: T = O 1 Null distribution: T binomial(n, p ) Decision rule: Choose t such that P(T t p = p ) 1 α, (Use Table A3 or a normal approximation) Reject H 0 if T > t Critical region: [T > t] Given T = t obs, the p-value is P(T t obs p = p ). For any value of p, the power is P(T > t p) (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 10 / 29
11 binomial(n = 10, p = 0.3) Power = P(T > 2 p = 0.3) = = (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 11 / 29
12 binomial(n = 10, p = 0.95) Power = P(T > 2 p = 0.95) = = (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 12 / 29
13 Example Normally, at least 50% of men undergoing a prostate cancer operation experience a certain side effect. New method for performing operation. Sample of 19 men. 3 experienced side effect. Is there statistically significant evidence that the new method has a lower chance of producing the side effect? (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 13 / 29
14 Lower-Tailed Binomial Test H 0 : p p vs. H 1 : p < p Test statistic: T = O 1 Null distribution: T binomial(n, p ) Decision rule: Choose t such that P(T t p = p ) α, (Use Table A3 or a normal approximation) Reject H0 if T t Critical region: [T t] Given T = t obs, the p-value is P(T t obs p = p ). For any value of p, the power is P(T t p) (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 14 / 29
15 Normal Approximation for Binomial Quantiles Suppose X binomial(n, p). If np 5, and n(1 p) 5, then the qth quantile of X is approximately x q np + z q np(1 p) Normal Approximation for p-values ( P(T t obs p = p ) P P(T t obs p = p ) P ( Z t obs np np (1 p ) Z t obs np 0.5 np (1 p ) ) ) (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 15 / 29
16 Two-Tailed Binomial Test H 0 : p = p vs. H 1 : p p Test statistic: T = O 1 Null distribution: T binomial(n, p ) Decision rule: Choose t1 and t 2 such that P(T t 1 p = p ) α/2 P(T t 2 p = p ) 1 α/2 (Use Table A3 or a normal approximation) Reject H 0 if T t 1 or T > t 2 Critical region: [T t 1 or T > t 2 ] The p-value is 2 min[p(t t obs p ), P(T t obs p )]. For any value of p, the power is P(T t 1 or T > t 2 p) (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 16 / 29
17 Binomial Distribution: Confidence Interval for p Suppose Y binomial(n, p) If n 30 and the confidence level is 0.9, 0.95, or 0.99, the exact Clopper Pearson confidence interval is given in table A4. If np 5 and n(1 p) 5, we can use the normal approximation Y Y (n Y ) n ± z 1 α/2 n 3 Note that this is the same as where ˆp = Y /n. ˆp(1 ˆp) ˆp ± z 1 α/2, n (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 17 / 29
18 Outline 1 Section 3.1: The Binomial Test and Estimation of p 2 Section 3.2: The Quantile Test and Estimation of x p 3 Section 3.4: The Sign Test 4 Section 3.5: Some Variations on the Sign Test (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 18 / 29
19 The Quantile Test Example Random sample of standardized test scores: Test whether the 75th percentile of the scores in the population is equal to 193. H 0 : x 0.75 = 193 vs. H 1 : x (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 19 / 29
20 Two-Tailed Quantile Test Assumption: X 1,..., X p is a random sample (they are IID) from a distribution whose measurement scale is at least ordinal. H 0 : x p = x vs. H 1 : x p x Test statistics: T 1 = # of X i s less than or equal to x T 2 = # of X i s less than x Null distributions for both T 1 and T 2 : binomial(n, p ) Decision rule: Let Y represent a binomial(n, p ) random variable. Choose t 1 and t 2 such that P(Y t 1 ) α/2 P(Y t 2 ) 1 α/2 (Use Table A3 or a normal approximation) Reject H0 if T 1 t 1 or T 2 > t 2. Critical region: [T 1 t 1 or T 2 > t 2 ] (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 20 / 29
21 Example Random sample of standardized test scores: H 0 : x 0.75 = 193 vs. H 1 : x T 1 = # of X i s less than or equal to x T 2 = # of X i s less than x Choose t 1 and t 2 such that P(Y t 1 ) α/2 P(Y t 2 ) 1 α/2 Reject H 0 if T 1 t 1 or T 2 > t 2 (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 21 / 29
22 Lower-Tailed Quantile Test H 0 : x p x vs. H 1 : x p > x Test statistic: T 1 = # of X i s less than or equal to x Null distribution: T 1 binomial(n, p ) Decision rule: Let Y represent a binomial(n, p ) random variable. Choose t 1 such that P(Y t 1 ) α (Use Table A3 or a normal approximation) Reject H0 if T 1 t 1 Critical region: [T 1 t 1 ] (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 22 / 29
23 Upper-Tailed Quantile Test H 0 : x p x vs. H 1 : x p < x Test statistic: T2 = # of X i s less than x Null distribution: T 2 binomial(n, p ) Decision rule: Let Y represent a binomial(n, p ) random variable. Choose t 2 such that P(Y t 2 ) 1 α (Use Table A3 or a normal approximation) Reject H 0 if T 2 > t 2 Critical region: [T 2 > t 2 ] (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 23 / 29
24 Outline 1 Section 3.1: The Binomial Test and Estimation of p 2 Section 3.2: The Quantile Test and Estimation of x p 3 Section 3.4: The Sign Test 4 Section 3.5: Some Variations on the Sign Test (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 24 / 29
25 The Sign Test 81 ties H 0 : P(+) = P( ) vs. H 1 : P(+) P( ) Example 100 people tested two products. 15 people preferred product A to product B 4 people preferred product B to product A 81 people had no preference Summary: 15 + s 4 s (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 25 / 29
26 Two-Tailed Sign Test H 0 : P(+) = P( ) vs. H 1 : P(+) P( ) n = [# of + s] + [# of s] Test statistic: T = [# of + s] Null distribution: T binomial(n, 1 2 ) Decision rule: Let Y represent a binomial(n, 1 2 ) random variable. Choose t 1 and t 2 such that P(Y t 1 ) α/2 P(Y t 2 ) 1 α/2 (Use Table A3 or a normal approximation) Reject H 0 if T t 1 or T > t 2 Critical region: [T t 1 or T > t 2 ] (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 26 / 29
27 Outline 1 Section 3.1: The Binomial Test and Estimation of p 2 Section 3.2: The Quantile Test and Estimation of x p 3 Section 3.4: The Sign Test 4 Section 3.5: Some Variations on the Sign Test (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 27 / 29
28 The McNemar Test for Significance of Changes Example Presidential Debate Summary of voter intentions Test whether a statistically significant difference in voter intentions exists before and after the debate. (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 28 / 29
29 Cox-Stuart Test for Trend Example Precipitation readings for 19 years: Test whether a trend in this data exists. (Tarleton State University) Ch 3: Tests Based on the Binomial Dist. 29 / 29
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