1 / 12

χ 2 Distribution

χ 2 Distribution. Given n random independent variants (x 1 , x 2 , …, x n ), their distribution will be a normal distribution. If these variants are all squared (x 1 2 , x 2 2 , …, x n 2 ), will they still fall into a normal distribution?. χ 2 Distribution. χ 2 Distribution.

adrina
Télécharger la présentation

χ 2 Distribution

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. χ2 Distribution • Given n random independent variants (x1, x2, …, xn), their distribution will be a normal distribution. • If these variants are all squared (x12, x22, …, xn2), will they still fall into a normal distribution?

  2. χ2 Distribution

  3. χ2Distribution • χ2=Σ(x-μ)2/σ2 = ns2/σ2 • df = n-1 • critical value: χα(n)2 • e.g. χ0.05(12)2=21.00

  4. χ2 Distribution • Common usage:• Inference on a single normal variance.• Chi-squared Tests:   - test for independence,   - homogenity,   - goodness of fit.

  5. Case • 教材试用:中等水平的学校 • 人数:n=101 • 标准差:s=15.7 • 全区标准差: σ=12.1 • 试点平均分=全区平均分 • α= 0.05 • 教材是否适用?

  6. Case • Null hypothesis: H0: s= σ • χ2=ns2/σ2 =101*15.72/12.12 =170.039 χ2 α/2=129.56 χ 2 >χ2 α/2 Conclusion: suitable for the advanced students, but not for the intermediate.

  7. F distribution • The F distribution is the distribution of the ratio of two estimates of variance. It is used to compute probability values in the analysis of variance. • The F distribution has two parameters: • degrees of freedom numerator (dfn, dfb) • degrees of freedom denominator (dfd, dfw)

  8. F distribution

  9. F distribution • F=S2(n1-1)/S2(n2-1) • S2(n1-1):the first variance with the degree of freedom of n1-1 • S2(n2-1): the second variance with the degree of freedom of n2-1

  10. F distribution • Example Sample 1: standard deviation of 19.17, n1=15 Sample 2: standard deviation of 54.19 n2=15 Variance of Sample 1: 19.172=367.49 Variance of Sample 2: 54.192=2936.56 F=367.49/2936.56=7.99 F(14,14, α=0.05)=2.48

  11. Case • 两个班使用不同的教学方法,甲班31人,乙班25人。期末两个班考试成绩方差分别为62,92。方差是否有显著差别?

  12. Case • H0: σ12=σ22 • F=S2(n1-1)/S2(n2-1) = S2(大)/S2(小) = 92 /62 =81/36 =2.25 F(24,30, α=0.05/2)=2.14 F> F(24,30, α=0.05/2) H0 rejected There is significant difference.

More Related