can you help with x^2 statistic? As well as P-value and then check the others? **Overview of Preterm Births Analysis by Age Group**Most pregnancies reach full term, but some are preterm (less than 37 weeks). Preterm births are classified as early (less than 34 weeks) and late (34 to 36 weeks). A study analyzed the outcomes of preterm births over one year, categorized by the mother's age. The goal was to determine if the outcomes are independent of age group.**Hypotheses:**1. \( H_0 \): The proportions of early/late preterm births are the same for all age groups.2. \( H_A \): The proportions of early/late preterm births are not the same for all age groups.**Age Group and Preterm Birth Data:**The table summarizes the number of early and late preterm births across different age groups:| Age Group | Early Preterm | Late Preterm ||-----------|---------------|--------------|| Under 20 | 129 | 272 || 20 to 29 | 243 | 604 || 30 to 39 | 162 | 429 || 40 or Over| 19 | 42 |**Statistical Analysis:**1. **Compute the \(\chi^2\) Statistic:** \[ \chi^2 = 2.233 \quad \text{(Rounded to three decimal places as needed.)} \]2. **Find the P-value:** \[ \text{P-value} = 0.526 \quad \text{(Rounded to three decimal places as needed.)} \]**Conclusion:**- The decision involves comparing the P-value to the level of significance, \(\alpha = 0.01\).- **Correct Conclusion (Option B):** - The P-value is greater than or equal to \(\alpha = 0.01\). - This indicates insufficient evidence to reject \( H_0 \), suggesting that age group and outcome are independent.This analysis aids in understanding whether maternal age influences the likelihood of early or late preterm births, which can inform healthcare strategies and interventions.

Solution-: Our aim to find (a) Hypothesis (b) Test statistic=? (c) p-value =? To test is there evidence that the outcomes are not independent of age group? (a) Hypothesis: Here, we want to test H0: Two attribute type of age group (A) and outcomes (B) are independent of each other. Vs H1:Two attribute type of age group (A) and outcomes (B) are not independent of each other. (or They are associated with each other) The given frequencies table are observed frequencies (Oij) Early Preterm Late Preterm Total Under 20 129 272 401 20 to 29 243 604 847 30 to 39 162 429 591 40 or over 19 42 61 Total 553 1347 1900 The corresponding expected frequencies (eij)are obtained using formula eij=(Ai)*(Bj)N for i=1,2,3,4;j=1,2 The given frequencies table are expected frequencies (eij): Early Preterm Late Preterm Under 20 116.7121 284.2879 20 to 29 246.5216 600.4784 30 to 39 172.0121 418.9879 40 or over 17.7542 43.2458 N=∑(Oij)=∑(eij)=1900 Table for Oij2/eij Early Preterm Late Preterm Under 20 142.5816 260.2432 20 to 29 239.5287 607.5422 30 to 39 152.5707 439.2514 40 or over 20.3332 40.7901 From this table we get, ∑i=14∑j=12Oij2eij=1902.8411 The test statistic is χstat2=χ(4-1)*(2-1)2=χ32=∑i=14∑j=12Oij2eij-N =1902.8411-1900 =2.841 ∴χstat2=2.841 p-value:- d.f.=(r-1)*(c-1)=(4-1)*(2-1)=3 p-value=P[χd.f2>χstat2] =P[χ32>2.841] By using MS-Excel Command "=CHIDIST(2.841,3)" =0.417 Here, p-value=0.417>α=0.01 (Level of significance) hence, we fail to reject H0. Option (B) The p-value is greater than or equal to the level of significance, α=0.01. There is insufficient evidence to reject H0 and conclude that age group and outcomes are not independent is correct