Week9-Data Analysis—Small Group Discussion As a nurse engaged in evidence-based practice, it is important to recognize how statistics and other data analysis tools are used to generate and assess evidence. Most nurses need only a foundational understanding of statistical tools and terminology to understand the majority of research studies. As a nurse, you should be able to recognize the most commonly used statistical tests, how and when they are used, and how significance is determined.In this Discussion, you examine different types of statistics and statistical tests, when and why these particular tests would be selected for use, and, most importantly, what the results indicate. To this end, you will be assigned to a group by Day 1 of this week. Each group will be assigned one of the five chapters listed in this week’s Learning Resources and will develop a study sheet on their chapter that will be shared with the other groups.To prepare:• Review the information in your assigned chapter.• As a group, develop a 1-page study sheet that includes the following:• The key concepts of the chapter: Focus on the basic concepts that are important for nurses to understand as they review research studies.• A description of the statistical methods covered in the chapter, what they measure, and under what circumstances they are used. Identify examples of how the statistical methods have been used in research studies.• An explanation of the key statistical tests and how they measure significance (if applicable)• Please give me an answer based on this question from chapter 17Chapter 17, “Inferential Statistics”Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Wolters Kluwer.This chapter focuses on inferential statistics, which are based on the laws of probability. It introduces sampling distributions, estimates of parameters, and levels of significance. In addition, the chapter provides an overview of some of the most commonly used inferential statistical tests, including t-tests, analysis of variance (ANOVA), and chi-square tests. Finally, the process of testing correlations is examined.