Summary and Descriptive Statisticsthere is often the requirement to evaluate descriptive statistics for data within the organization or for health care information. Every year the National Cancer Institute collects and publishes data based on patient demographics. Understanding differences between the groups based upon the collected data often informs health care professionals towards research, treatment options, or patient education.Using the data on the "National Cancer Institute Data" Excel spreadsheet, calculate the descriptive statistics indicated below for each of the Race/Ethnicity groups. Refer to your textbook and the Topic Materials, as needed, for assistance in with creating Excel formulas.Provide the following descriptive statistics:Measures of Central Tendency: Mean, Median, and ModeMeasures of Variation: Variance, Standard Deviation, and Range (a formula is not needed for Range).Once the data is calculated, provide a 150-250 word analysis of the descriptive statistics on the spreadsheet. This should include differences and health outcomes between groups.APA style is not required, but solid academic writing is expected.This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

This is an exercise accompanying a very basic course, Reasoning and Argumentation. This is an assignment of deductive logic. There are only two questions here, which are more likely basic knowledge. I only have one request, please provide a detailed quality answer as much as you can. Please show your bids kindly if are good at it.

Context - A Real Court CaseIn the early 1970s, a young man challenged an Oklahoma state law that prohibited the sale of 3.2% beer to males under age 21 but allowed its sale to females in the same age group. The case (Craig v. Boren, 429 U.S. 190, 1976) was ultimately heard by the U.S. Supreme Court. The state of Oklahoma argued that the law improved traffic safety. One of the three main pieces of data presented to the court was the result of a “random roadside survey.” This survey gathered information on gender and whether or not the driver had been drinking alcohol in the previous 2 hours. A total of 619 drivers under 21 years of age were included in the survey.PromptA test of independence may be appropriate if we are examining the relationship between two categorical variables in one population. For this situation what is the population? What is the explanatory variable? What is the response variable?What are the hypotheses for the Test of Independence? State hypotheses with reference to the context of the scenario.The spreadsheet of the data looked like this: Roadside survey dataDriverGenderAlcohol in lasttwo hours?Driver 1MYesDriver 2FNoDriver 3FYes.........Driver 619MNo We will not use the raw data. Instead we will use the summarized data shown in the table below. Roadside survey summaryDrank alcohol in last 2 hours?YesNoTotals Male77404481 Female16122138 Totals93526619Use StatCrunch to find expected counts, the Chi-square test statistic and the P-value. (directions) Copy and paste your StatCrunch table into your post. How many males in the sample are expected to answer yes to question about alcohol consumption in the last two hours? Show how to calculate this expected count and explain what it means relative to the hypotheses.Explain how we know that this data meets the conditions for use of a chi-square distribution.State a conclusion at a 5% level of significance. Do you think that the data supports the Oklahoma law that forbids sale of 3.2% beer to males and permits it to females?