do suffolk county new york National Ambient Air Quality Standards (NAAQS) can be found at the EPA’s website. Over the past 50 years the standard annual mean for fine particulate matter PM2.5 has been significantly tightened, starting out at 75 µg/m3 of air in 1971 and now only 12 µg/m3 of air (as of 2012 standards).Create a new tab/sheet in your worksheet and name it “Mod 9”. Copy the following three columns from your other tabs into this new worksheet, making sure to label these columns: Daily Mean PM2.5 Concentration 2018, Daily AQI Values 2003, and Daily AQI Values 2018. Note that the number of rows may differ between 2003 and 2018, but that is okay. Use StatCrunch to find a 90% confidence interval for the column Daily Mean PM2.5 Concentration from your 2018 data. Note the two conditions for a valid confidence interval are met. Insert the StatCrunch results into your Mod 9 worksheet.What is the confidence interval for your 2018 PM2.5 data? Is the 12 µg/m3 of air standard limit contained in your confidence interval? With standards getting stricter over time, it is possible that even if it the current standard is not contained in the confidence interval a future stricter standard might be. What concerns might you have if this were contained in your confidence interval? What can you interpret from this? The textbook noted that confidence intervals may be reported in two different ways. Please give your results in both formats. Which format do you find to be more useful or clearer?Now, utilize Excel's COUNTIF function to find how many days in your data set had a Daily Mean PM2.5 Concentration over 12 µg/m3. Did your area have any days over the standard annual mean for fine particulate matter, and if so how many? Note that the 12 µg/m3 is an annual mean so that over the course of the year the AVERAGE for any given area should be under that value. As an average, one would expect some days to be higher and some days to be lower concentrations, but the overall average for the year should be below this value to meet the EPA's standards.Learn more about the Air Quality Index (AQI) which is calculated for four major air pollutants regulated by the Clean Air Act in the AQI Brochure. Page 3 of this brochure includes a table noting levels of health concerns for various air quality index values. In your Mod 9 worksheet, create a table containing a row for each range of AQI values (as found on page 3 of the brochure) and a column for each of the following: Levels of Health Concerns, # of days 2003, and # of days 2018. Utilize the COUNTIF function in Excel to find the number of days within each range of AQI values on the table, for each year of your data. For example, to find the number of days with AQI in the Moderate Level of Health Concern (AQI 51 to 100), use this command (adapt to reflect the appropriate cells in your data file): =COUNTIF(G2:G477,"<101")-COUNTIF(G2:G477,"<51").Create a single post addressing all of the questions and topics above, making sure to report your results found (use complete and descriptive sentences). Attach your Excel data file (*.xls or *.xlsx) to your discussion post. The Excel file will include not only the data, but also the use of commands and clearly labeled results.In addition to your main post, you are to respond to at least two other students’ main posts. Substantive responses to other students’ main posts might include the following: (1) a detailed comparison of your results to their results including proposing why the results might (or might not) differ between your two regions, or (2) detailed and polite recommendations for improvements should their work be incorrect or not fully meet the assignment's requirements.Grading for this assignment will be based on the Discussion Participation Rubric in the Course Information Tab.

Everything below is what has been given to me as far as rules and resources. Please complete this project. If you have any questions feel free to contact me. Math 140 Project: Exploring relationships between two variablesIn this project, you will search two quantitative variables that may have a linear correlation. You will describe and analyze the relationship between the variables the way it is explained in Chapter 4 (4.1-4.2). You will, then, create a written report including all 4 parts below and turn in by the stated due date according to the guidelines provided in this paper. Required components:1. Understand the Problema) Search for two quantitative variables that may have a linear correlation from the internet,in Canvas or any other media. You may also get the data by surveying 15-20 people.Possible websites to look for data:You may obtain the data in StatCrunch.com: Click explore and click Data.http://www.city-data.com/ for demographic information about citieshttp://www.cde.ca.gov/ta/ac/ap/ for academic performance index.http://graphics.latimes.com/responsivemap-pollutio... for pollution burdens.Website where you found the data: b) Use your intuition and/or experience to predict and write down the descriptions of the possible relationship: Form, Direction, Strength, and outlier, etc. c) Develop a question that address a possible linear correlation between two variables. State the question(s):Identify two variables from the data that are relevant to answer the questions: 2. Analyze the paired Dataa) What is the likely explanatory variable in the paired data?b) Draw a scatter plot of the data. Does the graph show a linear relationship between the variables? Comment on the direction and strength appeared on the scatter diagram.c) Compute the linear correlation coefficient between the two variables and interpret the meaning specifically for your data. d) Find the equation of the least-squares regression line.e) Interpret the slope and y-intercept, if appropriate. f) Use the equation of the least-squares regression line to predict the outcome (y-value) for one of the x-values in your data.g) Find the residual for the x-value you chose in part (f).Explain what it means when a residual is positive or negative.3. Draw Conclusions a) What do the results indicate about the relationship between two variables? b) Do you think there is a causal relation between the variables? Explain. c) Relate the comments you made in step 1b before analyzing the data by commenting on both of the following: How your expectation differs (or do not differ) from the actual results? If it is relevant or meaningful in context, think of a way that these results could be used in practice.4. Summarize Write a short summary of the main findings that you discovered. Math 140 Project: Exploring relationships between two variables -Score Sheet (Total 50 points)Name:________________________________________Date:__________________________________Title of the project: ____________________________________________________________________Website where you found the data:_______________________________________________________Project Grade: __________________________________