Discussion: Concentration in Beijing China Research Paper

Discussion: Concentration in Beijing China Research Paper ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON Discussion: Concentration in Beijing China Research Paper I’m studying for my Statistics class and need an explanation. you should be familiar with r studio. Using r to finish a statistics vivualization homework. Discussion: Concentration in Beijing China Research Paper sta141ass20_hw2_2.pdf STA 141A Summer 2020 Homework 2 Due: August 28 11.59 pm Submit the assignment electronically on Canvas. The electronic submission must be in the form of a zip folder (with extension .zip, .7z, etc.) containing your data analysis report in pdf and the R codes used to perform the data analysis in an Appendix. Honor Code: ”The codes and results derived by using these codes constitute my own work. I have consulted the following resources regarding this assignment:” (ADD: names of persons or web resources, if any, excluding the instructor, TAs, and materials posted on course website) Description of the data The Beijing PM2.5 Data Set is taken by the website https://archive.ics.uci.edu/ml/datasets/Beijing+PM2.5+Data. It contains the PM2.5 data of US Embassy in Beijing and the meteorological data from Beijing Capital International Airport. These data are collected in the R data frame Beijing_pollution.RData, which contains the following columns: 1. No: row number 2. year: year of data in this row 3. month: month of data in this row 4. day: day of data in this row 5. hour: hour of data in this row 6. pm2.5: PM2.5 concentration (ug/m3 ) 7. DEWP: Dew Point 8. TEMP: Temperature 9. PRES: Pressure (hP a) 10. cbwd: Combined wind direction: NE (North-East), SE (South-East), NW (North-West), cv (South-West) 11. Iws: Cumulated wind speed (m/s) 12. Is: Cumulated hours of snow 13. Ir: Cumulated hours of rain 1 • You may use both graphical and analytical methods (such as linear regression and scatterplot smoother) to find interesting patterns in the data that may help in building predictive statistical models.Discussion: Concentration in Beijing China Research Paper • The data analysis, which should address the following questions, needs to be summarized in the form of a report (a maximum of 1000 words, i.e, approximately 2 pages). • The variable pm2.5 has many missing values, which should be accounted for while carrying out any analysis. • While building a predictive model (question 4 below), you may consider transforming certain variables and fitting linear regression models using original or transformed variables. Questions: 1. Provide a graphical summary, with explanations, to describe how the various numeric variables relate to each other. 2. Briefly describe if you find any relationship between pm2.5 and month. How do such patterns change across hour and cbwd? 3. Consider the variables DEWP, TEMP and PRES and describe how the relationships among any pair of these variables vary across strata determined by factors such as year, month and hour. (You need to think carefully about how to present such information graphically). 4. Can you identify a subset of variables that are effective in terms of predicting pm2.5? Are there differential effects across month, hour and cbwd? Propose a predictive model based on your analysis. References: (Online versions of the first two books are available through UC Davis Library.) 1. James, G., Witten, D., Hastie, T. and Tibshirani, R. (2013). An Introduction to Statistical Learning with Applications in R. Springer. 2. Wickham, H. (2009). ggplot2: Elegant Graphics for Data Analysis. Springer. 3. Wickham, H. and Grolemund, G. (2017). R for Data Science. O’Rielly. 2 …Discussion: Concentration in Beijing China Research Paper Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10