Coronavirus Disease 2019

This work is a 4th-year level economic assignment asking for R programming to analyze the data mentioned in the assignment. This assignment is somewhat open-ended. You can choose any data you may find on the following ‘Our World in Data’ site. Or you may try to find data on US or Canada Covid 19 cases from any other sites). The following is just an example of where you may find some interesting recent data: a) Coronavirus (COVID-19) Cases – Statistics and Research – Our World in Data. b) COVID-19: Government Stringency Index, Feb 10, 2021 ( 1) If you have Covid 19 cases for several dates starting from say January 2020 (in your data), choose the data for any one of the dates preferably the current date (row selection). 2) Select Covid 19 cases or any other variable as the dependent variable and from 4 to 6 other (relevant variables) as your independent variables (column selection). 3) If you choose a categorical variable (that is not numerical such as gender) as your independent variable, convert it to factor: x <- as.factor(x), or x <-factor(x). (Noes: Variables such as gender (M or F) are called categorical variables. R programming needs to know that they are factors. Both categorical and numerical variables can be converted into factors, however.) 4) You may also directly write factor(x) in your equation while performing linear regression. (you may try all 3 different ways and see what you get. And choose the one that looks as desired.) 5) If x has multiple levels, you may try as follows as well (note ‘data’= name of your data and x = name of the x variable): data$x <- factor(data$x, levels = c("B", "A")). Note if x = gender then A = male and B = female. 6) Perform Shapiro. test to see if your data (say x variable) follow the normality assumption. If not, then use log transformation to x (and y as well): data$logX <- log10(data$X). 7) Run linear regression for this log-transformed data: lm(logY ~logX, data = ..) 8) Draw a linear regression plot using ggplot2. Optional. You may do the following or any other you may find interesting particularly if you choose to write a paper for 20 marks (out of 50 marks allocated for the final). 9) If you use Covid data from the site I mentioned above, you may select anyone (or a couple of) country and draw a graph (using ggplot2) with x = time/date and (100 – stringency index) and Covid 19 cases in the vertical axis. 10) You may try to analyze any other interesting relations you can think of. 11) You may also draw any other plots such as bar or boxplots (of the variables that make sense or may show interesting patterns). 

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