1. For this assignment you need to use data frame wine which contains information on prices and growing characteristics of 25 Bordeaux wines from 1952 to 1998. The data frame contains 7 columns and 47 rows. The columns are: year of production year, average price of the wines as a percentage of the 1961 price (price), mm of rain in the harvest month (h.rain), average temperature (C) over the summer preceding harvest (s.temp), mm of rain in the winter preceding harvest (w.rain), average temperature (C) at harvest (h.temp), a rating of the wine quality (parker).
See https://www.wine-searcher.com/critics-27-robert+parker+the+wine+advocate
for details on parker.
The aim of the analysis is to model the response variable price as a function of the variables described above.
Using these data, write a report addressing the following points:
(a) Justification of the chosen regression model specification. [5]
(b) Using the final model, provide a summary (e.g., using tables and figures) of the empirical findings as well as interpretation of the estimated model parameters. [5]
(c) Provide recommendations and limitations of your analysis. [5]
(d) What did you learn from the analysis? What is the answer, if any, to the questions you set out to address? How can the analysis be improved? [5]
Other 5 marks will be for overall report structure (e.g., report neatness, presentation style, extra effort).
The report must be in pdf format. It (excluding the title page) must not be longer than 5 pages (including graphs, tables, etc.) using font size 12pt with one and a half line spacing and at least 2.5 cm margin.
[Total marks: 25]
2. An economist is interested in trying to find simple models for predicting the amount of carbon dioxide that individuals are responsible for emitting into the atmosphere each year. For a sample of two hundred adults she draws up a detailed carbon budget to estimate each person’s CO2 emissions in tonnes per year (CO2). As part of the study their household income is recorded (income in thousands of pounds), along with whether or not they own a 4 wheel drive car (fwd, a factor with levels 0, for no and 1 for yes) and their beliefs about climate change (belief, a factor with levels: yes, they believe the science; no, they do not; and not.understand, for claiming not to understand the science.)
The following R session is an attempt to build a model for these data.
(a) By looking at the R code below write down the statistical model that has been fitted and the model assumptions. [2]
> co.mod <- lm(CO2~income+fwd+belief,data=warm)
(b) Comment on the following residual plots. [3]
> par(mfrow=c(2,2))
> plot(co.mod)
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