SIT718 - Using Aggregation Functions For Data Analysis And Transformation For All Variables - IT/Computer Science Assignment Help

Assignment Task -

Tasks:

1. Understand, clean (if necessary) and prepare the data 

(i) Download the txt file (EuStockMarkets2.txt) from CloudDeakin and save it to your R working directory. 

(ii) Assign the data to a matrix, e.g. using 

(iii) Your variable of interest is X4, the FTSE index. Generate a subset of 500 data, e.g. using: 

(iv) Using descriptive statistics, find the main statistical characteristics of all variables. Include assessment of the the outliers using boxplots (4 boxplots). Record your results in a table (Table 1).

(v) Using scatterplots and histograms, report on the general properties of each vari able Xi, i=1,2,3,4 and relationship (if any) between each of the variables X1,X2, X3and your variable of interest X4 (FTSE). Include a scatter plot for each of the variables Xi, i=1,2,3,4, (4 scatterplots) and each pair of variables, e.g. X1 and X4, X1 and X2, etc. (6 scatterplots). Include a histogram for each variable X1,X2,X3 and X4 (4 histograms). Include 1 or 2 sentences about the relationships and distributions. 

2. Transform the data 

(i) Apply transformations to all variables, X1, X2, X3, to model X4. 

Make appropriate transformations to the variables so that the values can be aggregated in order to predict the variable of interest X4 (FTSE). The transformations should reflect the general relationship between each of the four variables and the variable of interest. Assign your transformed data along with your transformed variable of interest to an array (it should be 500 rows and 4 columns). Save it to a txt file titled ”name-transformed.txt” using 

(ii) Briefly explain each transformation for all variables. You may also include mathe matical formulae if appropriate (1- 2 sentences each). 

(iii) Include the histograms of all four transformed variables in your report (4 histograms). 

3. Build models using aggregation functions and investigate the importance of each vari able.

(i) Download the AggWaFit.R file (from CloudDeakin) to your working directory and load into the R workspace using,

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