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1 . Consider a dataset on Standardized Precipitation Evaporation Index ( SPEI ) which measures the drought level of areas. Here, SPEI _ 1 9

1. Consider a dataset on Standardized Precipitation Evaporation Index (SPEI) which measures the drought level of areas. Here, SPEI_1981_2010.csv data is given and indicate the drought level of a sample of districts in Amhara region, Ethiopia. The SPEI data is the monthly measures between 1981 and 2010.The main objective of this data manipulation or exploratory data analysis is to provide insightful information to respond the objectives of a research. That is:a. A researcher wants to classify drought level in eight classes and wants to compare percentage of time that a given district was in each drought level in the past 30 years.b. In addition, the researcher want to estimate the mean and standard deviation of SPEI in each drought level class. c. Further, the researcher wants to compare drought levels of districts in the region using mean and standard deviation. The classification of the SPEI into drought level is based on the following criteria. SPEI ValueClassExtremely wetSeverely wetModerately wetMild wetNormalMild droughtModerately droughtSeverely droughtExtremely drought Based on the interest of the research,i. Summarize the data using frequency tables of SPEI class with frequency, percentage, mean and standard deviation of SPEI in each drought level. The frequency table look like (the values in the table are not true).Drought levelAdet frequencyPercentMeanSt.dev.Extremely drought92.2%-3.6 Extremely wet143.4%2.3 Mild drought5012.3%-.8 Mild wet6716.5%.8 Moderate drought368.9%-1.3 Moderately wet245.9%1.3 Normal17643.3%.1 Severely wet123.0%1.8 Severely drought184.4%-1.7 ii. Write R-code generate an appropriate output and give full description for each function in your code. iii. Write discussion about your results.iv. Visualize your data using different graphical methods like time series plots (line, smooth plot (lm, loess,..)v. Draw some bar plot, simple or multiple bar plots.vi. Visualize presence of seasonality in SPEI across districts.

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