Publications by aardvarkfunnyxia
Exercise 1.3 Simple random walk
Look up the help file of the cumsum() function. Apply this function on the vector of Rademacher random variables you obtained in Exercise 1.2 to create a simple random walk with 1000 steps. Plot your random walk on a suitable graph. What is the maximal deviation of this random walk from 0? How many times has your random walk returned to 0? prep...
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hubble ## distance velocity ## 1 0.032 170 ## 2 0.034 290 ## 3 0.214 -130 ## 4 0.263 -70 ## 5 0.275 -185 ## 6 0.275 -220 ## 7 0.450 200 ## 8 0.500 290 ## 9 0.500 270 ## 10 0.630 200 ## 11 0.800 300 ## 12 0.900 -30 ## 13 0.900 650 ## 14 ...
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Exercise 9
Sheff_temp <- read.csv("Sheffield_max_temp_data.csv", header = FALSE) colnames (Sheff_temp) <- c ("Year", "Month", "Max_temp") Exercise 9.1. boxplot (Sheff_temp$Max_temp ~ Sheff_temp$Month, xlab = "", ylab = "Celsius", xaxt = "n", main = "Average maximum monthly temperature in Sheffield, 1883 - 2014") axis(side = 1, at = 1:12, l...
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Cocoa price from 2012 to 2014
###### The plot for exercise 6.4. Cocoa Prices from 2012 to 2014 # add the price and mean lines for all three years using # the a and b arguments for abline(), legend, text and axis features. cocoa <- read.csv ("Cocoa_prices.csv", header = FALSE) Mths <- substr(cocoa$V1, start = 1, stop = 3) Yrs <- paste ("20", substr ( cocoa$V1, start = 5, stop ...
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Updated: cocoa price from 2012 to 2014
cocoa <- read.csv ("Cocoa_prices.csv", header = FALSE) Mths <- substr(cocoa$V1, start = 1, stop = 3) Yrs <- paste ("20", substr ( cocoa$V1, start = 5, stop = 6)) cocoa_updated <- data.frame (Yrs, Mths, cocoa$V2) Price <- cocoa_updated$cocoa.V2 cocoa_updated_price <- data.frame (Yrs, Mths, Price) cocoa_wide <- reshape ( cocoa_updated_price, timeva...
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Sheff_temp <- read.csv("Sheffield_max_temp_data.csv", header = FALSE) colnames (Sheff_temp) <- c ("Year", "Month", "Max_temp") Sheff_temp_noNA <- na.omit(Sheff_temp) par (mfrow = c (1,1)) boxplot (Sheff_temp$Max_temp ~ Sheff_temp$Month, xlab = "Months", ylab = "Celsius", xaxt = "n", main = "Average maximum monthly temperature ...
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The purpose of a violin plot: It is used to visualize the distribution of numerical data. library(ggplot2) Sheff_temp <- read.csv("Sheffield_max_temp_data.csv", header = FALSE) colnames (Sheff_temp) <- c ("Year", "Month", "Max_temp") Sheff_temp_noNA <- na.omit(Sheff_temp) attach(Sheff_temp_noNA) ggplot (Sheff_temp_noNA, aes (x = fact...
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apply() Use the apply() function when we want to apply a function to the rows or columns of a matrix / data frame. apply ( name (of the matrix/data frame), MARGIN (which dimension to perform an operation across 1 = row, 2 = column), FUN (specific operation you want to perform (max, min, sum. mean, etc.)) Example: # We first create a data frame with...
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Exercise 8.1. x_values = seq ( -3, 3, length.out = 100000) plot ( x_values, dnorm (x_values, mean = 0, sd = 1), type = "l") abline ( v = c (-3, 3), col = "red", lty = 2, lwd = 2) total_area <- pnorm (Inf, mean = 0, sd = 1) area_below_3 <- pnorm (3, mean = 0, sd = 1) area_between <- ((2 * area_below_3 - 1) / total_area ) *100 print...
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When a certain driver parks their car in the evenings, they are equally likely to remember or to forget to switch off the headlights. Giving your answers in their simplest index form, find the probability that on the next 16 occasions that they park their car in the evening, they forget to switch off the headlights: a) 14 more times than they rem...
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