Use R language to complete assignment. Load the Iris dataset and answer the following questions with the help of R code given. State the descriptive statistics, including maximum, minimum, average, median, range, sum and standard deviation for of Sepal length, sepal width, petal length and petal width. Create and show histogram plots of Sepal length, sepal width, petal length and petal width. In the Question 2, Which histogram plots do resemble normal distribution? Discuss. Create and show a scatter plot of sepal width and sepal length. What trend do you see? Discuss. What other data visualization or analysis can be done on this dataset? Give some ideas. library(psych) library(ggplot2) Data(iris) head(iris) psych::describe(iris) # Create a scatter plot ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Petal.Length, size = Petal.Width, shape = Species)) + geom_point() + scale_color_gradient(low = "blue", high = "red") + labs(title = "Iris Dataset: Four-Dimensional Visualization", x = "Sepal Length", y = "Sepal Width", color = "Petal Length", size = "Petal Width") + theme_minimal() # Basic histogram ggplot(df, aes(x=weight)) + geom_histogram()

Np Ms Office 365/Excel 2016 I Ntermed
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ISBN:9781337508841
Author:Carey
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Chapter4: Analyzing And Charting Financial Data
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Use R language to complete assignment. Load the Iris dataset and answer the following questions with the help of R code given. State the descriptive statistics, including maximum, minimum, average, median, range, sum and standard deviation for of Sepal length, sepal width, petal length and petal width. Create and show histogram plots of Sepal length, sepal width, petal length and petal width. In the Question 2, Which histogram plots do resemble normal distribution? Discuss. Create and show a scatter plot of sepal width and sepal length. What trend do you see? Discuss. What other data visualization or analysis can be done on this dataset? Give some ideas. library(psych) library(ggplot2) Data(iris) head(iris) psych::describe(iris) # Create a scatter plot ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Petal.Length, size = Petal.Width, shape = Species)) + geom_point() + scale_color_gradient(low = "blue", high = "red") + labs(title = "Iris Dataset: Four-Dimensional Visualization", x = "Sepal Length", y = "Sepal Width", color = "Petal Length", size = "Petal Width") + theme_minimal() # Basic histogram ggplot(df, aes(x=weight)) + geom_histogram()
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