HI need a help with this.

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If you could send me as soon as possible,thank you.

Assignment: Data- Simple Graphs in RStudio

Background: As we have learned, a lot of thought goes into the design of a visualization. This week we review how the data types influence the graphing types.

Assignment:

• Use RStudio to generate a word document with simple graphs of the following dataset: dataset_price_personal_computers.csv
• Review the slides to learn the data types requirements for each graph type: Analyzing and Visualizing Data - Selecting a Graph.pptx
• Use the following videos to learn the commands to produce simple graphs in RStudio: RStudio - Simple Graphs - Part1.mp4 | RStudio - Simple Graphs - Part2.mp4

Graphs to Produce:

Pie Chart:

• Create a pie chart of the computer ram
• Label the ram sizes as follows: 2GB, 4GB, 8GB, 16GB, 24GB, 32GB
• Title the pie chart as "Computer Ram"
• Color the pie chart using the rainbow option

Bar Plot:

• Create a barplot of the computer screen sizes
• Label the x axis as "Screen Sizes"
• Label the y axis as "Frequency"
• Title the barplot as "Computer Screen Sizes"
• Color the bars in the barplot any color you wish.

Histogram:

• Create a histogram of the computer prices
• Label the x axis as "Prices"
• Title the histogram as "Computer Prices"
• Give the histogram any color you wish.

Box Plot:

• Create a boxplot of the comparing the computer price and premium category
• Label the y axis as "Price"
• Label the x axis as "Premium"
• Title the boxplot as "Premium Computer Prices Distribution"
• Color the boxplot any color you wish.

Scatter Plot:

• Create a scatter plot of computer price and hard drive size
• Label the x axis as "Hard Drive Size"
• Label the y axis as "Price"
• Title the scatter plot as "Computer Price vs Hard Drive Size"
• Color the scatter any color you wish

Analyzing and Visualizing Data - Selecting a Graph

Pie Charts

qCompare a certain sector to the total.

qUseful when there are only two sectors, for example yeso or queued/finished.

qInstant understanding of proportions when few sectors are used as dimensions.

qWhen you use 10 sectors, or less, the pie chart keeps its visual efficiency.

Bar Charts/Plots

qOrdinal and nominal data sets

qCompare things between different groups or to track changes over time

qMeasure change over time, bar graphs are best when the changes are larger

qDisplay and compare the number, frequency or other measure (e.g. mean) for different discrete categories of data

qFlexible chart type and there are several variations of the standard bar chart including horizontal bar charts, grouped or component charts, and stacked bar charts.

qFrequency for each category of a categorical variable

qRelative frequency (%) for each category

Histograms

qIt plots the frequencies that data appears within certain ranges.

qUnderlying frequency distribution (shape) of a set of continuous data.

qUnderlying distribution (e.g., normal distribution), outliers, skewness, etc

qPlot the frequency of score occurrences in a continuous data set that has been divided into classes

Box plots

qDistribution of a continuous measure by some grouping variable

qThey measure the spread of the data, sort of like standard deviation.

oThe line in the middle of the box is the median.

oThe box itself represents the middle 50% of the data.

oThe box edges are the 25th and 75th percentiles.

oThe vertical size of the boxes are the interquartile range, or IQR.

oThe tops and bottoms of the boxes are referred to as hinges.

oWhiskers: They represent the reasonable extremes of the data. That is, these are the minimum and maximum values that do not exceed a certain distance from the middle 50% of the data.

oIf no points exceed that distance, then the whiskers are simply the minimum and maximum values.

oOutliers, data points that are too big or too small compared to the rest of the data.

Scatter plots

qView the potential relationship of two continuous variables

qGraphical view of the relationship between two sets of numbers.

qScatter plots show how much one variable is affected by another.

qThe relationship between two variables is called their correlation.

qFind potential relationships between values, and to find outliers in data sets.

please complete this graphs and send me as soon as possible.