Data Mining using R help:
What R technique would you use to reduce the number of points to make a scatter plot of dataset that has 200,000 points but would still guarantee all the points chosen from the dataset were random selections?
Try the code "sample"
This will help you to draw smaller sample from the original dataset and you may carryout suitable procedure to infer something about the dataset. (Whatever you want to do)
"sample" will draw a random sample from the dataset
Eg. s = sampl(1:200000, size = n)
If you want to then may add replace = TRUE to do draw with replacement
Then do this data[s,]
This will give what you require
Then draw a scatterplot
Data Mining using R help: What R technique would you use to reduce the number of points to make a scatter plot of dataset that has 200,000 points but would still guarantee all the points chosen from t...
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Prepare:
Context: What do the data mean? What is the goal of the
study?
Source: What is the source objective, is the source
biased?
Sampling: Does the method influence the validity of the
conclusion? Voluntary response (self-selected?) Bias?
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Below is a description of the data, how it was collected, and
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Please help guide or explain how I would graph this? Thank you
so much
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Please help! Comments added in would be a great help. Thank
you!
Input file
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Someone plz plz help with this Statistics Intro to R programming
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Here are the examples and follow by my question!!
Thank you so much!! I appreciate it
!!!!My question!!!!
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