Reference no: EM132474664
Discussion: What's simple random sampling? Is it possible to sample data instances using a distribution different from the uniform distribution? If so, give an example of a probability distribution of the data instances that is different from uniform (i.e., equal probability).
You must make at least two substantive responses to your classmates' posts. Respond to these posts in any of the following ways:
• Build on something your classmate said.
• Explain why and how you see things differently.
• Ask a probing or clarifying question.
• Share an insight from having read your classmates' postings.
• Offer and support an opinion.
• Validate an idea with your own experience.
• Expand on your classmates' postings.
• Ask for evidence that supports the post.
Discussion Length (word count): At least 150 words
References: At least one peer-reviewed, scholarly journal references.
Assignment: 1. What's an attribute? What's a data instance?
2. What's noise? How can noise be reduced in a dataset?
3. Define outlier. Describe 2 different approaches to detect outliers in a dataset.
4. Describe 3 different techniques to deal with missing values in a dataset. Explain when each of these techniques would be most appropriate.
5. Given a sample dataset with missing values, apply an appropriate technique to deal with them.
6. Give 2 examples in which aggregation is useful.
7. Given a sample dataset, apply aggregation of data values.
8. What's sampling?
9. What's simple random sampling? Is it possible to sample data instances using a distribution different from the uniform distribution? If so, give an example of a probability distribution of the data instances that is different from uniform (i.e., equal probability).
10. What's stratified sampling?