Data instance
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?
Sample Solution
Data instance What is an attribute? An attribute is a specification that defines a property of an object, element, or file. It may also refer to or set the specific value for a given instance of such. For clarity, attributes should more correctly be considered metadata. What is a data instance? Data are the given information to be processed and stored. For example, in a digital photograph, the pattern of recorded light from the CCD in a camera could provide the data. A data instance is one particular piece of digital information. This is comparable to how an organism is one particular plant or animal of a species.
to get supplies from. This makes the bargaining power of supplier low. However, despite high number of suppliers, the suppliers do no compete within the industry for products, which means that A2 company can only purchase what the suppliers provide. This gives the supplier a high bargaining power. To sustain in this competitive industry, A2 milk can get supplies from multiple suppliers, more flexibility within its supply chain. Or they can encourage better relationship with the supplier can benefit on both sides.