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Data Description

Jason Dsilva Data Mining Bachelors Degree Inglés 8 fichas

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  1. 1What is a dataset?A dataset is a collection of objects and attributes. E.g customer name, age, address and country. Attributes can be numerical or categorical.
  2. 2Data Quality-Accuracy; How accurate?
    -Completeness; Any missing data?
    -Consistency; Any inconsistency?
    -Timeliness; Are there any timely updates?
    -Believability; How trustworthy?
    -Interpretability; How easy is it to understand?
  3. 3TerminologyPopulation: A collection of things under consideration.
    Sample: A proportion of a population selected for sampling.
    Statistics: A summary of measure computer to describe a characteristic of the sample data.
  4. 4Correlation CoefficientUsed to measure the degree of a linear relationship between two variables. If y>0 than positive correlation, however it y<0 its negative correlation.
  5. 5Mean, Medium and ModelMean: Sensitive to extreme values e.g Outliers
    Medium: Middle values
    Mode: Most common number in the dataset. Unimodal if one one number is the model and Bimodal for two modes
  6. 6Scatter plots:Shows the relationship between two variables. Linear (Straight line) demonstrates a negative relationship. Non-linear curved relationship shows no relationship.
  7. 7Normal Distribution- 68 percent of all values are within one standard deviation on either side of the mean.
    - 95 percent are between two standard deviations on either side of the mean.
  8. 8Frequency TableContains the outcome along with its frequencies. Allow us to see better distribution of the marks.

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Bachelors Degree Data Mining Fichas sobre Data Description, creado por Jason Dsilva el 01/05/2016.
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Jason Dsilva
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