Data Validation and Classification Quiz
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Questions and Answers

What is the purpose of identifying outliers in a dataset?

  • To improve the accuracy of statistical methods (correct)
  • To introduce errors in the data
  • To decrease the stability of neural networks
  • To maintain inconsistencies in the data
  • In the context of data analysis, what is the role of normalization?

  • To introduce errors into the data
  • To scale and transform data for better analysis (correct)
  • To maintain extreme values in the dataset
  • To prevent the identification of outliers
  • Which statistical methods benefit from normalized data according to the text?

  • Neural Networks and k-Means (correct)
  • Methods that rely on outliers
  • Methods that are insensitive to data distribution
  • Methods that avoid data preprocessing
  • What is the significance of maintaining consistency in class labels for data from different origins?

    <p>To avoid errors in data entry</p> Signup and view all the answers

    Why might a value like 192.5 pounds be considered an outlier in a dataset focused on whole-numbered weight values?

    <p>It represents an error in data labeling</p> Signup and view all the answers

    How does a histogram aid in identifying outliers in a dataset?

    <p>By highlighting extreme values in the dataset</p> Signup and view all the answers

    What is the downside of deleting records containing missing values?

    <p>Creates a biased subset</p> Signup and view all the answers

    Which method of handling missing data involves replacing missing numeric values with 0.0 and missing categorical values with 'Missing'?

    <p>Replacing with User-defined Constant</p> Signup and view all the answers

    Why is replacing missing values with random values considered superior to mean substitution?

    <p>Measures of location and spread are closer to the original</p> Signup and view all the answers

    When replacing missing values with random values, what is the potential risk regarding the resulting records?

    <p>They might introduce outliers</p> Signup and view all the answers

    In handling missing data, why is it important to consult domain experts regarding the replacement approach?

    <p>To evaluate benefits and drawbacks</p> Signup and view all the answers

    Which method involves replacing missing values based on the mode for categorical fields and the mean for numeric fields?

    <p>Replacing with Mode or Mean</p> Signup and view all the answers

    What is a common characteristic of the two possible outliers identified in the scatter plot of mpg against weightlbs?

    <p>They both have extremely high gas mileage.</p> Signup and view all the answers

    What is a common measure of center used for datasets with skewed distributions?

    <p>Median</p> Signup and view all the answers

    What is a measure of spread that includes the range, standard deviation, mean absolute deviation, and interquartile range?

    <p>Standard Deviation</p> Signup and view all the answers

    In data transformation, why is it important to normalize numeric field values?

    <p>To ensure all variables have the same range of effect on results</p> Signup and view all the answers

    Which normalization technique involves scaling the field value based on the range between the minimum and maximum values?

    <p>Min-max normalization</p> Signup and view all the answers

    In transformation to achieve normality, what analysis tool is used to check if the distribution is normal?

    <p>Normal probability plot</p> Signup and view all the answers

    Why is it suggested that ID fields should be filtered out from downstream data mining algorithms?

    <p>ID fields do not add value to the analysis.</p> Signup and view all the answers

    What is a common issue with variables containing a high percentage of missing values?

    <p>They may bias imputation strategies.</p> Signup and view all the answers

    'Double-counting' can occur when including what type of variables in analysis?

    <p>'Correlated' variables</p> Signup and view all the answers

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