(1 mark) Why is working with the income in a log-scale a common practice in data analysis? Answer 1 Question 1A. Income is often left skewed, and through a log-transformation, the distribution of the log income is more symmetric.B. Log-transformation is useful because it always improves the accuracy of the model.C. Income is often positively skewed, and through a log-transformation, the distribution of the log income is more symmetric.D. Log-transformation makes the data look more linear.

What is the main advantage of using a logarithmic scale in a chart?It can handle negative values betterIt emphasizes the differences between larger valuesIt compresses the scale for larger values and expands for smaller onesIt removes outliers from the data

Why is normalizing log data important in a centralized logging setup?Log normalizing detects potential attacks.The data must be decrypted before sending it to the log server.It's difficult to analyze abnormal logs.Uniformly formatted logs are easier to store and analyze.

If a feature has a highly skewed distribution, then which of the following transformations should be used to transform the data?Select an option Clear ResponseBinningLog TransformationsGeometric Means TransformationStandard Scaling

Which data scaling technique transforms data to a fixed range, often between 0 and 1?Review LaterMin-Max ScalingZ-Score StandardizationRobust ScalingLog Transformation

Which data scaling technique adjusts the data distribution by raising it to a power, such as Box-Cox or Yeo-Johnson?Review LaterMin-Max ScalingZ-Score StandardizationLog TransformationPower Transformation