What range of values does a dataset typically have after Min-Max scaling?
- -1 to 1
- 0 to 1
- Depends on the dataset
- Depends on the feature
Min-Max scaling transforms features by scaling each feature to a given range. The default range for the Min-Max scaling technique is 0 to 1. Therefore, after Min-Max scaling, the dataset will typically have values ranging from 0 to 1.
What is the term for the measure of how spread out the values in a data set are?
- Central Tendency
- Dispersion
- Kurtosis
- Skewness
The term for the measure of how spread out the values in a data set are is called "Dispersion". It includes range, interquartile range (IQR), variance, and standard deviation.
You've created a histogram of your data and you notice a few bars standing alone far from the main distribution. What might this suggest?
- Data is evenly distributed
- Normal distribution
- Outliers
- Skewness
In a histogram, bars that stand alone far from the main distribution often suggest the presence of outliers.
You have a dataset where the relationships between variables are not linear. Which correlation method is better to use and why?
- Covariance
- Kendall's Tau
- Pearson's correlation coefficient
- Spearman's correlation coefficient
For non-linear relationships between variables, Spearman's correlation coefficient would be a better choice. This is because Spearman's correlation measures the monotonic relationship between two variables and does not require the relationship to be linear.
Which of the following is a type of data distribution?
- Age Bracket Distribution
- Binomial Distribution
- Household Distribution
- Sales Distribution
The Binomial Distribution is a type of probability distribution that describes the number of successes in a fixed number of independent Bernoulli trials each with the same probability of success.
How does Robust scaling minimize the effect of outliers?
- By ignoring them during the scaling process
- By removing the outliers
- By scaling based on the median and interquartile range instead of mean and variance
- By transforming the outliers
Robust scaling minimizes the effects of outliers by using the median and the interquartile range for scaling, instead of the mean and variance used by standardization. The interquartile range is the range between the 1st quartile (25th percentile) and the 3rd quartile (75th percentile). As the median and interquartile range are not affected by outliers, this method is robust to them.
Which measure of dispersion is defined as the difference between the largest and smallest values in a data set?
- Interquartile Range (IQR)
- Range
- Standard Deviation
- Variance
The "Range" is the measure of dispersion that is defined as the difference between the largest and smallest values in a data set.
Describe the impact of skewness and kurtosis on parametric testing.
- They can improve the accuracy of parametric testing.
- They can invalidate the results of parametric testing.
- They can reduce the variance in parametric testing.
- They do not impact parametric testing.
Skewness and kurtosis can invalidate the results of parametric testing. Many parametric tests assume that the data follows a normal distribution. If the data is highly skewed or has high kurtosis, these assumptions are violated, and the test results may not be valid.
If a distribution is leptokurtic, what does it signify about the data?
- The data has a high variance.
- The data is heavily tailed with potential outliers.
- The data is less outlier-prone.
- The data is normally distributed.
Leptokurtic distribution signifies that the data has heavy tails and a sharp peak, meaning there are substantial outliers (or extreme values). This kind of distribution often indicates that the data may have more frequent large jumps away from the mean.
A potential drawback of the Z-score method for outlier detection is that it assumes the data is _______ distributed.
- exponentially
- logistically
- normally
- uniformly
The Z-score method assumes that the data is normally distributed, which may not be the case with all datasets, and is a drawback.