All Flashcards
What are the differences between mean and median?
Mean: Average value, sensitive to outliers | Median: Middle value, resistant to outliers
What are the differences between standard deviation and IQR?
Standard Deviation: Measures spread around the mean, best for symmetric data | IQR: Measures spread of middle 50%, best for skewed data
What are the differences between unimodal and bimodal distributions?
Unimodal: Has one peak, indicating one mode | Bimodal: Has two peaks, indicating two modes
What are the differences between symmetric and skewed distributions?
Symmetric: Data evenly distributed around the center, mean ≈ median | Skewed: Data concentrated on one side, mean ≠ median
What are the differences between range and IQR?
Range: Max - Min, sensitive to outliers | IQR: Q3 - Q1, resistant to outliers
What are the differences between right-skewed and left-skewed distributions?
Right-skewed: Tail longer on the right, mean > median | Left-skewed: Tail longer on the left, mean < median
What is a symmetric distribution?
A distribution where both sides look like mirror images when folded in half.
What is a right-skewed distribution?
A distribution with a tail longer on the right side; mean > median.
What is a left-skewed distribution?
A distribution with a tail longer on the left side; mean < median.
What is a mode in a distribution?
The most frequent value(s) in a dataset, represented by peak(s) in a histogram.
What are outliers?
Values that are significantly higher or lower than the rest of the data.
What is the range of a dataset?
Maximum value minus the minimum value.
What is the Interquartile Range (IQR)?
The range of the middle 50% of the data (Q3 - Q1).
What is the formula for Range?
Range = Maximum value - Minimum value
What is the formula for Interquartile Range (IQR)?
IQR = Q3 - Q1
How do you calculate the mean?
Sum of all values divided by the number of values.
How do you calculate the median?
The middle value when the data is ordered from least to greatest.
How to identify outliers?
Values significantly higher or lower than the rest of the data.