Question
Which of the following visualizations is most effective
for detecting outliers in a dataset ?Solution
Explanation: Box plots are specifically designed to display the distribution of data and highlight outliers. They show the interquartile range (IQR), the median, and the minimum and maximum values within 1.5 times the IQR. Data points outside this range are identified as outliers. This makes box plots an invaluable tool for quickly spotting anomalies. For instance, in financial datasets, box plots can reveal unusually high or low transaction amounts that might warrant further investigation. Option A: Line charts display trends over time but are not effective for identifying individual outliers. Option B: Bar charts represent categorical data frequencies but do not highlight outliers. Option D: Histograms show frequency distributions but might not clearly indicate outliers, especially for large bins. Option E: Scatter plots can suggest outliers in relationships between two variables but lack formal criteria for identifying them.
If (x + 1/x) = 5, then value of x3 + 1/x3 is:
? Γ 5.5 = β1225 + 40% of 30% of 37.5% of 5000 β 63
(21 X 5) + ? = (480 - 120) Γ· 3
The value of 15 × 14 – 30 + (32 + 17) is:
30% of 8/5 Γ 5/7 Γ 2870 =?
74% of 2840 + 80% of 1640 - ?= 47²
(22 + β3364)/(? + 4) = 10
What value should come in the place of (?) in the following questions?
β(60 + 82 + 101) * 5 = ?
25% of 12% of 1600 + 112 = ? Γ 4Β
(22.5 × 24) ÷ 40 + 51.50 = ? ÷ 5.25