Question
When using descriptive statistics, which measure is best
for understanding data variability?Solution
Standard deviation is the most informative measure of data variability because it quantifies the average deviation of each data point from the mean. By providing insight into the spread of data values around the mean, standard deviation helps analysts understand how clustered or dispersed the data is, which is crucial for interpreting patterns and making comparisons between datasets. Standard deviation is particularly valuable in assessing consistency and identifying outliers, making it essential in descriptive statistical analysis. The other options are incorrect because: • Option 1 (mean) is a central tendency measure, not a measure of variability. • Option 2 (median) indicates the central value but not data spread. • Option 3 (mode) is useful for frequency analysis but not for assessing variability. • Option 5 (range) provides a simple variability measure but lacks the detail of standard deviation, as it only considers extremes.
What is a botnet typically used for?
Which component in IoT performs data preprocessing before sending it to the cloud?
What is a confusion matrix used for?
Which technique is used to reduce dimensionality while preserving variance?
What does underfitting indicate?
Which layer of IoT focuses on transmitting data between devices and servers?
Which of the following is an example of an IoT application in healthcare?
Which of these is a parametric algorithm?
What is overfitting?
Which protocol is lightweight and widely used for IoT messaging?