A graph can reveal anomalous results by displaying data points that significantly deviate from the overall trend or pattern. For instance, if most points cluster around a specific range and one point is far removed from this cluster, it indicates an outlier. Additionally, statistical measures such as standard deviation can help highlight these anomalies by showing points that fall outside of expected variability. Visual representation makes it easier to spot these discrepancies quickly.
it differs becaus eit shows differ amount of data and it gives a differ piont of point of numbers
A graph does not cook your meals when you are hungry! A graph does not show causation.
a picture graph uses pictures to show the point and bar graph use bar lines to show the point.
A pie graph is best for using to show percentages.
a table graph doesn't exist a frequency table show how often something happens
If you are trying to spot an anomalous result from a graph, draw a line of best fit onto your graph, the anomalous result will be the result that is way off the line of best fit/ does not fit the pattern. If you are looking for an anomalous result within a table, the results should fall with in .1 of each other, if any of the figures do not, then they are the anomalies (anomalous results).
You should exclude the anomalous results when calculating an average.
Why do you include an anomalous result in a piece of data
An Outlier; an Outlier is when a point is not part of a trend (pattern)
it differs becaus eit shows differ amount of data and it gives a differ piont of point of numbers
it differs becaus eit shows differ amount of data and it gives a differ piont of point of numbers
it differs becaus eit shows differ amount of data and it gives a differ piont of point of numbers
it differs becaus eit shows differ amount of data and it gives a differ piont of point of numbers
Anomalous data on a graph typically appears as points that deviate significantly from the overall pattern or trend of the dataset. These outliers can be much higher or lower than the majority of the data points, indicating potential errors, unique events, or variability in the data. In a scatter plot, for instance, they may lie far from the regression line, while in a time series graph, they might manifest as sudden spikes or drops. Identifying these anomalies is crucial for data analysis, as they can provide insights or indicate potential issues.
Anomalous data points on a graph are commonly referred to as "outliers." These are values that deviate significantly from the overall trend or pattern of the dataset, often indicating variability in the measurement or potential errors. Identifying outliers is crucial for data analysis, as they can influence statistical results and interpretations.
the odd one outby amra mohideen
Odd results in tables are called anomalous results.