Data Visualization & its Distribution
Code for Data Visualization using SAS:
Output & Distribution:
Diameter of the crater:
Depth of the Crater:
Number of Layers :
Distribution:
Uni-variate graph of rate of number of layers for Mars Crater:
This graph is unimodal, with its highest peak at NUMBER_LAYERS=0. It seems to be skewed to the right as there are higher frequencies in lower categories than the higher categories.
The entire weight of the graph seems to be on 0 which is more than 90% of the weight is carried by craters which doesn’t have any layers.
Uni-variate graph for Depth of Mars Crater:
This graph is unimodal, with its highest peak at NUMBER_LAYER= 5. It seems to be skewed to the left as there are higher frequencies in the higher Layer ranges.
The graph shows a positive linear distribution i.e. with increase in the Number of Layers, the Depth of the crater also increases.
Uni-variate graph for Diameter of Mars Crater:
This graph is unimodal, with its highest peak at NUMBER_LAYER= 5. It seems to be skewed to the left as there are higher frequencies in the higher Layer ranges.
The graph shows a positive linear distribution i.e. with increase in the Number of Layers, the Diameter of the crater also increases.
Bi-variate Graph :
The graph above plots the Diameter of the Crater corresponding to the Depth of the Crater. We can see that the scatter graph does not show a clear relationship/trend between the two variables.
Though a slight positive relationship between the two variables is seen i.e. with the increase in Depth of the crater, its Diameter also increases slightly from a depth of 1km. Presence of outliers is also seen at Depth almost equal to 0.
