What can be learned from a correlation matrix?
What will be an ideal response?
A correlation matrix allows you to see the type and strength of relationships between two or more variables. Creating a correlation matrix on multiple variables can allow you to easily see which independent variables have the strongest relationships with a dependent variable. Knowing which variables have the greatest impact can guide you in the process of creating a statistical model with regression analysis.
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A surface chart
A) contains a single chart and no spreadsheet data. B) displays trends using two dimensions on a continuous curve. C) displays relationships among three values by using bubbles. D) displays values as percentages of the whole but may contain more than one data series.
Consider HgSWWSN where the narrow search space in which the nodes form an LL is limited to 1km × 0 . 1km. The node density of sensors in the entire sensor network field is about 500 sensors per square kilometer. If the probability of a WSN node forming an LL is about 0.1, estimate the following: (a) the fraction of time a given node operates its LL in the first round of operation and (b) the number of WSN nodes with LL present in the narrow search space.
What will be an ideal response?