The span of a set of vectors is the collection of all vectors which can be represented by some linear combination of the set. That sounds confusing, but let’s think back to the basis vectors i=(1,0) and j=(0,1) in R^2. If you choose absolutely any vector, anywhere in R^2, you can get to that vector using a linear combination of i and j. If I choose (13,2), I can get to it with the linear combination a=13i+2j, or if I choose (-1,-7), I can get to it with the linear combination a=-i-7j. There’s no vector you can find in R^2 that you can’t reach with a linear combination of i and j.
Read MoreWe can conclude that every span is a subspace. Remember that the span of a vector set is all the linear combinations of that set. The span of any set of vectors is always a valid subspace.
Read MoreAny vector with a magnitude of 1 is called a unit vector, u. In general, a unit vector doesn’t have to point in a particular direction. As long as the vector is one unit long, it’s a unit vector. But oftentimes we’re interested in changing a particular vector v (with a length other than 1), into an associated unit vector. In that case, that unit vector needs to point in the same direction as v.
Read MoreNow we want to look at what happens when we combine two data sets, either by adding them or subtracting them. When we’re combining multiple linear random variables, we can find the mean and standard deviation of the combination using the means and standard deviations of the individual variables.
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