Could a set of three vectors in R4 span all of R4? Explain. What about n vectors in Rm when n is less than m? Could a set of three vectors in R4 span all of R4? Explain. Choose the correct answer below. O A. No. The matrix A whose columns are the three vectors has four rows. To have a pivot in each row, A would have to have at least four columns (one for each pivot). B. Yes. Any number of vectors in R4 will span all of R4. C. No. There is no way for any number of vectors in R* to span all of R4. D. Yes. A set of n vectors in RM can span Rm when n< m. There is a sufficient number of rows in the matrix A formed by the vectors to have enough pivot points to show that the vectors span R™. Could a set of n vectors in RM span all of RM when n is less than m? Explain. Choose the correct answer below. O A. No. Without knowing values of n and m, there is no way to determine if n vectors in RM will span all of Rm. B. Yes. Any number of vectors in Rm will span all of Rm. c. No. The matrix A whose columns are the n vectors has m rows. To have a pivot in each row, A would have to have at least m columns (one for each pivot). O D. Yes. A set of n vectors in R™ can span R™ if n < m. There is a sufficient number of rows in the matrix A formed by the vectors to have enough pivot points to show that the vectors span Rm.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
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