Understanding Binomial Distribution
The binomial distribution is the foundation of almost everything, describing the probability distribution of the number of successes \(k\) in \(n\) independent repeated experiments (Bernoulli trials).
...The binomial distribution is the foundation of almost everything, describing the probability distribution of the number of successes \(k\) in \(n\) independent repeated experiments (Bernoulli trials).
...The fundamental property of a matrix is the transformation space, so eigenvalues describe the scaling strength in a certain direction. Eigenvectors describe that direction.
...The determinant has nothing to do with “equations”, it is a scalar.
The determinant is only applicable to square matrices, describing the volume of n n-dimensional vectors. For two dimensions, it is the area. A determinant of zero indicates that the matrix cannot span an n-dimensional space, at most n-1 dimensions, i.e., not full rank. So the volume is zero in n dimensions.
...This is problem that you may encounter, and I found a simple way to calculate it. The result looks correct after comparing with the actual data. A website receives an average of 1000 requests per hour, and can only handle one at a time, taking 1 second. When a request arrives, if the previous one has not been completed, an error will occur. How many errors will occur on average in an hour?
...With a coding scheme where the minimum hamming distance between two valid codewords is m, it can detect r-bit errors at most when
...Matrix multiplication has four cases, but essentially they are all vector operations.
The variance measures the dispersion of a random variable, which is the expectation of the squared difference between each data point and the expectation.
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