" He continues by explaining that because 1 ≠ -1, the definition in Eq. (4) must be an "erroneous definition." Thus, he instructs, we cannot say "j is equal to the square root of negative one." I disagree, and here's why. The impossible result of 1 = -1 in Eq. (6) is ...
The reason I do not consider this equation to be as profound as is sometimes claimed is because that first equation is really a disguised way of saying that the cosine of 180 degrees is equal to minus one. But to understand why that is, it is necessary to understand a fair amount of m...
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After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help me to remember and to anyone who would like to know about it. I've skipped some contents in some lectures as it wasn't important to ...
It is responsible for sensing the oxygen levels via the heme signaling pathway, and activation of the oxidative stress response genes [10]. Overexpression (OE) of HAP1 in S. cerevisiae overproducing a secretory r-Prot led to the mitigation of the negative effects caused by reactive oxygen ...
Eigenvalues were calculated as the sum of squared factor loadings across all items for each factor. This value represents the proportion of variance in each item that can be explained by the analysis. To determine the percentage of total variance explained by each factor, the eigenvalue is ...
I went through all of the this work to show that the maximum point of the parabola (the highest point in the kangaroo's jump) is actually the point where the value being squared is 0 (14 - 14). The y-value of the vertex is 6. That is also the highest point in the jump. The ...
1. Russell 2000® Index is an unmanaged index of 2,000 U.S. small-cap stocks. Unless otherwise stated, index returns do not reflect the effect of any applicable sales charges, commissions, expenses, taxes or leverage, as applicable. It is not possible to invest directly in an index. ...
The least squares regression method is generally used for developing your prediction line and thus your prediction model. The calculation involves squaring the raw residuals and then moving the line around until the location of the line minimizes the sum of the squared residuals. ...