auto correlation function of a stationary process is an even function
Chat with our AI personalities
It stands for pooping in the bathroom like dogs do in the winter. : D
we can use timeseries in forecasting future values depending upon current and past values. we can also construct ACF and PACF plots and can know how many spikes are there in linear stationary models.
20: abc, abd, abe, abf, acd, ace, acf, ade, adf, aef, bcd, bce, bcf, bde, bdf, bef, cde, cdf, cef, def.
If you can only take one of each letter, it would be 19: abc, abd, abe, abf, acd, ace,acf,ade,adf,aef, bcd, bce, bcf, bde, bdf, bef, cde, cdf ,def.
Yes. Read on for why: Take a parallelogram ABCD with midpoints E and F in the bases. So something like this (forgive the "drawing"): A E B __.__ /__.__/ C F D We know that parallelogram AEFC = EBDF, since they have the same base (F bisects CD, so CF = FD), height (haven't touched that), and angles (<ACF = <EFD because they're parallel - trust me that everything else matches). We also know that every parallelogram can be divided into two congruent triangles along their diagonal. So if two congruent parallelograms consistent of two congruent triangles each, then all four triangles are congruent. So your congruent triangles are ACF, AEF, EFD, and EBD. You can further reinforce this through ASA triangle congruency proofs (as I did at first), but this is a far more concise and equally valid answer.