Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|

linearly dependent and independent vectors | 0.72 | 0.3 | 1164 | 88 | 42 |

linearly | 0.79 | 0.2 | 6073 | 58 | 8 |

dependent | 0.66 | 0.5 | 8642 | 27 | 9 |

and | 1.04 | 1 | 6688 | 38 | 3 |

independent | 1.23 | 0.7 | 9021 | 61 | 11 |

vectors | 1.9 | 0.9 | 4990 | 44 | 7 |

Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|

linearly dependent and independent vectors | 0.45 | 0.6 | 564 | 22 |

linearly dependent vs independent vectors | 1.24 | 0.6 | 3615 | 95 |

what are linearly independent vectors | 2 | 0.6 | 8095 | 63 |

what is linearly dependent vectors | 1.01 | 0.8 | 5007 | 22 |

what is linearly independent vectors | 0.31 | 0.3 | 6567 | 45 |

are these vectors linearly independent | 1.98 | 0.5 | 2324 | 1 |

define linearly independent vectors | 1 | 0.6 | 7138 | 59 |

define linearly dependent vectors | 1.44 | 0.7 | 5600 | 36 |

meaning of linearly independent vectors | 0.15 | 0.4 | 7933 | 26 |

linearly dependent vectors definition | 1.42 | 0.6 | 9597 | 13 |

linearly independent vectors definition | 1.16 | 0.2 | 4746 | 83 |

vectors that are linearly independent | 1.22 | 0.6 | 2061 | 64 |

vectors are linearly independent | 0.39 | 0.6 | 3979 | 39 |

your vectors are linearly dependent | 1.93 | 0.2 | 802 | 28 |

what is a linearly independent vector | 1.83 | 0.5 | 2924 | 79 |

linear dependence and independence of vectors | 0.48 | 1 | 9848 | 75 |

when is a vector linearly dependent | 0.03 | 0.5 | 8036 | 6 |

linearly independent vector definition | 1.52 | 0.2 | 4839 | 67 |

what makes a vector linearly independent | 0.87 | 0.3 | 7616 | 92 |

set of vectors is linearly independent: A set of n vectors of length n is linearly independent if the matrix with these vectors as columns has a non-zero The set is of course dependent if the determinant is zero. Example The vectors <1,2> and <-5,3> are linearly independent since the matrix has a non-zero determinant. Example

The vectors a 1, ..., a n are called linearly independent if there are no non-trivial combination of these vectors equal to the zero vector. That is, the vector a 1 , ..., a n are linearly independent if x 1 a 1 + ... + x n a n = 0 if and only if x 1 = 0, ..., x n = 0.

The relationship of the dependent variable and each of the independent variables can be direct or inverse. In a direct relationship, a higher value of the independent variable is related to a higher value of the dependent variable (or vice-versa). Mathematically, a direct relationship is also a positive relationship.