14.1 Types of Relationship Between Two Variables
14.1.1 Associative Analyses
Associative analyses(相关分析): determine where stable relationships exist between two variables
Examples
哪种经营方式与消费者满意度相关?
哪些人口统计特征变量与消费者对A产品的再次购买有关?
销售代表的培训方式是否与销售绩效相关?
新产品的购买意向是否与该产品的真实销量有关?
相关性≠因果关系
相关性
变量A的变化总是伴随变量B的变化,没有方向性。
例:太阳镜的销售量和雪糕的销售量是存在相关性。
因果关系
变量A的变化总是引起变量B的变化,有方向性。
例:下雨天导致燕子低飞。
14.1.2 Relationships Between Two Variables
Relationship: a consistent, systematic linkage between the levels or labels for two variables
“Levels” refers to the characteristics of description for interval or ratio scales.
“Labels” refers to the characteristics of description for nominal or ordinal scales.
(1)Nonmonotonic relationship(非单向关系): two variables are associated, but only in a very general sense. The presence (or absence) of one variable is associated with the presence (or absence) of another.
一个变量的出现(或不出现)与另一变量的出现(或不出现)存在联系。
“非单调”:这种联系没有明确的方向性,但联系确实存在。
(2)Monotonic relationship(单向关系): the general direction of a relationship between two variables is known
Increasing relationship
Decreasing relationship
(3)Linear relationship(线性关系): “straight-linear association” between two variables
(4)Curvilinear(曲线关系): some smooth curve pattern describes the association

