Statistic


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There are four general relationship types between variables that may be determined in research. A variable can be described as a situation, behavior or characteristic that varies (Cozby & Bates, 2015). These relationships are the positive linear relationship, negative linear relationship, no relationship between variables, and the curvilinear relationship. The positive linear relationship occurs when there is an increase in both of the values of the variables that are present in the research problem/ experiment (Cozby & Bates, 2015). For example, a scientist notices that tall people tend to have a larger shoe size, while those who are not as tall tend to have a smaller shoe size. The scientist tests 100 people (50 men, and 50 women). The scientist defines “tall” for men as being 6ft or taller, and for women, 5ft7in or taller. The scientist observes in both women and men that as their height increased, the size of the shoe also increased. The scientist is able to observe and conclude that there is a positive relationship between an increase in a person’s height and the increase in their shoe size.

References

Cozby, P. C., & Bates, S. C. (2015). Methods In behavioral research (12th ed.). Boston, MA: McGraw-Hill Higher Education. Retrieved from https://phoenix.vitalsource.com/#/books/1259798283/cfi/6/20!/4/4/4@0.00:0

Cozy & Bates (2015), some variables have true numeric values whereas the levels of other variables are simply different categories (p. 76). What I have gathered is the correlations between the different variables can show whether two variable move in the same direction (positive), if the variables move in opposite direction (negative), whether the variables remain consist, or change at least once (curvilinear), or shows no change between two variables (no relationship).

According to Cozy and Bates they listed the differences as following:

Positive Linear Relationship

In a positive linear relationship, increases in the values of one variable are accompanied by increases in the values of the second variable (p. 76).

Negative Linear Relationship

In a negative linear relationship, increase in the values of one variable are accompanied by decreases in the values of the other variable (p. 77).

Curvilinear Relationship

In a curvilinear relationship, increases in the values of one variable are accompanied by systematic increases and decreases in the values of the other variable. In other words, the direction of the relationship changes at least once (p.78).

No Relationship

When there is no relationship between the two variables, the graph is simply a flat line.

 
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