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QUESTION
Discuss the Difference Between a Positive Linear Relationship and a Negative Linear Relationship
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Statistics |
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2 |
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APA |
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Answer
Positive and Negative Linear Relationships
A linear relationship basically implies that the relationship between binary sets of variables can be displayed using a line. In simpler terms, one is able to identify a straight line without covers on a linear line. Linear relationships can be assessed using positive and linear relationship (Faraway, 2016). Therefore, this paper will assess the differences between negative and positive linear relationships. A positive linear relationship is represented by a line on a graph travelling up and from left to right. This relationship shows a stable rate of increase and implies that the dependent variable or the forecast appears to increase as the independent variable equally escalates (Faraway, 2016). Here, the scatter about a line is relatively small, which implies that there is a stout linear relationship. The line slope is positive because the units of X directly correspond to the small units of Y, and that the larger units of X equally correspond larger units of Y, which altogether form a positive co-relation between X and Y (Faraway, 2016).
Fig 1: A diagrammatic representations of Positive and Negative Linear relationships
Contrarily, a negative linear relationship occurs when a straight line goes downwards from the left side to the right. This is a reflection of a stable rate of decline. It implies that the two variables under test share an inverse relationship since as a variable increases, the other tends to decrease. Any slight fluctuation in the dependent variable causes a conforming fluctuation on the dependent variable. The line’s gradient is therefore negative. In conclusion, negative and positive linear relationships facilitate the definitions of linear correlations. As previously explained, the tow correlations have a number of differences.
References
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Faraway, J. J. (2016). Linear models with R. Chapman and Hall/CRC.
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