0
Still curious? Ask our experts.
Chat with our AI personalities
Beau
Devin
CoachAdd your answer:
Earn +20 pts
What is positive linear relationship?
Positive Linear Relationships are is there is a relationship in the situation. In some equations they aren't linear, but other relationships are, that's a positive linear Relationship.
What measures the strength of the linear relationship between two quantitative variables?
The strength of the linear relationship between two quantitative variables is measured by the correlation coefficient. The correlation coefficient, denoted by "r," ranges from -1 to 1. A value of 1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 indicates no linear relationship. The closer the absolute value of the correlation coefficient is to 1, the stronger the linear relationship between the variables.
How many types of correlation?
There are 3 types1.positive/ negative/zero/2.linear/non-linear3.simple/multiple/partial- If the direction is same,the relationship is positive-If the direction is opposite , the relationship is negative-If the amount of change is constant in different variable it is linear-If the amount of change is not constant in different variable is non- linear-If it is establishing a relationship between two characteristic then it is simple- If it is establishing a relationship between three or more characteristic then it is multiple-If it is establishing a relationship between only one of all the variable then it is partial
What does it means The strength and direction of a linear relationship between two variables?
The direction of a linear relationship is positive when the two variables increase together and decrease together. The direction is negative if an increase in one variable is accompanied by a decrease in the other. The strength of the relationship tells you, in the context of a scatter plot of the two variables, how close the observations are to the line representing the linear relationship. There are various very closely related measures: regression coefficient or product moment correlation coefficient (PMCC) are commonly used. These can take any value between -1 and +1. A value of -1 represents a perfect negative relationship, +1 represents a perfect positive relationship. A value of 0 represents no linear relationship (there may be a non-linear one, though). Values near -1 or +1 are said show a strong linear relationship, values near 0 a weak one. There is no universal rule about when a relation goes from being strong to moderate to none.
Linear regression r square?
r square is a measure of the linear relationship between the variables. The nearer r squared is to one, the stronger the linear relationship. However, a linear relatinship is NOT a causal relationship. Also the absence of a large r square is not evidence of no relationship: there may well be a non-linear relationship. It is commonly accepted that for scientific purposes, a very minimum of 0.98 is accepted for r2. This is because 0.98 actually allows for quite a variance (by eye)
