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Does the English system have a simple relationship between units of volume and cubed linear units?
Wiki User
∙ 10y ago
The English system does not have simple relationships of any kind, that is why scientists, and nearly the entire world other than the US, use the metric system.
Wiki User
∙ 10y ago
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How can you tell whether a linear function can be used to model a real life relationship?
You can create a scatter plot of the two variables. This may tell you if there is a relationship and, if so, whether or not it is linear. If there seems to be a linear relationship, you can carry out a linear regression. Note that the absence of a linear relationship does not mean that there is no relationship. The coordinates of the points on a circle do not show a linear relationship: the correlation coefficient is zero but there is a perfect and simple relationship between the abscissa and the ordinate. Even if there is evidence of a linear relationship, it may be valid only within the range of observations: do not extrapolate. For example, the increase in temperature of a body is linearly related to the amount of heat energy aded. However, for a solid, there will come a stage when the additional heat will not increase the temperature but will be used to melt (or sublimate) the solid. So the linear relationship will be broken.
Why is it important to look at a scatter plot prior to starting a simple linear regression?
To see if there is a linear relationship between the dependent and independent variables. The relationship may not be linear but of a higher degree polynomial, exponential, logarithmic etc. In that case the variable(s) may need to be transformed before carrying out a regression. It is also important to check that the data are homoscedastic, that is to say, the error (variance) remains the same across the values that the independent variable takes. If not, a transformation may be appropriate before starting a simple linear regression.
How you identify function based from graphs and equation?
An equation is the same as a function. Identifying a functional relationship from a graph is nearly impossible unless it is trivially simple like a linear relationship.
What is a curvilinear curve?
"In curvilinear relationships, the data points increase together up to a certain point (like a positive relationship) and then as one increases, the other decreases (negative relationship) or vice versa." A linear relation is very simple: if one variable goes up, the other goes up (positive correlation) or goes down (negative correlation). A curvilinear relation between variables is non-linear (i.e., that cannot be described by a straight line). Basically, anythig not linear is curvilinear.
What do you use when looking for a mathematical relationship between two variables?
The first step is to do a scatter plot. This will show if there is any relationship at all and, if there is, whether that relationship is linear or non linear, whether it remains the same throughout the domain or changes. As an example of the latter, think of the age and height of someone. The height starts off with birth height, grows quite rapidly for a few years, slows down pre-puberty, accelerates during puberty and then levels off. A very messy pattern. If there is a simple non-linear relationship you can try transforming one (or both) of the variables, and redraw the scatter plot. You can then try correlation or regression.
When would you use simple linear regression?
You use it when the relationship between the two variables of interest is linear. That is, if a constant change in one variable is expected to be accompanied by a constant [possibly different from the first variable] change in the other variable. Note that I used the phrase "accompanied by" rather than "caused by" or "results in". There is no need for a causal relationship between the variables. A simple linear regression may also be used after the original data have been transformed in such a way that the relationship between the transformed variables is linear.
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
How can you tell whether a linear function can be used to model a real life relationship?
You can create a scatter plot of the two variables. This may tell you if there is a relationship and, if so, whether or not it is linear. If there seems to be a linear relationship, you can carry out a linear regression. Note that the absence of a linear relationship does not mean that there is no relationship. The coordinates of the points on a circle do not show a linear relationship: the correlation coefficient is zero but there is a perfect and simple relationship between the abscissa and the ordinate. Even if there is evidence of a linear relationship, it may be valid only within the range of observations: do not extrapolate. For example, the increase in temperature of a body is linearly related to the amount of heat energy aded. However, for a solid, there will come a stage when the additional heat will not increase the temperature but will be used to melt (or sublimate) the solid. So the linear relationship will be broken.
Why is it important to look at a scatter plot prior to starting a simple linear regression?
To see if there is a linear relationship between the dependent and independent variables. The relationship may not be linear but of a higher degree polynomial, exponential, logarithmic etc. In that case the variable(s) may need to be transformed before carrying out a regression. It is also important to check that the data are homoscedastic, that is to say, the error (variance) remains the same across the values that the independent variable takes. If not, a transformation may be appropriate before starting a simple linear regression.
What similarities and differences do you see between the function and linear equations?
Linear equations are a tiny subset of functions. Linear equations are simple, continuous functions.
What is the relationship between apathy and sympathy?
simple...
How you identify function based from graphs and equation?
An equation is the same as a function. Identifying a functional relationship from a graph is nearly impossible unless it is trivially simple like a linear relationship.
What is relationship between absorption and percentage transmitance?
No particular relationship exists between the two for the simple reason that such relationship(if any exist) depends on the material one is concerned with.
What is the difference between English and Simple English?
Simplified English is English using simple vocabulary and sentence structure. English - normally is English is with sometimes sophisticated vocabulary and a range of sentence structures.
Why is a cascode current mirror better than a simple MOSFET current mirror?
In simple MOSFET current mirror, the load current does not follow a linear relationship with reference current (ie for short channel MOSFET's multiplying factor due to channel length modulation cannot be neglected). But by cascoding the output resistance can be increased and since output resistance follows an inverse relationship with lambda (channel-length modulation parameter), the multiplying factor due to channel length modulation reduces to one and a linear relationship is obtained between reference and load current.
How you recognize your data are chaotic?
There is no simple way. A scatter plot may help if there are at most two variables but they are difficult to read with several variables.A low absolute value for a regression coefficient simply means that there is not a linear relationship: the data could follow a non-linear relationship perfectly, for example.
Illustrate a linear view of a simple feeding relationship?
Well, take a bird's eye view of people having sex.. then show it to your girlfriend, and note her response.
