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If your dependent variable is dummy coded (binary) then you must use a logistic regression for you analysis. There are two types; logit and probit. Both types return very similar results and your decision on which to use is based on personal preference and discipline standards. Economics and marketing tend to use probit while sociology tends to use logit.
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How can i use the word regression in a sentence?
Her regression is smoking.
When you introduce more than one independent variable into a linear regression analysis?
Generally, when the dependent variable appears to be the result of more than one independent variables, a multiple regression model may be suitable. It is difficult to justify adding an additional variable, that does not significantly reduce the residual error of the fit. The setting of thresholds to justify addition of variables is in the area of "stepwise regression." The data must be adequate and consistent with the assumption of independent variables. I note from the first related link: Most authors recommend that one should have at least 10 to 20 times as many observations (cases, respondents) as one has variables, otherwise the estimates of the regression line are probably very unstable and unlikely to replicate if one were to do the study over. See related links. Many more are available in the Internet. Also, many books have been written on the multiple regression- proper and improper use.
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.
What is an example sentence with the word regression?
i know the facts. What is the reason? For your Regression?
What is alpha in regression analysis?
Alpha is not generally used in regression analysis. Alpha in statistics is the significance level. If you use a TI 83/84 calculator, an "a" will be used for constants, but do not confuse a for alpha. Some may, in derivation formulas for regression, use alpha as a variable so that is the only item I can think of where alpha could be used in regression analysis. Added: Though not generally relevant when using regression for prediction, the significance level is important when using regression for hypothesis testing. Also, alpha is frequently and incorrectly confused with the constant "a" in the regression equation Y = a + bX where a is the intercept of the regression line and the Y axis. By convention, Greek letters in statistics are sometimes used when referring to a population rather than a sample. But unless you are explicitly referring to a population prediction, and your field of study follows this convention, "alpha" is not the correct term here.
What serves as a standard of comparison to evaluate the effect of the dependent variable on the dependent variable?
ControlThe answer will depend on the nature of the effect. IFseveral requirements are met (the effect is linear, the "errors" are independent and have the same variance across the set of values that the independent variable can take (homoscedasticity) then, and only then, a linear regression is a standard. All to often people use regression when the data do not warrant its use.
How do you use the word dependent variable in a sentence?
the water in the experiment was the dependent variable in this situation
How do you use dependent variable in a sentence?
You could say, "Today in our science experiment we had to figure out what the dependent variable was"
Can you help me use responding variable or a dependent variable in a sentence?
yes
What serves as a standard of comparison to evaluate the effect of the independent variable on the dependent variable?
The control group serves as a standard of comparison to evaluate the effect of the independent variable on the dependent variable. By comparing the results of the experimental group receiving the independent variable with the control group, researchers can isolate the effect of the independent variable on the dependent variable.
Does the dependent number go on the Y-Axis?
Yes, the usual case in mathematics is to use the the y-axis variable as the dependent variable.
is it possible to use primary data as independent variable and secondary data as independent variable in correlation analysis and regression analysis?
Possible maybe
The letter y is most frequently use as?
The dependent variable.
What is the difference between independent variables and dependent variables?
The independent variable is the variable being manipulated in the experiment in order to show the effect on the dependent variable. It is also called the experimental variable.The dependent variable is the variable being observed in the experiment. Changes in the dependent variable as a result of changes in the independent variable are observed, which is the purpose of the experiment. Dependent variable is also called the response variable.
How does the manipulation of an independent variable during a scientific experiment allow a scientist to find a cause-and-effect relationship between variables?
The independent variable, or manipulating variable always affect the outcome of a dependent, or responsive, variable. For example, i have a fire going, and i want to put it out. I could use a range of materials. The range of materials is the independent variable, while the fire going out or not is the dependent variable. This shows a cause and effect.
Which factor in an experiment would a scientist use like a simile?
dependent variable
What is the variable you use during the part of an experiment that is being tested?
The variable being tested is called the independent variable. This is the variable that is deliberately changed by the experimenter to observe its effect on the dependent variable.
