If the value (not mean value) of y is related negatively to the value of x then larger values of x are associated with smaller values of y.
8ft by 4 ft by 2 ft is a measure of volume. Simple dimensional analysis teaches that a volume cannot be related to an area (square feet) without additional information.
hero is related to good as villain is related to evil.
showing data and seeing if it's closely related or not related at all
No. The word strength is a noun. The related adjective is strong and the related adverb is "strongly."
There are infinitely many possible ways in which two variables can be related to one another.
Correlation and regression analysis can help business to investigate the determinants of key variables such as their sales. Variations in a companies sales are likely to be related to variation in product prices,consumers,incomes,tastes and preference's multiple regression analysis can be used to investigate the nature of this relationship and correlation analysis can be used to test the goodness of fit. Regression can also be used to estimate the trend in a time series to make forecast
Correlation and regression analysis can help business to investigate the determinants of key variables such as their sales. Variations in a companies sales are likely to be related to variation in product prices,consumers,incomes,tastes and preference's multiple regression analysis can be used to investigate the nature of this relationship and correlation analysis can be used to test the goodness of fit. Regression can also be used to estimate the trend in a time series to make forecast
one dependent and one or more independent variables are related.
They are positively, or directly related. An increase in income is associated with an increase in income; a decrease in consumption accompanies a decrease in income.
Statistical analysis that describes the changes in a dependent variable, such as sunglass sales volumes, associated with changes in one or more independent variables, such as the average age of the residents of a market area. For example, a multiple-regression analysis might reveal a positive relationship between demand for sunglasses and various demographic characteristics (age, income) of the buyers-that is, demand varies directly with changes in their characteristics. Multiple regression thereby helps marketers to identify their best prospects.For the source and more detailed information concerning this subject, click on the related links section (Answers.com) indicated below.
There are numerous ways to do this. I think the easiest is to put the data in excel and have excel show the trend line, equation, andcorrelation coefficient. Excel gives you several options to choose for the trend line analysis. The other way is if it is a linear relationship, you can do the linear regression analysis following the steps listed in the related link. If you are not familiar with regression analysis, it may not be easy for you to follow.
Frank M. Andrews has written: 'The quality of survey data as related to age of respondent' -- subject(s): Age, Sampling (Statistics), Surveys 'Multiple classification analysis' -- subject(s): Computer programs, Discriminant analysis, Mathematical statistics, Multivariate analysis, Regression analysis
I am hoping that this hot toddy will aid in the regression of the symptoms related to my common cold. The retrograde motion of stars is sometimes referred to as their regression.
The question is vague. Regression can be a complex analysis, and which information is important depends greatly on what you are using the results for. But very generally, if you are using regression as a hypothesis test, then the F (test statistic), r-square (effect size), and p (significance level), will be important. If you are using regression for predicting a value of Y based on X, then the slope of the regression line (b) and its intercept with the Y axis (a) are needed for the regression equation: Y = a + bX. Computer programs such as SPSS also test the statistical significance of both the intercept and the slope by comparing them to zero, and they will report several other numbers related to these tests. However, this may or may not be information that the researcher is interested in. Again, it all depends on the situation.
Multi-collinearity occurs when two or more "explanatory" variables in a regression analysis are related to one another in such a way that the values of at least one of these variables can be very accurately determined by the others.
in general regression model the dependent variable is continuous and independent variable is discrete type. in genral regression model the variables are linearly related. in logistic regression model the response varaible must be categorical type. the relation ship between the response and explonatory variables is non-linear.
The related adverb is regressively. It is the adverb form of the derivative adjective regressive.