Ví dụ về việc sử dụng Regression analysis trong Tiếng anh và bản dịch của chúng sang Tiếng việt
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The scatter plot and regression analysis suggests a negative relationship.
Trendlines are used for the study of problems of prediction,also called regression analysis.
This fade period is estimated using regression analysis, and estimates vary widely.
Want to perform sophisticated what-if analysis operations on your data, such as statistical,engineering, and regression analysis.
The derivation procedure employed multiple regression analysis[Sen and Srivastava 1990].
Regression analysis is also used to understand which among the independent variables is related to the dependent variable, and to explore the forms of these relationships.
This is even below the expected rate after the regression analysis that controlled for age, sex, race, and income.
Next you should test the effect of the combination of these independent variables ordrivers by using multiple regression analysis software.
Simple statistical methods- mainly regression analysis- were used in most instances, without any clear probability theory assumptions whatsoever.
Market survey/ processing/ editing the survey data torun a factor analysis results converged, the regression analysis statistical significance.
For example, regression analysis may be used to model whether a change in advertising(independent variable X) explains the variation in sales(dependent variable Y).
By means of time series for the variables gt and xt, the parameters a andb can be estimated using statistical methods(known as regression analysis).
Since the true form of the data-generatingprocess is generally not known, regression analysis often depends to some extent on making assumptions about this process.
The performance of regression analysis methods in practice depends on the form of the data generating process and how it relates to the regression approach being used.
HRI used a variety of metrics in order to quantify and analyze BTS's economic effect,including Google trends, regression analysis, interindustry analysis, .
This was the methodologyused:“The predictions for each match are based on a regression analysis that uses the entire history of mandatory international football matches- that is, no friendlies- since 1960.
It used regression analysis, which looked at the relationship between a child's height and household, social and environmental variables that might impact on a child's height, including sanitation.
They studied"the long-term effects of growing up in, and living in,a polluted atmosphere," using economists' favorite statistical technique- regression analysis- to look at a few locales where data were available.
Simple linear regression analysis is a statistical tool for quantifying the relationship between just one independent variable(hence“simple”) and one dependent variable based on past experience(observations).
In the position paper titled:“Telco: Investment, Innovation and Competition in ICT Infrastructure”, Huawei said the development trends of ICT as observed around the globe and their potential social economic development spurred by ICT,after conducting a regression analysis based on a data set of 125 countries for the period 2010 to 2016.
In regression analysis involving time series data, if the regression model includes not only the current but also the lagged(past) values of the explanatory variables(the X's), it is called a distributed-lag model.
For example,a manufacturer may have found through simple linear regression analysis involving 15 monthly observations that 64% of the change in the total cost of electricity(the dependent variable) was associated with the change in the monthly production machine hours(the independent variable).
Regression analysis uses all of the monthly electricity bill amounts along with their related number of equipment hours in order to calculate the monthly fixed cost of electricity and the variable rate for each equipment hour.
More particularly, regression analysis assists one comprehend how the common worth of the reliant variable(or‘requirement variable') modifications when any one of the independent variables is differed, while the other independent variables are held repaired.
Regression analysis may be used when the analyst is trying to determine the extent to which independent variable X affects dependent variable Y(e.g.,“To what extent do changes in the unemployment rate(X) affect the inflation rate(Y)?”).
He added that regression analysis can be used for production forecasting based on a current set of variables(i.e. any data point) to determine, for example, what will be produced on a single line or overall by the end of a shift.
Linear regression analysis showed that in addition to four factors: the nature of work, relationships with colleagues, development opportunities and the support of superiors, the time working in the department also affects the satisfaction of lecturers.
Whereas(multiple) regression analysis uses additive logic where each X-variable can produce the outcome and the X's can compensate for each other(they are sufficient but not necessary), necessary condition analysis(NCA) uses necessity logic, where one or more X-variables allow the outcome to exist, but may not produce it(they are necessary but not sufficient).