每次做回归(regression)的时候,只用一年的数据,例如:Y是2005年的stock return,X是2005年的NIit,2005年的Qit,2005年的LEVit,等等等等(X要用到除了stock return之外的那些数据)。我用excel做的时候,一旦选择了多个X进行回归(regression)的时候,... 展开 匿名 | 浏览2948 次 |举报 我有更好的答案推荐于2017-12-...
比如：A1为a值，B1为b值，C1为C值，D1为X值，最后结果为E1。接着你在菜单里找出“插入--图表”，其中有柱形的，折线形的，饼图的，散点形的等等。你可以选择折线形的，点击折线形图表，会出现相应的对话框（因为不知道楼主用的是什么版本，所以在这里只有笼统的说明），在里面添加“最后结果为E1...
How To Run A Multiple Regression In Excel And Actually Understand The ResultsSara Silverstein
文档介绍:Statistics for Managers Using Microsoft® Excel 5th EditionChapter 14Introduction to Multiple RegressionChap 14-1Learning ObjectivesIn this chapter, you learn:How to develop a multiple regression modelHow to interpret the regression coefficientsHow to determine which independent variables to ...
如何用excel进行多元回归（multiple regression）？你应该是用加载项里的数据分析吧，你的X要连起来，比如...
A normal probability plot of the Y data does not provide any useful information and the checkbox that would produce that graph is therefore not checked. It is unclear why Excel includes that functionality with its regression data analysis tool. ...
Multiple lineare Regression Hello, the regrssion tool doesn't allow more than 16 variables in excel. I need 31 variables. What can I do now? Larissa 31 variables, wow. Perhaps this is out of Excel's league? Do you mean 31 'x' variables?
The output results of the regression tell us how well we can explain the data sample, but cannot give us an accurate measure of how the model will predict a salary increase. To explore this, we should do the following: Obtain a different sample of the payroll (in our case, we could ge...
Doubly aligned IMC (DAIMC) [73] integrated a weighted semi-NMF and a l2,1-norm regularized regression model. It considered feature alignment and different basis matrices alignment simultaneously. Partial multi-view clustering with locality graph regularization (PMVC-LGR) [74] They integrated a ...
87] were eventually included in this model. Attempts to improve the model (i.e., omitting the values that contributed least to the overall effect) resulted in a decrease of the estimates. As such, a better model could not be constructed. A visual representation of the regression can be ...