a strong linear or nonlinear relationship D. that the data is inaccurate 相关知识点: 试题来源: 解析 C。两变量相关性很高意味着有强的线性或非线性关系。A 选项高相关性不意味着因果关系;B 选项也不一定是一个变量导致另一个;D 选项与数据是否准确无关。反馈 收藏 ...
A ___ can be used to visualize the correlation between two variables. A. pie chart B. bar graph C. line graph D. scatter plot 相关知识点: 试题来源: 解析 D。散点图可以用来可视化两个变量之间的相关性。饼图展示比例,柱状图比较类别,折线图展示趋势。反馈...
Method 2 – Using the Data Analysis ToolPak to Find the Correlation Between Two Variables Steps: Go to the File tab. Choose Options in the File tab. In the Excel Options window, go to Add-ins. Choose Excel Add-ins in Manage:. Select Analysis ToolPak in Inactive Applications Add-ins. ...
If the correlation between two variables is −1.0, the scatter plot would appear along a:A. straight line running from northwest to southeast.B. straight line running from southwest to northeast.C. a curved line running from southwest to northeast. 正确答案:A 分享到: 答案解析: If the cor...
Estimating the Correlation between Two Variables when Individuals are Measured RepeatedlyCudeck, Robert
The correlation coefficient between two variables is 0.8. This indicates a A. weak positive correlation B. strong positive correlation C. weak negative correlation D. strong negative correlation 相关知识点: 试题来源: 解析 B。本题考查相关性系数的理解。相关性系数为 0.8,大于 0 且接近 1,表明是强...
百度试题 结果1 题目A positive correlation between two variables means that as ___.相关知识点: 试题来源: 解析 答案:第一年年初 反馈 收藏
The R function cor() can be used to compute the correlation coefficient between two variables, x and y. A simplified format of the function is : # x and y are numeric vectors cor(x, y, method = c("pearson", "kendall", "spearman")) - The pearson correlation method computes a parame...
TheKendall correlationmethod measures the correspondence between the ranking of x and y variables. The total number of possible pairings of x with y observations isn(n−1)/2n(n−1)/2, where n is the size of x and y. The procedure is as follow: ...
A correlation is a statistical measure of the relationship between two variables. It is best used in variables that demonstrate a linear relationship between each other.