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Hi all, I recently tried to calculate the mean and the median just for one column. In this column I have numbers with some empty cells due to missing data. So how can I calculate the mean just for the filled cells? I tried: mean(dataSet2$ac_60d_4d_after_ann[!is.na(master$ac_60d_4d_after_ann)], na.rm=TRUE) But the output was different to the calculation I died in Microsoft Excel. Thanks in

Hi there, I am really new to statistics in R and statistics itself as well. My situation: I ran a lot of OLS regressions with different independent variables. (using the lm() function). After having done that, I know there is endogeneity due to omitted variables. (or perhaps due to any other reasons). And here comes the Hausman test. I know this test is used to identify endogeneity. But what I

Hi there, I tried it many times but didn't get it worked. I just want to export the summary of a OLS regression (lm() function) into a csv-file including the "call"-formula", "coefficients", "r-squared", " adjusted r-squared" and "f statistic". I know I can export: write.csv2(Regression_60d_ann$coefficients,

Hi there, I'm sorry for the bad subject decision. Couldn't describe it better... In my dataset called "dataSet" I want to create a new variable column called "deal_category" which depends on another column called "trans_value". In column "trans_value" I have values in USDm. Now what I want to do is to give these values a category called

Hi there, I tried this code from homepage: http://myowelt.blogspot.de/2008/04/beautiful-correlation-tables-in-r.html <http://myowelt.blogspot.de/2008/04/beautiful-correlation-tables-in-r.html> corstarsl <- function(x){ require(Hmisc) x <- as.matrix(x) R <- rcorr(x)$r p <- rcorr(x)$P ## define notions for significance levels; spacing is important. mystars <- ifelse(p <