You can easily calculate the standard error of the mean using functions contained within the base R package. Use the SD function (standard deviation in R) for standalone computations.
# Calculate Standard Error in R > product_tests <- c(15,13,12,35,12,12,11,13,12,13,15,11,13,12,15) # Calculate Standard Error in R # using the SD function / SQRT of vector length > sd(product_tests)/sqrt(length(product_tests))  1.519607
One annoying quirk of real life data sets is they often have missing values. You can use the na.rm option and na.omit function as noted below (for the standard deviation in r function) to clean up the missing values and calculate the standard error using only the real values of the series.
# Calculate Standard Error in R > product_tests <- c(15,13,12,35,12,12,11,13,12,13,15,11,13,12,15, NA, NA, NA) > product_tests  15 13 12 35 12 12 11 13 12 13 15 11 13 12 15 NA NA NA > sd(product_tests, na.rm=TRUE)/sqrt(length(na.omit(product_tests)))  1.519607
- Find the mean in R
- Calculate Standard Error in R
- Calculate Standard Deviation in R
- Calculate Variance in R
- Calculate Skewness in R
- Calculate Kurtosis in R
- Calculate Confidence Interval in R
- Using a Chi Square Test in R
- Power analysis in R
- Percentile in R
- Quartile in R