I want to determine whether the means of my data set are significantly different. More specifically the means of the columns: 'avecbioparticules', 'cytochalasine' and 'nocodazole'.
I need to conduct two tests: ANOVA and Tukey post-hoc.
Here's my data set followed by the mean of each test conduct:
structure(list(equipe_groupe_a = c("1_plot_2", "2_plot_4", "3_plot_9", "4_plot_10", "5_plot_14", "6_plot_12", "7_plot_13", "moyenne_groupe_a" ), sansbioparticules = c(3509.38, 3000.17, 2649.73, 3144.21, 2568.15, 3683.09, 3079.8, 3090.64714285714), avecbioparticules = c(39943.1, 196243.66, 217530.19, 208580.65, 141190.58, 36057.75, 215243.31, 150684.177142857), cytochalasine = c(7803.43, 16167.45, 35824.48, 20455.36, 63512.36, 13987.32, 22140.02, 25698.6314285714), nocodazole = c(24646.26, 110821.01, 115812.52, 180575.51, 135193.28, 25954.82, 85538.64, 96934.5771428571)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -8L))
I know I've skipped steps but this is I tried so far: anova<-aov(donnees_phagocytose$moyenne_groupe_a, donnees_phagocytose)
Error in x$terms %||% attr(x, "terms") %||% stop("no terms component nor attribute") :
no terms component nor attribute
In addition: Warning message:
Unknown or uninitialised column: `moyenne_groupe_a`