Unpaired, one-tailed t-test — Use to compare two between-participants conditions where the alternative hypothesis suggests that the treatment condition causes an increase in the dependent variable: t.test(mydata_scales~mydata_conditions, alternative="less", paired = FALSE, var.equal=TRUE, conf.level=.95)

Eve multiboxingA hypothesis test can help determine if a difference in the estimated proportions reflects a difference in the population proportions. The difference of two proportions follows an approximate normal distribution. Generally, the null hypothesis states that the two proportions are the same.

value that occurs most frequently in population : MR: mid-range: MR = (x max + x min) / 2 : Md: sample median: half the population is below this value : Q 1: lower / first quartile: 25% of population are below this value : Q 2: median / second quartile: 50% of population are below this value = median of samples : Q 3: upper / third quartile: 75% of population are below this value : x