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Hypothesis Testing for Diffrence of Average

Hypothesis testing for diffrence of average is the most used hypothesis testing in SPC .

Basic way of this testing is for the difference between 2 groups.

Difference of Average between 2 Groups

There are 2 methods, Student's t-test and Welch's t-test.

Student's t-test needs "variance is equal". But Welch's do not need.

Example by R

In Excel, ttest function is for this test.

Student's t-test

Data <- read.csv("Data.csv", header=T)
t.test(x=Data$X1,y=Data$X2,var.equal=T,paired=F) # Student's t-test

Welch's t-test

Data <- read.csv("Data.csv", header=T)
t.test(x=Data$X1,y=Data$X2,var.equal=F,paired=F) # Welch's t-test

ANOVA and Paired t-test

ANOVA is used for the case that more than 3 groups. Paired t-test is used for the paired data.

These methods have other use.



I think R-QCA1 is a good way to compare Before-After . You can prepare and read a csv file that contains the data of the group you want to compare in the first and second columns.


In R-EDA1 , if you select "Basic_test_All_Varaiables", each variable is stratified based on the variable of the label, and for all the variables, the difference between the average values of the groups with labels 0 and 1 can be tested. .. Only the p-value is output.

NEXT Reinforcement the test in the meaning of difference