1. Nhập dữ liệu

Dữ liệu được nạp trực tiếp vào R để phân tích.

data_string <- "layer_height,wall_thickness,infill_density,infill_pattern,nozzle_temperature,bed_temperature,print_speed,material,fan_speed,roughness,tension_strength,elongation
0.02,8,90,grid,220,60,40,abs,0,25,18,1.2
0.02,7,90,honeycomb,225,65,40,abs,25,32,16,1.4
0.02,1,80,grid,230,70,40,abs,50,40,8,0.8
0.02,4,70,honeycomb,240,75,40,abs,75,68,10,0.5
0.02,6,90,grid,250,80,40,abs,100,92,5,0.7
0.06,10,80,grid,200,60,60,pla,0,125,27,2.1
0.06,5,10,honeycomb,205,65,60,pla,25,95,12,1.1
0.06,10,10,grid,210,70,60,pla,50,110,9,0.9
0.06,9,70,honeycomb,215,75,60,pla,75,121,24,1.5
0.06,2,40,grid,220,80,60,pla,100,149,18,1.4
0.1,1,50,grid,200,60,120,abs,0,224,19,1.8
0.1,10,50,honeycomb,205,65,120,abs,25,145,26,2.1
0.1,4,50,grid,210,70,120,abs,50,153,14,1.1
0.1,6,10,honeycomb,215,75,120,abs,75,212,24,2.2
0.1,3,50,grid,220,80,120,abs,100,168,10,0.8
0.1,10,90,honeycomb,220,60,60,pla,0,126,27,2.2
0.1,2,90,grid,225,65,60,pla,25,145,23,1.9
0.1,8,40,honeycomb,230,70,60,pla,50,121,26,2.4
0.1,5,80,grid,240,75,60,pla,75,115,19,1.7
0.1,7,50,honeycomb,250,80,60,pla,100,122,23,2.1
0.15,1,10,grid,200,60,40,abs,0,192,12,1.1
0.15,4,30,honeycomb,205,65,40,abs,25,212,14,1.2
0.15,2,50,grid,210,70,40,abs,50,168,10,0.8
0.15,8,70,honeycomb,215,75,40,abs,75,118,28,2.7
0.15,10,90,grid,220,80,40,abs,100,92,28,2.8
0.15,1,90,honeycomb,220,60,120,pla,0,200,35,3.3
0.15,4,40,grid,225,65,120,pla,25,176,12,1.1
0.15,3,50,honeycomb,230,70,120,pla,50,128,29,2.8
0.15,9,90,grid,240,75,120,pla,75,138,34,3.1
0.15,7,20,honeycomb,250,80,120,pla,100,121,14,1.5
0.2,4,10,grid,200,60,60,abs,0,168,7,0.7
0.2,7,10,honeycomb,205,65,60,abs,25,154,19,1.8
0.2,6,50,grid,210,70,60,abs,50,225,18,1.4
0.2,1,50,honeycomb,215,75,60,abs,75,289,9,0.8
0.2,10,80,grid,220,80,60,abs,100,326,24,2.3
0.2,3,80,honeycomb,220,60,40,pla,0,192,33,2.8
0.2,4,90,grid,225,65,40,pla,25,212,24,2.2
0.2,10,30,honeycomb,230,70,40,pla,50,168,26,2.1
0.2,8,40,grid,240,75,40,pla,75,118,22,1.9
0.2,9,90,honeycomb,250,80,40,pla,100,92,37,3.3
0.02,9,50,grid,200,60,40,abs,0,212,15,1.3
0.02,6,40,honeycomb,225,65,40,abs,25,168,12,1.1
0.02,10,30,grid,210,70,40,abs,50,118,11,0.9
0.02,8,80,honeycomb,215,75,40,abs,75,92,26,2.4
0.02,3,70,grid,250,80,40,abs,100,212,12,1.1
0.06,8,70,honeycomb,200,60,60,pla,0,168,28,2.7
0.06,4,30,grid,205,65,60,pla,25,118,12,1.1
0.06,5,90,honeycomb,210,70,60,pla,50,92,28,2.8
0.06,10,50,grid,215,75,60,pla,75,212,19,1.7
0.06,1,20,honeycomb,220,80,60,pla,100,168,10,0.8"

new_DF <- read.csv(text = data_string)
abs_data <- subset(new_DF, material == "abs")
pla_data <- subset(new_DF, material == "pla")

2. Kiểm tra phân phối chuẩn (QQ-plot và Shapiro.test)

Đối với vật liệu ABS:

qqnorm(abs_data$tension_strength, main = "Normal Q-Q Plot - ABS Data")
qqline(abs_data$tension_strength)

shapiro.test(abs_data$tension_strength)
## 
##  Shapiro-Wilk normality test
## 
## data:  abs_data$tension_strength
## W = 0.93184, p-value = 0.09585

Đối với vật liệu PLA:

qqnorm(pla_data$tension_strength, main = "Normal Q-Q Plot - PLA Data")
qqline(pla_data$tension_strength)

shapiro.test(pla_data$tension_strength)
## 
##  Shapiro-Wilk normality test
## 
## data:  pla_data$tension_strength
## W = 0.95617, p-value = 0.3434

3. Kiểm định phương sai (F-test)

var.test(tension_strength ~ material, data = new_DF, alternative = "greater")
## 
##  F test to compare two variances
## 
## data:  tension_strength by material
## F = 0.7321, num df = 24, denom df = 24, p-value = 0.7747
## alternative hypothesis: true ratio of variances is greater than 1
## 95 percent confidence interval:
##  0.3690467       Inf
## sample estimates:
## ratio of variances 
##             0.7321

4. Kiểm định T-test hai mẫu độc lập

Do phương sai bằng nhau, ta dùng var.equal = TRUE.

t.test(tension_strength ~ material, data = new_DF, var.equal = TRUE)
## 
##  Two Sample t-test
## 
## data:  tension_strength by material
## t = -3.3117, df = 48, p-value = 0.001767
## alternative hypothesis: true difference in means between group abs and group pla is not equal to 0
## 95 percent confidence interval:
##  -11.314164  -2.765836
## sample estimates:
## mean in group abs mean in group pla 
##             15.80             22.84