Academic Integrity: tutoring, explanations, and feedback — we don’t complete graded work or submit on a student’s behalf.

I generated predictions and their summaries. Do you notice anything odd about th

ID: 3318059 • Letter: I

Question

I generated predictions and their summaries. Do you notice anything odd about the predictions? Why might this have happened?

# For model 1
mod_preds <- predict(mod, type="response")
summary(mod_preds)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.192 1.206 1.247 1.240 1.271 1.292

# For model 2
mod_2_preds <- predict(mod_2, type="response")
summary(mod_2_preds)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.034 1.060 1.103 1.265 1.288 3.132

# For model 3
mod_3_preds <- predict(mod_3, type="response")
summary(mod_3_preds)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.014 1.051 1.091 1.265 1.270 3.792

# For model 4
mod_4_preds <- predict(mod_4, type="response")
summary(mod_4_preds)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.7258 1.0098 1.1378 1.2784 1.3659 4.3097

Explanation / Answer

The Odd one is Model 1 with no outliers.

IQR(inter-quartile range)= Q3-Q1

Upper limit : Q3+1.5*IQR

Lower Limit: Q1-1.5*IQR

Model 1 has no outliers.

IQR= 0.065

Upper limit:1.271+1.5*0.065= 1.3685

Lower limit: 1.206- 1.5*0.065= 1.1085

Model 2: maximum value is outlier

IQR= 0.228

Upper limit:1.63

Lower limit: 0.718

Model 3: maximum value is outlier

IQR= 0.219

Upper limit:1.5985

Lower limit: 0.7225

Model 4: maxmium value is outlier

IQR= 0.3561

Upper limit: 1.90005

Lower limit: 0.47565