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IE 345

Regression Applications and Forecasting in Engineering

Mechanical & Industrial Engr

3 credit hoursUsually offered: Fall, Spring
Avg GPA
3.03
Easiness
2.70
Total regs
135

Grade Distribution

Based on all available term-level grade data for this course

Avg GPA
3.03
A
42.7%
56
B
34.4%
45
C
17.6%
23
D
3.1%
4
F
0.8%
1
W
1.5%
2
Visual total
131
Other
4
Total regs
135

Quick Insights

Avg GPA
3.03
Easiness
2.70
Pass rate
97.7%
Using A, B, C, D as passing
Withdrawal rate
1.5%
Based on visible distribution
Most common grade
A
Students counted
131
A through F plus W

IE 345 by Professor

Ranked highest to lowest GPA — using A, B, C, D, and F outcomes only

#1
Tejada Lopez, Carla A
3.10
RMP
NR
Graded
39
Total regs
41
#2
Huang, Jida
3.00
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Best professor lead
Tejada Lopez, Carla A

Top GPA signal with 39 grades.

Avg GPA 3.10Open profile →
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About This Class

Single and multiple regression analysis of variance, examination of residuals, introduction to time series analysis, and analytical forecasting techniques; application to engineering system. Course Information: Prerequisite(s): IE 342 .

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RMP
NR
Graded
33
Total regs
33
#
Professor
Avg GPA
RMP
Graded
Total regs
  • 1
    Tejada Lopez, Carla A
    3.10
    NR
    39
    41
  • 2
    Huang, Jida
    3.00
    NR
    33
    33
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