Nicolas Christou
Department of Statistics
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4.2
Overall Rating
Based on 4 Users
Easiness 2.0 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 4.2 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 2.8 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 4.8 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Tough Tests
  • Engaging Lectures
  • Would Take Again
GRADE DISTRIBUTIONS
44.8%
37.4%
29.9%
22.4%
14.9%
7.5%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

34.6%
28.8%
23.1%
17.3%
11.5%
5.8%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

50.0%
41.7%
33.3%
25.0%
16.7%
8.3%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

47.4%
39.5%
31.6%
23.7%
15.8%
7.9%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

28.2%
23.5%
18.8%
14.1%
9.4%
4.7%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

58.8%
49.0%
39.2%
29.4%
19.6%
9.8%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

66.7%
55.6%
44.4%
33.3%
22.2%
11.1%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

70.0%
58.3%
46.7%
35.0%
23.3%
11.7%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

ENROLLMENT DISTRIBUTIONS
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Reviews (2)

1 of 1
1 of 1
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Quarter: Winter 2026
Grade: N/A
Verified Reviewer This user is a verified UCLA student/alum.
Feb. 28, 2026

Ok look, there are positives here. Professor Christou is obviously a very nice man who is extremely available to his students, even holding office hours on Saturday, and the curve on the tests is extremely helpful. That's about where the positives stop though.

First, this class is "applied" geostatistics in name only. Basically everything you are going to do in class and on the exams is deriving estimators and then re-deriving estimators, and then occasionally running some R code in the Homeworks and Labs.

As for the exams, like other reviews of Christou for other classes have noted, this man's tests are likely something out of a torture manual. Three exams, closed notes, two hours outside of class for the midterm and you *still* have class the day of the exams. The exams do not actually measure whether you have understood the material he has taught, instead they seem designed to identify whether you're going to be a stats PhD student or something by just ladling stuff you haven't seem on top of stuff that's worded very differently from how you learned it in class. The average on our first midterm was a 35% for instance. You'll still get probably like a B- at minimum because of the wicked curve, but it is extremely annoying to have to sit through 7 hours of exams where you feel like you have basically no idea how to do half of it. Also, maybe it was just our reader, but we received no feedback on why our answers in the exams were wrong, just indications for how many points we lost.

This is made harder by the fact that Christou is really not an effective lecturer. Maybe his style works for some people but it 100% did not work for me. He would go way to fast, skip steps during the derivation, etc. Really disorganized, the sample exams and solutions he gives are not terribly helpful, yadda yadda yadda. I just found this course to be really annoying.

Also, the course project that you have? The one that the syllabus says you will discuss regularly? Yeah you are not going to discuss that at all until it is sprung on you again at the end of the quarter while you are trying to cram for exams and final projects in other classes and all that jazz.

Anyway, tldr, I would not take this class again.

Helpful?

0 0 Please log in to provide feedback.
Quarter: Spring 2018
Grade: A
March 31, 2018

This is an extremely interesting class and professor Christou does an amazing job of teaching it. Knowing what to do with spatial data is an increasingly important skill, and in this class you'll learn how to analyze if there are trends in spatial data, make predictions, create heat maps, contour maps, etc. Dr. Christou is one of the best instructors in the department and you will walk away with rigorous and practical knowledge.

Helpful?

0 0 Please log in to provide feedback.
Verified Reviewer This user is a verified UCLA student/alum.
Quarter: Winter 2026
Grade: N/A
Feb. 28, 2026

Ok look, there are positives here. Professor Christou is obviously a very nice man who is extremely available to his students, even holding office hours on Saturday, and the curve on the tests is extremely helpful. That's about where the positives stop though.

First, this class is "applied" geostatistics in name only. Basically everything you are going to do in class and on the exams is deriving estimators and then re-deriving estimators, and then occasionally running some R code in the Homeworks and Labs.

As for the exams, like other reviews of Christou for other classes have noted, this man's tests are likely something out of a torture manual. Three exams, closed notes, two hours outside of class for the midterm and you *still* have class the day of the exams. The exams do not actually measure whether you have understood the material he has taught, instead they seem designed to identify whether you're going to be a stats PhD student or something by just ladling stuff you haven't seem on top of stuff that's worded very differently from how you learned it in class. The average on our first midterm was a 35% for instance. You'll still get probably like a B- at minimum because of the wicked curve, but it is extremely annoying to have to sit through 7 hours of exams where you feel like you have basically no idea how to do half of it. Also, maybe it was just our reader, but we received no feedback on why our answers in the exams were wrong, just indications for how many points we lost.

This is made harder by the fact that Christou is really not an effective lecturer. Maybe his style works for some people but it 100% did not work for me. He would go way to fast, skip steps during the derivation, etc. Really disorganized, the sample exams and solutions he gives are not terribly helpful, yadda yadda yadda. I just found this course to be really annoying.

Also, the course project that you have? The one that the syllabus says you will discuss regularly? Yeah you are not going to discuss that at all until it is sprung on you again at the end of the quarter while you are trying to cram for exams and final projects in other classes and all that jazz.

Anyway, tldr, I would not take this class again.

Helpful?

0 0 Please log in to provide feedback.
Quarter: Spring 2018
Grade: A
March 31, 2018

This is an extremely interesting class and professor Christou does an amazing job of teaching it. Knowing what to do with spatial data is an increasingly important skill, and in this class you'll learn how to analyze if there are trends in spatial data, make predictions, create heat maps, contour maps, etc. Dr. Christou is one of the best instructors in the department and you will walk away with rigorous and practical knowledge.

Helpful?

0 0 Please log in to provide feedback.
1 of 1
4.2
Overall Rating
Based on 4 Users
Easiness 2.0 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 4.2 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 2.8 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 4.8 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

TOP TAGS

  • Tough Tests
    (3)
  • Engaging Lectures
    (2)
  • Would Take Again
    (2)
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