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A sample is not the population
Statistics begins with the gap between measured data and the larger group you want to understand.
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01:960:211 · Statistics · School 01 — New Brunswick School of Arts and Sciences
Statistics I covers principles and methods including probability distributions, sampling, estimation, hypothesis testing, regression, correlation, curve fitting, nonparametric methods, and ANOVA.
How hard?
Students rate teaching
SIRS · 2,211 responses · 2014–2025
Spring 2027
3 open in snapshot · 3 instructors
When it meets
College Avenue, Busch
Checked-in sections · current seat counts are unavailable.
TTh 5:40 PM · College Avenue · 1 section · 1 open
Th 5:40 PM · Busch · 1 section · 1 open
W 7:30 PM · Busch · 1 section · 1 open
AI-generated overview
Higher means more demanding · AI summary
5 units · topic sequence may vary by instructor
The course begins by framing data as observations with variability, then builds the probability language needed to reason about random outcomes and distributions.
Students connect samples to populations and learn how estimates, standard errors, and sampling behavior support responsible conclusions from data.
The course develops formal tests for claims, emphasizing null models, test statistics, p-values, and the difference between statistical evidence and practical importance.
Students model relationships between variables and interpret correlation, regression, and fitted curves without treating association as automatic proof of causation.
The final topic set broadens the toolkit to nonparametric procedures and analysis of variance for comparing groups and handling different data assumptions.
Public Rutgers discussion about Statistics I focuses on section differences, how to study when meeting time is limited, and the need to keep up with practice. Instructor-specific comments are anecdotal and sometimes conflicting, so students should rely on the current syllabus and their section's materials for workload and grading.
Statistics begins with the gap between measured data and the larger group you want to understand.
Standard error, confidence intervals, and p-values are ways to express uncertainty, not remove it.
Normality, independence, random sampling, and equal variance conditions determine whether a method is appropriate.
A regression line describes expected response values under a model, not automatic causation.
Common pitfall
Instead
A p-value is probability of data this extreme assuming the null model.
Common pitfall
Instead
Inference is only as credible as the design that produced the data.
Common pitfall
Instead
Look for design, confounding, and mechanism before causal claims.
3 open · College Avenue, Busch
| Section | Status | Instructor | Meeting | Campus |
|---|---|---|---|---|
| 0116848 | Open | Ravi Ramaswamy | Tuesday 5:40 PM-7:00 PM at ABW 2125; Thursday 5:40 PM-7:00 PM at ABW 2125ABW 2125 | College Avenue |
| 0216849 | Open | Donald Hoover | Thursday 5:40 PM-8:40 PM at FBO 108FBO 108 | Busch |
| 0316850 | Open | Philip He | Wednesday 7:30 PM-10:30 PM at EN B120EN B120 | Busch |
Historical student surveys
Teaching
3.78
Course quality
3.74
Response rate
37.9%
Coverage
56 offerings · 2014–2025
| Instructor | Offerings | Teaching | Quality |
|---|---|---|---|
| John Klincewicz | 8 | 4.28 | 4.16 |
| Ravi Ramaswamy | 4 | 3.95 | 3.80 |
| Berhanu Alemayehu | 4 | 3.47 | 3.53 |
| Patricio Rojas | 4 | 3.05 | 3.15 |
| Hei-Ki Dong | 3 | 4.20 | 4.17 |
| Javier Cabrera | 3 | 3.30 | 3.20 |
Catalog and planning context
Credits
3
Current campuses
College Avenue, Busch
Current availability
3 open of 3
Catalog terms
Fall, Spring, Summer
Core codes
ITR, QQ, QR
Loaded terms
6
Any Course EQUAL or GREATER Than: (01:640:112)
No direct degree-list membership appears in the checked-in requirement index.