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MATH 385 — PROBABILITY AND STATISTICAL INFERENCE I

5 credits Catalog-Derived
Data Science Mathematics
5
Objectives
5
Matches
0
Reviewed
5
Occupations
Your experience with this course
Top occupation matches for this course
34.5% Data Scientists 1t
38.8% Biostatisticians 1t
34.6% Operations Research Analysts 1t
30.3% Mathematicians 1t
36.3% Actuaries 1t

Learning Objectives & Matches

LO1

Introduces mathematical theory of probability and statistical inference including proofs, discrete/continuous distributions, and hypothesis testing.

1 O*NET task matches
Batch:
Data Scientists
35% ok

Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.

LO2

Perform hypothesis testing

1 O*NET task matches
Batch:
Operations Research Analysts 4.5/5
35% ok

Define data requirements, and gather and validate information, applying judgment and statistical tests.

LO3

Apply probability distributions rigorously

1 O*NET task matches
Batch:
Mathematicians 4.0/5
30% ok

Assemble sets of assumptions, and explore the consequences of each set.

LO4

Prove probability theorems

1 O*NET task matches
Batch:
Actuaries 4.2/5
36% ok

Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information.

LO5

Construct confidence intervals

1 O*NET task matches
Batch:
Biostatisticians 4.3/5
39% ok

Calculate sample size requirements for clinical studies.

Source: Course learning outcomes from the EWU catalog. O*NET task matches are computed by comparing each learning outcome statement against every O*NET task statement using sentence-embedding similarity; faculty review confirms which matches count as preparation evidence.