• Scott Wolpert to lead NSF-funded project on DEI in mathematics and statistics

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  • Congratulations to Perrin Ruth and Elliot Kienzle

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  • Congrats to CMNS' Deven Bowman, 2023 Goldwater Scholar

    Congratulations to Deven Bowman, a junior physics and mathematics dual-degree student, who was named a 2023 Goldwater Scholar! Deven has done research with Eun-Suk Seo and Steve Rolston and studied abroad in Florence with Luis Orozco. This summer he’ll be at Caltech working on LIGO. And, fun fact, both of his parents… Read More

  • Maryland finishes fourth in the 2022 Putnam competition

     We are very excited to share the news that the University of Maryland Putnam team ranked fourth among 456 institutions in the 2022 Putnam Competition. This is the best result for our team in more than four decades. The first three teams are MIT, Harvard and Stanford. Our team members,… Read More
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Description

STAT 430 will introduce modern techniques of computational statistics for practical analysis of data. The course will utilize the SAS software system, which is widely used both in statistical applications and in corporate data management applications. Data analysis and interpretation will be emphasized, rather than statistical theory. At every point in the course real world data sets will be used to illustrate statistical principles.

For undergraduates in mathematics or computer science seeking statistical employment after graduation, SAS is a valuable job credential. For graduate students in fields which use statistics heavily, such as agriculture, life science, education, engineering or social science, SAS is a powerful aid to research.  Graduate students who have successfully taken an applied statistics course in their own department should have no difficulty with STAT 430.

Prerequisites

1 course with a minimum grade of C- from (STAT400, STAT410).

co-requisite starting Spring 2023 1 course with a minimum grade of C- from (STAT401, STAT420).


Level of Rigor

Standard


Sample Textbooks

Applied Statistics and the SAS Programming Language, by R.P. Cody and J.K. Smith

The Little SAS Book: A Primer, by L. Delwiche & S. Slaughter


Applications



If you like this course, you might also consider the following courses



Additional Notes

Students interested in grad school in STAT should consider this course 

Topics

Brief review of statistical concepts

Descriptive statistics

Points estimators

Confidence intervals

Hypothesis testing

Introduction to the SAS software system

Data screening

Data summaries and graphics

Creating and manipulating data sets

Merging, sorting and splitting data sets

Least squares and fitting models

Straight line fits

Graphical tools for model criticism

Multiple predictors

Categorical predictors and analysis of variance

Categorical data

Frequency tables

Logistic regression

Models for count data

Simulation

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