STSCI 2200

STSCI 2200

Course information provided by the 2015-2016 Catalog.

In this course, students develop statistical methods and apply them to problems encountered in the biological and environmental sciences. Methods include data visualization, population parameter estimation, sampling, bootstrap resampling, hypothesis testing, the Normal and other probability distributions, and an introduction to linear modeling. Applied analysis is carried out in the R statistical computing environment.


Prerequisites/Corequisites Prerequisite: one semester of calculus.

Outcomes

  • Students will be able to discuss and explain hypothesis testing and the basic principles of probability and statistics.
  • Students will be able visualize trends in complex data sets and develop simple models for analysis.
  • Students will be able to estimate population means, variances, standard deviations, and standard errors through a variety of methods.
  • Students will be able to critically evaluate the assumptions upon which statistical estimation is based.
  • Students will be able to conduct a single-sample, two-sample, and paired t-tests.
  • Students will be able to conduct goodness-of-fit tests, contingency tables, simple linear regression and one-way analysis of variance.

Distribution Category (MQR)

When Offered Fall.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one laboratory. Combined with: BTRY 3010NTRES 3130

  • 4 Credits Stdnt Opt

  • 12380 STSCI 2200   LEC 001

  • Instruction Mode: In Person

    Prerequisite: one semester of calculus.

  • 12381 STSCI 2200   LAB 401

  • Instruction Mode: In Person

  • 12382 STSCI 2200   LAB 402

  • Instruction Mode: In Person

  • 12383 STSCI 2200   LAB 403

  • Instruction Mode: In Person

  • 12384 STSCI 2200   LAB 404

  • Instruction Mode: In Person

  • 12385 STSCI 2200   LAB 405

  • Instruction Mode: In Person

  • 12386 STSCI 2200   LAB 406

  • Instruction Mode: In Person