Statistics for the Sciences

Description

How do we use data to make informed scientific decisions? This course introduces students to statistical thinking, data collection, data presentation and statistical analysis. Examples from a range of science related disciplines are used to illustrate the key concepts.

Although the emphasis is on applied data analysis rather than statistical theory, the course also provides an appropriate introduction for those students who intend to study statistics at a higher level.

This course cannot count with STAT1060 Business Decision Making.

Availability

Callaghan

  • Semester 1 - 2015
  • Semester 2 - 2015
  • Semester 1 - 2016
  • Semester 2 - 2016

Ourimbah

  • Semester 2 - 2015
  • Semester 2 - 2016

Learning Outcomes

1. Appreciate the role of statistics in developing scientific knowledge

2. Relate probability and sampling concepts to statistical analysis of data

3. Apply basic principles of experimental design when collecting data

4. Analyse data using common statistical software and interpret results to solve science related problems.

Content

  • Introduction & overview of statistics in the sciences
  • Understanding variation and describing univariate data
  • Understanding bivariate relationships
  • Collecting data - surveys and experiments
  • Probability concepts
  • Statistical inference hypothesis tests and confidence intervals
  • Simple bivariate statistical models including regression and ANOVA
  • Non-parametric (distribution-free) tests

Requisite

This course has similarities to STAT1020 or STAT1060. If you have successfully completed any of these courses you cannot enrol in this course.

Assumed Knowledge

Students who are not confident with their mathematics background are advised to complete MATH1001 Preparatory Studies in Mathematics before enrolling in STAT1070. Note: Knowledge of calculus and matrices is not required.

Assessment Items

Written Assignment: Assignments (x2)

Formal Examination: Examination

Quiz: Online Quiz (x6)

Contact Hours

Callaghan

Computer Lab

Face to Face On Campus 1 hour(s) per Week for Full Term

Lecture

Face to Face On Campus 2 hour(s) per Week for Full Term

Tutorial

Face to Face On Campus 1 hour(s) per Week for Full Term