Statistics in Practice

Victoria University of Wellington

Course Description

  • Course Name

    Statistics in Practice

  • Host University

    Victoria University of Wellington

  • Location

    Wellington, New Zealand

  • Area of Study

    Mathematics, Statistics

  • Language Level

    Taught In English

  • Course Level Recommendations


    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Credit Points

  • Recommended U.S. Semester Credits
    3 - 4
  • Recommended U.S. Quarter Units
    4 - 6
  • Overview

    An applied statistics course for students who will be advancing in other disciplines as well as those majoring in Applied Statistics. It is particularly suitable for students majoring in Biological Science subjects, Geography, Linguistics, Psychology and social sciences such as Education and is also suitable for students taking BCA subjects.

    Course content
    The course material will be delivered in 36 lectures, including revision lectures. Topics covered include, summary and graphical display of data, correlation, regression, probability. Introduction to the Normal distribution, large sample confidence intervals and hypothesis tests. Small sample hypothesis tests and confidence intervals, analysis of variance (ANOVA), the chi-squared test for contingency tables and the non-parametric Sign test.

    Course learning objectives
    Students who pass this course should be able to:

    • Identify and interpret differences between different data types.
    • Choose, construct and interpret appropriate visual and numerical data summaries for each data type.
    • Explain and apply concepts of probability, random variables and probability distributions.
    • Explain and apply the concept of sampling variability.
    • Pose and test a hypothesis to answer a research question of interest on specified univariate and bivariate data types; and interpret the results of the hypothesis test plus associated confidence intervals.
    • Use statistical software to summarise, display and analyse data.

Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Some courses may require additional fees.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

Please reference fall and spring course lists as not all courses are taught during both semesters.

Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations

Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.


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