Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2013-2014 (archived)

Module FOUN0397: FOUNDATIONS OF STATISTICS (TB1)

Department: Foundation Year

FOUN0397: FOUNDATIONS OF STATISTICS (TB1)

Type Open Level 0 Credits 10 Availability Available in 2013/14 Module Cap None. Location Durham and Queen's Campus Stockton

Prerequisites

  • None.

Corequisites

  • None.

Excluded Combination of Modules

  • Numerical Skills and Research Methods for Social Scientists (FOUN0321).

Aims

  • To introduce and develop understanding of basic statistical principles to provide a foundation for future study.
  • To develop understanding of application of statistics to develop students' learning skills.
  • To encourage students to develop confidence in their own abilities in statistics.

Content

  • Statistics: Sampling - Distinctions between sample and population, Need for randomness in selecting a sample.
  • Tabulation - Discrete/continuous data, Tally charts, frequency and grouped frequency tables, Class intervals and Implications of grouping.
  • Representation - Bar Charts, Pie Charts, Histograms, Recognising visual misrepresentation.
  • Measures of location - Mean and mode for raw data and frequency distribution, Median for raw data.
  • Measures of Spread - Range, Quartiles, Inter-quartile range, Variance, standard deviation for raw data, frequency distribution, cumulative frequency.
  • Correlation - Scatter diagrams +ve, -ve, or lack of correlation, line of best fit (by eye) through (x,y), interpolation and extrapolation.
  • Tests - Chi squared, Normal distribution, Contingency tables.
  • Probability - Venn diagrams.
  • Range 0-1, impossible to certainty, Probabilities of equally likely events, Probability as a limit to relative frequency.
  • Simple Addition and Multiplication of probabilities as appropriate, Tree diagrams.
  • Introduction to computer use for statistics.

Learning Outcomes

Subject-specific Knowledge:
  • Knowledge of different forms of sampling, tabulation and visual representation
  • Understanding of the distinctions and implications of using different forms of sampling, tabulation and visual representation
  • Knowledge of calculations required for measures of central location, spread, correlation and significance testing
  • Understanding of implications and appropriateness of use of different measures
  • Knowledge of probability, including calculations of equally likely events and simple addition and multiplication as appropriate
  • Knowledge of some probability diagrams including Tree diagrams, Venn diagrams and probability space tables.
Subject-specific Skills:
  • By the end of the module the students will have acquired the skills to be able to:
  • use a calculator appropriately in relation to problems faced.
  • use a computer appropriately in relation to problems faced.
  • carry out a range of statistical procedures as listed on the attached syllabus.
  • conduct a survey and analyse results statistically.
Key Skills:
  • By the end of the module the students will:
  • be able to communicate effectively in writing
  • be able to apply number both in the tackling of numerical problems and in the collecting, recording, interpreting and presenting of data
  • Research project tests: SSK1, SSK2, SSk3, SSk4, SSS1, SSS2, SSS3, SSS4, KS1, KS2.,
  • Test tests: SSK1, SSK2, SSk3, SSk4, SSK5, SSK6, SSS1, SSS3, , KS1, KS2.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Theory, initial concepts and techniques will be introduced during lectures.
  • Much of the learning, understanding and consolidation will take place through the use of structured worksheets during tutorials and students' own time.
  • Knowledge and ability to use and apply concepts and techniques will be tested in the module test.
  • Knowledge and ability to use and apply concepts and teachniques will also be consolidated and assessed by the project and the other coursework task.
  • Design, implementation and statistical analysis of surveys will be consolidated and assessed through the independent production of the projects.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 10 weekly 2 hours 20
Tutorials 10 weekly 1 hour 10
Preparation and Reading 70
Total 100

Summative Assessment

Component: Research Project (non computer) Component Weighting: 45%
Element Length / duration Element Weighting Resit Opportunity
Research project 100% Resubmission
Component: Two Hour Invigilated Test Component Weighting: 55%
Element Length / duration Element Weighting Resit Opportunity
Two Hour Invigilated Test 2 hours 100% Resit

Formative Assessment:

Students will be given self-testing units on a weekly basis


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University