SD5811 Statistical Foundations

Academic year

2024 to 2025 Semester 2

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

15

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Available only to students on the PG Cert, PG Dip, or MSc in Data Literacy for Social and Environmental Justice

Planned timetable

Not Applicable

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr E O Olamijuwon

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Dr L Cole; Dr T Mendo; Dr E Olamijuwon

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

The course is structured around the use of statistics to understand social or environmental processes, using real datasets and surveys. This module builds on the foundation provided by “SD5510 Welcome to Data,” and students will further develop their coding skills, using open-source software (e.g., R/RStudio and Google Sheets). Here we provide an introduction to: basic statistical concepts, methods to explore patterns in data, and skills in interpreting statistical results. At the end of this module, students should be able to: critically evaluate available data and published statistics, select and generate appropriate plots and tables to explore data, and use techniques to assess relationships between both continuous and categorical (discrete) variables. This module will have two pathways managed through the virtual learning environment – social science vs. environmental science – to ensure students engage with data that are relevant for their subfield of study.

Relationship to other modules

Pre-requisites

IN ORDER TO TAKE THIS MODULE YOU MUST TAKE OR HAVE TAKEN SD5510 OR HAVE PERMISSION FROM THE PROGRAMME DIRECTOR

Assessment pattern

100% coursework

Re-assessment

100% coursework

Learning and teaching methods and delivery

Weekly contact

This module includes 5 1-hour synchronous tutorial sessions and at least 5 hours of pre-recorded content (e.g., lectures). Students should consider the amount of independent study time this module involves when planning their learning.

Scheduled learning hours

0

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

145

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Organise and rearrange large quantitative datasets for use in common software packages;
  • Perform data manipulation upon large quantitative datasets, e.g., creating categorical variables from continuous variables;
  • Use software to explore large quantitative datasets, including building summary tables;
  • Select and generate appropriate plots to describe large quantitative datasets;
  • Use statistical techniques to assess relationships between both continuous and categorical variables.

SD5811 Statistical Foundations

Academic year

2024 to 2025 Semester 1

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

15

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Available only to students on the PG Cert, PG Dip, or MSc in Data Literacy for Social and Environmental Justice

Planned timetable

Not Applicable

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr E O Olamijuwon

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Dr L Cole; Dr T Mendo; Dr E Olamijuwon

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

The course is structured around the use of statistics to understand social or environmental processes, using real datasets and surveys. This module builds on the foundation provided by “SD5510 Welcome to Data,” and students will further develop their coding skills, using open-source software (e.g., R/RStudio and Google Sheets). Here we provide an introduction to: basic statistical concepts, methods to explore patterns in data, and skills in interpreting statistical results. At the end of this module, students should be able to: critically evaluate available data and published statistics, select and generate appropriate plots and tables to explore data, and use techniques to assess relationships between both continuous and categorical (discrete) variables. This module will have two pathways managed through the virtual learning environment – social science vs. environmental science – to ensure students engage with data that are relevant for their subfield of study.

Relationship to other modules

Pre-requisites

IN ORDER TO TAKE THIS MODULE YOU MUST TAKE OR HAVE TAKEN SD5510 OR HAVE PERMISSION FROM THE PROGRAMME DIRECTOR

Assessment pattern

100% coursework

Re-assessment

100% coursework

Learning and teaching methods and delivery

Weekly contact

This module includes 5 1-hour synchronous tutorial sessions and at least 5 hours of pre-recorded content (e.g., lectures). Students should consider the amount of independent study time this module involves when planning their learning.

Scheduled learning hours

0

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

145

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Organise and rearrange large quantitative datasets for use in common software packages;
  • Perform data manipulation upon large quantitative datasets, e.g., creating categorical variables from continuous variables;
  • Use software to explore large quantitative datasets, including building summary tables;
  • Select and generate appropriate plots to describe large quantitative datasets;
  • Use statistical techniques to assess relationships between both continuous and categorical variables.