Postgraduate Programme and Module Handbook 2022-2023 (archived)

# Module PSYC42415: Statistics for Psychology and the Behavioural Sciences

## Department: Psychology

### PSYC42415: Statistics for Psychology and the Behavioural Sciences

Type | Tied | Level | 4 | Credits | 15 | Availability | Available in 2022/23 | Module Cap | None. |
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Tied to | C8K109 |
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Tied to | C8K409 |

Tied to | C8K107 |

#### Prerequisites

- None

#### Corequisites

- None

#### Excluded Combination of Modules

- None

#### Aims

- To teach students a core set of statistical methods that are commonly used across psychology and the behavioural sciences
- To provide students with the capacity to confidently identify appropriate statistical techniques and analyse data using relevant software across a range of different types of research

#### Content

- Indicative content as follows:
- Data collection and validation
- Data management and organisation
- Exploring and presenting data
- Interpretation and reporting of descriptive statistics
- Statistical inference/ null hypothesis testing/ multiple testing correction/ power analysis
- Basic parametric (e.g., t-tests) and non-parametric techniques (e.g., chi-square, correlation)
- Analysis of Variance (ANOVA) (One way / Two-way, Repeated Measures, Mixed Models)
- Multivariate ANOVA (MANOVA)
- Analysis of Covariance (ANCOVA)
- Simple linear regression
- Multiple linear regression
- Dimension reduction

#### Learning Outcomes

Subject-specific Knowledge:

- On completion of this module, students will acquire knowledge and understanding of:
- A range of common-used statistical tests in psychology and the behavioural sciences
- The importance of the role of statistics in any successful data analysis
- The assumptions and limitations of the statistical techniques covered
- The advantages and limitations of using different statistical software (e.g., SPSS, R, JASP)

Subject-specific Skills:

- By the end of the module students should be able to:
- Use and apply a range of statistical techniques commonly used in psychology and the behavioural sciences
- Effectively use statistical applications software (e.g., SPSS, R)
- Analyse data accurately
- Interpret data appropriately
- Create reproducible analyses and reports

Key Skills:

- Students will also develop some important key skills, suitable for underpinning study at this and subsequent levels, such as:
- Implement general IT and research skills
- Organsiation and datat management skills
- Manage their own time and resources
- Work to deadlines and within defined parameters

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

- The weekly teaching will usually include a 1-2 hour lecture which will outline the key statistical methods and concepts, how they can be used in psychology and the behavioural sciences, and their appropriate interpretation followed by 1-2 hours of practical activities in which students will undertake practical data analysis exercises using statistical software.
- The summative assessment will consist of one end-of-term assignment and two components assessed continuously during the term, consisting of practical exercises and pre-lecture questions. The end-of-term assignment and the practical exercises will require students to demonstrate their knowledge and understanding of statistics, the pre-lecture questions will reqiure students to demontrate continuous engagment with the cours. Each practical excercise requires students to conduct and report one statistical analysis. The end-of-term assignment requires students to independently conduct and report several statistical analyses and answer a series of theoretical questions.
- The formative assessment provides students with an opportunity to perform, write up and obtain feedback on a series of analyses of pre-specified secondary data sets.

#### Teaching Methods and Learning Hours

Activity | Number | Frequency | Duration | Total/Hours | |
---|---|---|---|---|---|

Lecture | 10 | 1 per week | 1-2 hours | 15 | ■ |

Practical | 10 | 1 per week | 1-2 hours | 15 | ■ |

Preparation and Reading | 120 | ||||

Total | 150 |

#### Summative Assessment

Component: End-of-term Assignment | Component Weighting: 67% | ||
---|---|---|---|

Element | Length / duration | Element Weighting | Resit Opportunity |

Take-home assignment consisting of several statistical analyses and theory questions | approximately 10 pages or 5000 words | 100% | yes |

Component: In-term Exercises | Component Weighting: 33% | ||

Element | Length / duration | Element Weighting | Resit Opportunity |

Practical exercise 1 (take-home assignment consisting of a series of statistical operations) | 1 hour | 30% | yes |

Practical exercise 2 (take-home assignment consisting of a series of statistical operations) | 1 hour | 30% | yes |

Practical exercise 3 (take-home assignment consisting of a series of statistical operations) | 1 hour | 30% | yes |

10 pre-lecture questions (1% each submission) | 5 mins (each) | 10% | yes |

#### Formative Assessment:

Formative student assessments (both written and oral) will be undertaken throughout the duration of the module. These will be assessed by the tutor to enable students to gauge their own individual rate of progress.

■ 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