Module Directory

This module covers the statistical skills needed to proceed to any degree course within the Department of Psychology. The syllabus covers statistical methods including data collect and analysis, distributions and hypothesis testing.

The associated work in classes and lab exercises develops the skills used to solve relevant problems, with classwork and assignments being set and full solutions provided where appropriate as part of the feedback process.

The aims of this module are:

• To ensure that students from a wide range of educational backgrounds have an understanding of statistical methods needed within the study of Psychology.


• To develop the ability to acquire knowledge and skills from lectures, classwork exercises, and appropriate software and application of theory to a range of ongoing tasks.


• To develop students' ability to use these skills in their subsequent degree courses.


• To equip students with the techniques needed to collect and analyse data, calculate statistical measures and to clearly structure their solutions and conclusions.


• To give students the ability to present and interpret data clearly and unambiguously, both by hand and with the use of Excel software.


• To give students an understanding of data distributions and the ability to set up hypothesis tests.

By the end of this module, students will be expected to be able to:

1. Understand sampling methods for data collection.


2. Understand and calculate basic statistical measures of centrality and spread.


3. Understand and interpret basic statistical graphs, including using Excel to analyse data and produce various graphs.


4. Understand the normal distribution and be familiar with other common distributions.


5. Understand basic probability.


6. Understand basic statistical inference and be able to conduct simple hypothesis tests.


7. Understand correlation and simple regression.

Skills for your professional life (Transferable Skills)

By the end of this module, students will have practised the following transferable skills:

• Application of Statistics: Statistics is applied in almost every scenario which involves data. This is extremely useful in everyday life and many disciplines including psychology, medicine, public health, business, science, engineering etc. In the real world, we need to collect data and apply statistical techniques to the data to learn the underlying causes and relationships, and to make correct decisions.


• Using graphs to see patterns in data and to present the evidence: Another exciting skill you will learn is to make different graphs for visually showing patterns and trends in the data and also to present the results.


• IT skills: you will learn the exciting use of technology for accurate and speedy statistical analysis by using Microsoft Excel software. Excel is widely sued in everyday life data management and analysis by researchers, business communities, government bodies etc. Excel makes the application of statistics and data analysis easy. Learning Excel is a great skill you can use in your future studies as well as in your work career. Further, by using NUMBAS in lab activities, you learn how to use software to get instant results from your problem-solving activity. This is a vital tool in many applications and environments where extensive statistics and mathematics are used.


• Logical approach: doing advanced topics such as inferential statistics help you to develop additional skills in planning, analysing, and learning methodical and logical approach to problem-solving. These skills are transferrable to many areas of your future studies and work.

Syllabus

• Data collection: methods to ensure data is unbiased.


• Descriptive statistics: interpreting data, measures of location and dispersion.


• Displaying data: Constructing and analysing histograms and other graphs.


• Distributions: normal distribution and other common distributions.


• Inference Statistics: hypothesis testing and statistics tables.


• Using Excel to carry out statistical computations, create graphs and interpret data.


• Measures of dispersion and central tendency, probability, correlation and regression.


• Practical application of statistics to Psychology related problems.

This module will be delivered via:

• One 1-hour lecture per week.
• One 2-hour class per week.
• One 1-hour computer lab per week.

There are two weeks of revision lectures and classes in the Summer Term.

Students are expected to complete the Moodle-based online assignments/activities in their own individual study time. Support for this is provided through academic support hours and email.

Teaching and learning on Essex Pathways modules offers students the ability to develop the foundation knowledge, skills, and competencies to study at the undergraduate level, through a curriculum that is purposely designed to provide an exceptional learning experience.

All lecture notes and worksheet exercises are placed on Moodle prior to the teaching event for easy student access. Solutions to worksheet exercises are also placed on Moodle after the teaching event is concluded to aid with revision. Listen Again is also used as part of learning support in which students can review the recordings at a later date.