Module Directory

On successful completion of this module a student is 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 able to conduct simple hypothesis tests.


7. Understand correlation and simple regression.

Skills for your professional life (Transferrable Skills)

This module offers you numerous transferable and professional skills such as:

a) 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 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.

b) 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.

c) 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 environment where extensive statistics and mathematics are used.

d) 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.

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

The module is delivered via a weekly 1 x 1-hour lecture, 1 x 2-hour class and 1 x 1-hour computer lab. 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. In total, there are 22 weeks of teaching, including two weeks of revision lectures and classes in the Summer Term.

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 reviews the recordings at a later date.