The aim of this course is to provide an introduction to the statistical issues associated with the collection, description, and interpretation of data. In addition, this course aims to introduce statistical computing via Microsoft Excel with a view to describing data using various graphical and numerical methods.
1. Introduction to statistical practice (1.1 Types of statistical applications descriptive, inferential, 1.2 Types of data, 1.3 Sources of data, 1.4 Looking at data intelligently)
2. Collecting Data (2.1 Sampling, 2.2 Experimentation , 2.3 Ethics in Sampling and Experimentation , 2.4 Measurement)
3. Organising data (3.1 Displaying data, 3.2 Displaying distributions, 3.3 Measuring centre or average, 3.4 Measuring spread or variability, 3.5 Density curves and the normal distribution)
4. Understanding relationships (4.1 Two-way tables, 4.2 Scatter plots and correlation, 4.3 Association and causation, 4.4 Least-squares regression, 4.5 Prediction, 4.6 The coefficient of determination)
5. Demonstrate an understanding of probability and probability model and statistical inference. (5.1 Probability models in statistical practice , 5.2 Introduction to statistical inference)
By the end of the course, students should be able to do the following:
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SCQF Level: 7
Credits: 15