CODE: SOR 1212

TITLE: Introduction to Applied Statistics and Data Analysis I

MQF LEVEL: 5

ECTS CREDITS: 4

DEPARTMENT: Junior College

DESCRIPTION:

This is an introductory study-unit in statistics designed to provide students with a theoretical background in statistical techniques and data analysis with emphasis on application. Students will learn to differentiate between different types of data and how it is collected, the different ways in which these can be represented graphically, how to summarize and analyze a presented data set, as well as the basics of probability and probability distributions. Practical examples from different fields will be used to illustrate the techniques discussed. A more detailed list of topics is listed below:

Introduction to Statistics

• Definition and importance of statistics
• Types of data: qualitative vs quantitative
• Types of measurement: e.g. nominal, ordinal, interval

Data Collection and Sampling Methods

• Population vs sample
• Sampling techniques: random, stratified, cluster, systematic, convenience
• Designing surveys and experiments
• Sources of bias in data collection

Descriptive Statistics

• Measures of central tendency: mean, median, mode
• Measures of variability: range, variance, standard deviation
• Introduction to frequency distributions
• Graphical representations: histograms, bar charts, pie charts, box plots, stem and leaf, cumulative frequency curves

Probability Basics

• Definition and rules of probability
• Addition and multiplication rules
• Conditional probability and independence
• Probability distributions: discrete and continuous

Discrete Probability Distributions

• Binomial distribution
• Poisson distribution

Continuous Probability Distributions

• Normal distribution
• Standard normal distribution (z-scores)
• Central limit theorem

Learning Outcomes

Knowledge and Understanding

By the end of the Study-Unit the student will be able to:

• Define and explain the significance of key statistical terms and concepts
• Distinguish between different types of data and levels of measurement
• Design surveys and experiments using appropriate sampling methods
• Recognise and mitigate sources of bias in data collection
• Calculate and interpret measures of central tendency (mean, median, mode) and variability (range, variance, standard deviation)
• Create and interpret graphical representations of data, including histograms, bar charts, pie charts, and box plots
• Use basic probability rules to solve problems involving random events
• Identify and apply appropriate probability distributions for different types of data

Skills

By the end of the Study-Unit the student will be able to:

• Perform basic statistical analysis using spreadsheets
• Create and interpret various types of graphs and charts, such as histograms, bar charts, pie charts, and scatter plots, to effectively communicate data insights.
• Apply key probability concepts and distributions
• Interpret and critically evaluate statistical results in the context of real-world scenarios
• Assess the validity and reliability of conclusions drawn from statistical analyses.

Main Reading List

• McClave, J.T. and Sincich T., 2018. A First Course in Statistics. 12^th ed. Boston: Pearson. ISBN 13: 978-1-292-16541-7
• Triola, M.F., 2021. Elementary Statistics. 14^th ed. Hoboken, NJ: Pearson. ISBN-13: 978-0-137-36644-6
• Sullivan, M., 2020. Statistics: Informed Decisions Using Data. 6^th ed. Boston: Pearson. ISBN-13: 978-0-136-87274-0

Supplementary Reading

• Agresti, A. and Franklin, C.A., 2017. Statistics: The Art and Science of Learning from Data. 4^th ed. Boston: Pearson. ISBN-13: 978-0-133-86082-5

STUDY-UNIT TYPE: Lecture

METHOD OF ASSESSMENT:

Component                                        Weighting

Assignment                                         80%

Classwork                                           20%