St. Lawrence University Electronic Learning Environment: All courses

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1.0 INTRODUCTION

Statistics on the other hand is the study of collection, organization, analysis, synthesis and interpretation of data.
This course therefore provides a student with a solid foundation in the methods and theories of such disciplines. One is trained to advance their understanding of economic conditions through the analysis, synthesis and reporting of data using the advanced research methods.

2.0 Justification of Study of course

The objective of the Bachelor of statistics programme of study is to prepare undergraduates for careers in the fields of Statistics through a judicious mix of units that are core to the disciplines and those drawn from complementary disciplines. Areas of employment include banking and other financial institutions e.g. banks industrial firms where they are useful in optimizing production costs, government departments dealing with issues of economic policies, regulation and analysis.

3.0 Learning Outcomes

By the time of graduation, our students will have achieved the following:

· Recognize the importance of proper collection and management of quantitative information to the scientific process, including appreciation of the importance of data accuracy , verifiability and context

· Understand, explain and contextualize the importance of quantitative analysis in at least one major area of application.

· Understand the theoretical and mathematical underpinnings of statistical theory and practice.

· Apply data analytic techniques that are appropriate to inquiry context, including demonstrating appreciation for the underlying assumptions and data requirements for these techniques to be valid.

· Communicate the principles and results of data analyses using the language and conventions of the discipline.

· Apply a wide range of statistical testing and estimation techniques, including modern and computer based modeling, in appropriate context.

· Develop the skills necessary to critically engage with and evaluate literature on data analysis.

· Explain and convey findings and information from data analysis.