### STAM 200/3.0 Introduction to Statistics

Course applicable to the following Majors / Medials/ Minors:    BCHM (core) / BIMA (core) / BIOL (core) / BIPS (core) / BMCO (option) / BTEC (core) / COGS (option) / COMP (option) / CSCI (option) / EBIO (core) / ETOX (core) / HLTH (option) / PSYC (option) / SOCY (option) / SODE (option)
Course Instructor: Matt Haynes - This email address is being protected from spambots. You need JavaScript enabled to view it.
This course is available in:   Fall term at the BISC
Course Prerequisites / Exclusions:   EXCLUSION: No more than 3.0 units from BIOL 243/3.0; CHEE 209/3.0; ECON 250/3.0; GPHY 247/3.0; KNPE 251/3.0 (formerly PHED 251/3.0); NURS 323/3.0; POLS 385/3.0; PSYC 202/3.0; SOCY 211/3.0; STAT 263/3.0; STAT 267/3.0; STAT 367/3.0; COMM 162/3.0. ONE-WAY EXCLUSION May not be taken with or after STAT 269/3.0.

Statistics is a branch of mathematics that deals with collection, organization, analysis and interpretation of data. STAM 200 students will be able to contextualize core concepts of this field of study by analysing data from real life situations and its implications - for example, we may look at voting statistics in the recent US election, or compare infection rates for different countries during the recent Covid19 pandemic.

DR NAGEENA FROST, COURSE INSTRUCTOR, BISC

### Course Highlights:

Emphasis will be placed on the foundation of statistical inference and practical application of statistical methods.

This is a blended course that will use adaptive learning programs, weekly lectures and labs.

Put theory into practice. An introduction to the analysis of data from real life situations and what reasonable inferences can be made from the data.

A broad introduction to statistics. Topics include probability, t-tests, regression, Chi-square tests and analysis of variance.

### STAM 200/3.0 Introduction to Statistics

Introduces descriptive and inferential statistics and data analysis strategies. Topics include probability, correlation/regression, experimental design and analysis of variance. Online learning and weekly laboratories provide practice in computation, interpretation and communication of statistical findings, and large class review sessions and individual drop in assistance ensure mastery. Applications appropriate to different fields of study will be explored.

### Learning Outcomes

After completing this course, successful students should have the knowledge and skills to do the following:

• Identify the features of a data set to determine how best to summarize and display it.
• Choose the appropriate statistical test and provide the rationale for selection.
• Compute basic parametric and nonparametric statistical tests to test hypotheses.
• Interpret the results of statistical tests and data software output to be able to draw valid conclusions.
• Apply knowledge of statistics and research design (e.g., sampling) to critically evaluate research findings.
Herstmonceux Castle
Hailsham, East Sussex
United Kingdom, BN27 1RN
Phone: +44 1323 834444
This email address is being protected from spambots. You need JavaScript enabled to view it.