A student's guide to performing frequentist statistical analyses using JASP. This document is a collection of standalone handouts covering the most common standard (frequentist) statistical analyses used by students studying Biological Sciences. Datasets used in this document are available for download from: https://osf.io/bx6uv/.

This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester of such a course. It is freely available under the Creative Commons License, and includes a software library in Python for making some of the calculations and visualizations easier.

Introductory statistics course developed through the Ohio Department of Higher Education OER Innovation Grant. The course is part of the Ohio Transfer Module and is also named TMM010. For more information about credit transfer between Ohio colleges and universities please visit: www.ohiohighered.org/transfer.Team LeadKameswarrao Casukhela                     Ohio State University – LimaContent ContributorsEmily Dennett                                       Central Ohio Technical CollegeSara Rollo                                            North Central State CollegeNicholas Shay                                      Central Ohio Technical CollegeChan Siriphokha                                   Clark State Community CollegeLibrarianJoy Gao                                                Ohio Wesleyan UniversityReview TeamAlice Taylor                                           University of Rio GrandeJim Cottrill                                             Ohio Dominican University

ProbabilityThe notion of chance or probability of an event plays a crucial role in statistics. In this module we will study this notion and learn different rules that will help us determine the probability of different types of events associated with a process.Learning Objectives:Random experiment, sample space, eventsPermutation and CombinationDefinition of probability of an event and its propertiesDisjoint and independent eventsConditional eventsVenn and Tree DiagramsComplement (Subtraction) ruleAddition ruleMultiplication ruleDivision ruleTwo-Way tablesTotal Probability Rule and Bayes Rule