Introduction to Statistics with R workshop, Nov 15 - 18 Overview Introduction to Statistics with R This workshop uses a public health dataset and examples (NHANES from the US National Center for Health Statistics) but the materials are relevant to researchers more generally in the life, health and social sciences. The workshop assumes no prior experience of statistical analysis in R. However, learners are expected to have some familiarity with R such as having done an introductory course. If you do not have any experience currently, one of these Carpentries courses would prepare you: Data Analysis and Visualization in R for Ecologists Episodes 1 to 5 R for Social Scientists Episodes 1 to 5 General Information Where: This training will take place online. The instructors will provide you with the information you will need to connect to this meeting. When: 15 - 18 November. Requirements: Participants must have access to a computer with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed. Accessibility: We are dedicated to providing a positive and accessible learning environment for all. Please notify the instructors in advance of the workshop if you require any accommodations or if there is anything we can do to make this workshop more accessible to you. Schedule The lesson taught in this workshop is being piloted and a precise schedule is yet to be established. Day 1 : 15th November (10:00 - 13:00) Pre-workshop Setup Lessons Statistical thinking for public health Estimating the mean, variance and standard deviation Estimating the variation around the mean Visualising and quantifying linear associations Predicting means using linear associations Break Morning 11:30 - 11:45 Day 2 : 16th November (10:00 - 13:00) Lessons Simple linear regression for public health An introduction to linear regression Linear regression with one continuous explanatory variable Linear regression with a two-level factor explanatory variable Making predictions from a simple linear regression model Break Morning 11:30 - 11:45 Day 3 : 17th November (10:00 - 13:00) Lessons Simple linear regression for public health Assessing simple linear regression model fit and assumptions Linear regression with a multi-level factor explanatory variable Break Morning 11:30 - 11:45 Day 4 : 18th November (10:00 - 13:00) Lessons Multiple linear regression for public health Linear regression with one continuous and one categorical explanatory variable Linear regression including an interaction between one continuous and one categorical explanatory variable Break Morning 11:30 - 11:45 More information Ed-DaSH homepage Ed-DaSH contact Nov 15 2022 10.00 - Nov 18 2022 13.00 Introduction to Statistics with R workshop, Nov 15 - 18 This workshop uses a public health dataset and examples but the materials are relevant to researchers more generally in the life, health and social sciences. Register here
Introduction to Statistics with R workshop, Nov 15 - 18 Overview Introduction to Statistics with R This workshop uses a public health dataset and examples (NHANES from the US National Center for Health Statistics) but the materials are relevant to researchers more generally in the life, health and social sciences. The workshop assumes no prior experience of statistical analysis in R. However, learners are expected to have some familiarity with R such as having done an introductory course. If you do not have any experience currently, one of these Carpentries courses would prepare you: Data Analysis and Visualization in R for Ecologists Episodes 1 to 5 R for Social Scientists Episodes 1 to 5 General Information Where: This training will take place online. The instructors will provide you with the information you will need to connect to this meeting. When: 15 - 18 November. Requirements: Participants must have access to a computer with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed. Accessibility: We are dedicated to providing a positive and accessible learning environment for all. Please notify the instructors in advance of the workshop if you require any accommodations or if there is anything we can do to make this workshop more accessible to you. Schedule The lesson taught in this workshop is being piloted and a precise schedule is yet to be established. Day 1 : 15th November (10:00 - 13:00) Pre-workshop Setup Lessons Statistical thinking for public health Estimating the mean, variance and standard deviation Estimating the variation around the mean Visualising and quantifying linear associations Predicting means using linear associations Break Morning 11:30 - 11:45 Day 2 : 16th November (10:00 - 13:00) Lessons Simple linear regression for public health An introduction to linear regression Linear regression with one continuous explanatory variable Linear regression with a two-level factor explanatory variable Making predictions from a simple linear regression model Break Morning 11:30 - 11:45 Day 3 : 17th November (10:00 - 13:00) Lessons Simple linear regression for public health Assessing simple linear regression model fit and assumptions Linear regression with a multi-level factor explanatory variable Break Morning 11:30 - 11:45 Day 4 : 18th November (10:00 - 13:00) Lessons Multiple linear regression for public health Linear regression with one continuous and one categorical explanatory variable Linear regression including an interaction between one continuous and one categorical explanatory variable Break Morning 11:30 - 11:45 More information Ed-DaSH homepage Ed-DaSH contact Nov 15 2022 10.00 - Nov 18 2022 13.00 Introduction to Statistics with R workshop, Nov 15 - 18 This workshop uses a public health dataset and examples but the materials are relevant to researchers more generally in the life, health and social sciences. Register here
Nov 15 2022 10.00 - Nov 18 2022 13.00 Introduction to Statistics with R workshop, Nov 15 - 18 This workshop uses a public health dataset and examples but the materials are relevant to researchers more generally in the life, health and social sciences.
