Канал: Mine Çetinkaya-Rundel

Visualizing Data

Visualizing Data

ASA DataFest 2022 @dukeuniversity

ASA DataFest 2022 @dukeuniversity

Exporting PDF out of RStudio container

Exporting PDF out of RStudio container

Feedback at scale (promo)

Feedback at scale (promo)

IDS - Week 11 - Code along

IDS - Week 11 - Code along

IDS - Week 11 - 06 - Wrapping up IDS!

IDS - Week 11 - 06 - Wrapping up IDS!

IDS - Week 11 - 05 - Machine learning

IDS - Week 11 - 05 - Machine learning

IDS - Week 11 - 04 - Interactive web apps

IDS - Week 11 - 04 - Interactive web apps

IDS - Week 11 - 01 - Keeping up with IDS

IDS - Week 11 - 01 - Keeping up with IDS

IDS - Week 11 - 03 - Comparing texts

IDS - Week 11 - 03 - Comparing texts

IDS - Week 11 - 02 - Text analysis

IDS - Week 11 - 02 - Text analysis

IDS - Week 10 - 06 - Bootstrapping

IDS - Week 10 - 06 - Bootstrapping

IDS - Week 10 - 05 - Quantifying uncertainty

IDS - Week 10 - 05 - Quantifying uncertainty

IDS - Week 10 - 04 - AE - The Office, Part 2

IDS - Week 10 - 04 - AE - The Office, Part 2

IDS - Week 10 - 03 - AE - The Office, Part 1

IDS - Week 10 - 03 - AE - The Office, Part 1

IDS - Week 10 - 01 - Keeping up with IDS

IDS - Week 10 - 01 - Keeping up with IDS

IDS - Week 10 - 02 - Cross validation

IDS - Week 10 - 02 - Cross validation

IDS - Week 09 - Code along

IDS - Week 09 - Code along

IDS - Week 09 - 04 - Feature engineering

IDS - Week 09 - 04 - Feature engineering

IDS - Week 09 - 01 - Keeping up with IDS

IDS - Week 09 - 01 - Keeping up with IDS

IDS - Week 09 - 03 - Prediction and overfitting

IDS - Week 09 - 03 - Prediction and overfitting

IDS - Week 09 - 02 - Logistic regression

IDS - Week 09 - 02 - Logistic regression

IDS - Week 08 - Code-along

IDS - Week 08 - Code-along

IDS - Week 08 - 05 - Models with multiple predictors

IDS - Week 08 - 05 - Models with multiple predictors

IDS - Week 08 - 06 - More models with multiple predictors

IDS - Week 08 - 06 - More models with multiple predictors

Improve your workflow for reproducible science

Improve your workflow for reproducible science

IDS - Week 08 - 04 - Modelling nonlinear relationships

IDS - Week 08 - 04 - Modelling nonlinear relationships

IDS - Week 08 - 03 - Fitting and interpreting models

IDS - Week 08 - 03 - Fitting and interpreting models

IDS - Week 08 - 02 - The language of models

IDS - Week 08 - 02 - The language of models

IDS - Week 08 - 01 - Keeping up with IDS

IDS - Week 08 - 01 - Keeping up with IDS

IDS - Week 07 - Code along

IDS - Week 07 - Code along

IDS - Week 07 - 04 - Algorithmic bias

IDS - Week 07 - 04 - Algorithmic bias

IDS - Week 07 - 03 - Data privacy

IDS - Week 07 - 03 - Data privacy

IDS - Week 07 - 02 - Misrepresentation

IDS - Week 07 - 02 - Misrepresentation

IDS - Week 07 - 01 - Keeping up with IDS

IDS - Week 07 - 01 - Keeping up with IDS

IDS - Week 06 - Code along

IDS - Week 06 - Code along

IDS - Week 06 - 07 - Iteration

IDS - Week 06 - 07 - Iteration

IDS - Week 06 - 06 - Functions

IDS - Week 06 - 06 - Functions

IDS - Week 06 - 05 - AE: IMDB + Web scraping

IDS - Week 06 - 05 - AE: IMDB + Web scraping

IDS - Week 06 - 04 - Web scraping considerations

IDS - Week 06 - 04 - Web scraping considerations

IDS - Week 06 - 03 - Scraping IMDB Top 250

IDS - Week 06 - 03 - Scraping IMDB Top 250

IDS - Week 06 - 02 - Web scraping

IDS - Week 06 - 02 - Web scraping

IDS - Week 06 - 01 - Keeping up with IDS

IDS - Week 06 - 01 - Keeping up with IDS

IDS - Week 05 - Code along

IDS - Week 05 - Code along

IDS - Week 05 - 05 - Simpson's paradox

IDS - Week 05 - 05 - Simpson's paradox

IDS - Week 05 - 06 - Doing data science

IDS - Week 05 - 06 - Doing data science

IDS - Week 05 - 04 - Scientific studies and confounding

IDS - Week 05 - 04 - Scientific studies and confounding

IDS - Week 05 - 01 - Keeping up with IDS

IDS - Week 05 - 01 - Keeping up with IDS

IDS - Week 04 - 07 - AE: Nobels & sales + Data import

IDS - Week 04 - 07 - AE: Nobels & sales + Data import

IDS - Week 04 - Code along

IDS - Week 04 - Code along

IDS - Week 05 - 03 - AE: Brexit + Telling stories with dataviz

IDS - Week 05 - 03 - AE: Brexit + Telling stories with dataviz

IDS - Week 05 - 02 - Tips for effective data visualisation

IDS - Week 05 - 02 - Tips for effective data visualisation

IDS - Week 04 - 06 - AE: Hotels + data types

IDS - Week 04 - 06 - AE: Hotels + data types

IDS - Week 04 - 04 - Importing data

IDS - Week 04 - 04 - Importing data

IDS - Week 04 - 05 - Recoding data

IDS - Week 04 - 05 - Recoding data

IDS - Week 04 - 03 - Data classes

IDS - Week 04 - 03 - Data classes

IDS - Week 04 - 02 - Data types

IDS - Week 04 - 02 - Data types

IDS - Week 04 - 01 - Keeping up with IDS

IDS - Week 04 - 01 - Keeping up with IDS

IDS - Week 03 - AE: Hotels + Data wrangling

IDS - Week 03 - AE: Hotels + Data wrangling

IDS - Week 03 - Code along

IDS - Week 03 - Code along

IDS - Week 03 - 06 - Tidying data

IDS - Week 03 - 06 - Tidying data

IDS - Week 03 - 05 - Working with multiple data frames

IDS - Week 03 - 05 - Working with multiple data frames

IDS - Week 03 - 04 - Working with a single data frame

IDS - Week 03 - 04 - Working with a single data frame

IDS - Week 03 - 03 - Grammar of data wrangling

IDS - Week 03 - 03 - Grammar of data wrangling

IDS - Week 03 - 02 - Tidy data

IDS - Week 03 - 02 - Tidy data

IDS - Week 03 - 01- Keeping up with IDS

IDS - Week 03 - 01- Keeping up with IDS

IDS - Week 02 - Code-along

IDS - Week 02 - Code-along

IDS - Week 02 - 06 - AE: StarWars + Dataviz

IDS - Week 02 - 06 - AE: StarWars + Dataviz

IDS - Week 02 - 01 - KUWIDS

IDS - Week 02 - 01 - KUWIDS

IDS - Week 02 - 05 - Visualising categorical data

IDS - Week 02 - 05 - Visualising categorical data

IDS - Week 02 - 04 - Visualising numerical data

IDS - Week 02 - 04 - Visualising numerical data

IDS - Week 02 - 03 - Visualising data with ggplot2

IDS - Week 02 - 03 - Visualising data with ggplot2

IDS - Week 02 - 02 - Data and visualisation

IDS - Week 02 - 02 - Data and visualisation

IDS - Week 01 - Code-along

IDS - Week 01 - Code-along

IDS - Week 01 - 06 - Meet the toolkit: Version control and collaboration

IDS - Week 01 - 06 - Meet the toolkit: Version control and collaboration

IDS - Week 01 - 05 - Meet the toolkit: Programming

IDS - Week 01 - 05 - Meet the toolkit: Programming

IDS - Week 01 - 04 - Meet the toolkit: Course operation

IDS - Week 01 - 04 - Meet the toolkit: Course operation

IDS - Week 01 - 03 - Course information

IDS - Week 01 - 03 - Course information

IDS - Week 01 - 02 - AE: First dataviz

IDS - Week 01 - 02 - AE: First dataviz

IDS - Week 01 - 01 - Welcome to IDS!

IDS - Week 01 - 01 - Welcome to IDS!

Falkirk Wheel

Falkirk Wheel

RStudio Cloud to GitHub

RStudio Cloud to GitHub

GitHub to RStudio Cloud

GitHub to RStudio Cloud

Teaching Remotely

Teaching Remotely

First Year as Faculty

First Year as Faculty

Opportunities in Statistics Education Research

Opportunities in Statistics Education Research

Teaching Focused Career Opportunities

Teaching Focused Career Opportunities

Implementing GAISE Recommendations for Teaching Introductory Statistics

Implementing GAISE Recommendations for Teaching Introductory Statistics

ASA DataFest

ASA DataFest

RStudio Cloud - Add base project to workspace, instructor view

RStudio Cloud - Add base project to workspace, instructor view

RStudio Cloud - Joining a workspace, student view

RStudio Cloud - Joining a workspace, student view

RStudio Cloud - Creating a workspace, instructor view

RStudio Cloud - Creating a workspace, instructor view

RStudio Cloud, Single project - student view

RStudio Cloud, Single project - student view

RStudio Cloud - Single project, instructor view

RStudio Cloud - Single project, instructor view

Getting started with RStudio Cloud

Getting started with RStudio Cloud

6 4 Homogeneity and independence in two way tables

6 4 Homogeneity and independence in two way tables

6 3 Testing for goodness of fit using chi square

6 3 Testing for goodness of fit using chi square

5 5C Multiple comparisons

5 5C Multiple comparisons

5 5B Conditions for ANOVA

5 5B Conditions for ANOVA

5 5A ANOVA Introduction

5 5A ANOVA Introduction

5 4 Power Calculations for difference of two means

5 4 Power Calculations for difference of two means

5 3 Difference of two independent means

5 3 Difference of two independent means

5 2 Inference for paired data

5 2 Inference for paired data

5 1B Inference for a mean

5 1B Inference for a mean

5 1A t distribution

5 1A t distribution

Sta199 - Lab1 - First commit and push

Sta199 - Lab1 - First commit and push

Sta199 - Lab1 - Git configuration

Sta199 - Lab1 - Git configuration

Sta199 - Lab1 - Getting started with R/RStudio/Git/GitHub

Sta199 - Lab1 - Getting started with R/RStudio/Git/GitHub

01 01 A Introduction

01 01 A Introduction

Ds12

Ds12

Sta 101 - S16 - DS 6: MT1 Review

Sta 101 - S16 - DS 6: MT1 Review

Normal approximation to binomial

Normal approximation to binomial

Probability Trees

Probability Trees

Normal Distribution - Finding Probabilities

Normal Distribution - Finding Probabilities

Inference for difference of two means

Inference for difference of two means

Working with the CLT for means

Working with the CLT for means

Inference for comparing many means (ANOVA)

Inference for comparing many means (ANOVA)

Sampling distribution for proportions

Sampling distribution for proportions

Sample vs. sampling distribution

Sample vs. sampling distribution

Prediction and Confidence Intervals for SLR

Prediction and Confidence Intervals for SLR

Exploring relationships between categorical variables

Exploring relationships between categorical variables

Visualizing distributions of numerical variables

Visualizing distributions of numerical variables

Mean, median, and mode

Mean, median, and mode

Random sampling vs. random assignment

Random sampling vs. random assignment

Types of variables

Types of variables

Inference for comparing many proportions (Chi-square test of independence)

Inference for comparing many proportions (Chi-square test of independence)

Inference for difference of two proportions

Inference for difference of two proportions

Inference for one proportion

Inference for one proportion

Inference for paired means

Inference for paired means

Inference for one mean

Inference for one mean

Binomial Distribution - Finding Probabilities

Binomial Distribution - Finding Probabilities

Normal Distribution - Finding Cutoff Points

Normal Distribution - Finding Cutoff Points