Search this site
Embedded Files
Skip to main content
Skip to navigation
Analytic Resources
Home
Foundational Concepts
Critical Thinking
AI and Gen AI
Analytics Overview
Data and Data Collection
Variables Types
Data Management
Descriptive Statistics
MCT
Variability
Visualizing Data
Hypothesis Testing
CLT
Confidence Intervals
Issues with NHST
Inferential Errors and Power
Effect Size
Missing Data
Correlations and Regression
Correlations
Linear Regression
Relative Importance Analysis
Non-Linear Regression
Interaction-Moderation
Indirect-Mediation
Maximum Likelihood Estimation
Generalized Linear Models
Logistic Regression
ROC, Sensitive, and Specificity
ANOVA
Between Groups ANOVA
Within Subjects ANOVA
Mixed Model ANOVA
ANCOVA
EFA and PCA
Linear Mixed Model
Cross Validation
R Resources
Getting Started in R and RStudio
Directories, Scripts, and Code
Packages and Libraries
SWIRL- Get Started
Dataframes and Types of Data
Importing Data
Generative AI and R
Getting to Know Your Data
Numeric Summaries
Descriptive Visuals
Pie Chart
Bar Chart
Histogram
Box Plot
Automated Exploration
Data Wrangling
Adding Labels
Renaming Variables
Missing Data
Data Recodes
Row Functions
Concatenate
Lag Functions
Reshaping Data
Subsetting
Group Functions
Merging Data
Dates and Times
Duplicate and Unique Cases
Missing Data
Correlations
OLS Regression
Non-Linear Regression
Interactions and Moderation
Indirect and Mediation Effects
PROCESS packages
ANOVA
Statistical Power
Dimension Reduction
Relative Importance Analysis
GZLM
Logistic Regression
Linear Mix Models
Cross Validation
jamovi Resources
Getting Started
Import Data & Types
Modules & R Code
Wrangling Data
Data Exploration
Correlations
General, Mixed and Generalized Models
OLS Regression
Non-Linear Regression
Interaction-Moderation
Indirect and Mediation Effects
ANOVA
Linear Mix Models
Logistic Regression
Statistical Power
EFA and PCA
Analytic Resources
Home
Foundational Concepts
Critical Thinking
AI and Gen AI
Analytics Overview
Data and Data Collection
Variables Types
Data Management
Descriptive Statistics
MCT
Variability
Visualizing Data
Hypothesis Testing
CLT
Confidence Intervals
Issues with NHST
Inferential Errors and Power
Effect Size
Missing Data
Correlations and Regression
Correlations
Linear Regression
Relative Importance Analysis
Non-Linear Regression
Interaction-Moderation
Indirect-Mediation
Maximum Likelihood Estimation
Generalized Linear Models
Logistic Regression
ROC, Sensitive, and Specificity
ANOVA
Between Groups ANOVA
Within Subjects ANOVA
Mixed Model ANOVA
ANCOVA
EFA and PCA
Linear Mixed Model
Cross Validation
R Resources
Getting Started in R and RStudio
Directories, Scripts, and Code
Packages and Libraries
SWIRL- Get Started
Dataframes and Types of Data
Importing Data
Generative AI and R
Getting to Know Your Data
Numeric Summaries
Descriptive Visuals
Pie Chart
Bar Chart
Histogram
Box Plot
Automated Exploration
Data Wrangling
Adding Labels
Renaming Variables
Missing Data
Data Recodes
Row Functions
Concatenate
Lag Functions
Reshaping Data
Subsetting
Group Functions
Merging Data
Dates and Times
Duplicate and Unique Cases
Missing Data
Correlations
OLS Regression
Non-Linear Regression
Interactions and Moderation
Indirect and Mediation Effects
PROCESS packages
ANOVA
Statistical Power
Dimension Reduction
Relative Importance Analysis
GZLM
Logistic Regression
Linear Mix Models
Cross Validation
jamovi Resources
Getting Started
Import Data & Types
Modules & R Code
Wrangling Data
Data Exploration
Correlations
General, Mixed and Generalized Models
OLS Regression
Non-Linear Regression
Interaction-Moderation
Indirect and Mediation Effects
ANOVA
Linear Mix Models
Logistic Regression
Statistical Power
EFA and PCA
More
Home
Foundational Concepts
Critical Thinking
AI and Gen AI
Analytics Overview
Data and Data Collection
Variables Types
Data Management
Descriptive Statistics
MCT
Variability
Visualizing Data
Hypothesis Testing
CLT
Confidence Intervals
Issues with NHST
Inferential Errors and Power
Effect Size
Missing Data
Correlations and Regression
Correlations
Linear Regression
Relative Importance Analysis
Non-Linear Regression
Interaction-Moderation
Indirect-Mediation
Maximum Likelihood Estimation
Generalized Linear Models
Logistic Regression
ROC, Sensitive, and Specificity
ANOVA
Between Groups ANOVA
Within Subjects ANOVA
Mixed Model ANOVA
ANCOVA
EFA and PCA
Linear Mixed Model
Cross Validation
R Resources
Getting Started in R and RStudio
Directories, Scripts, and Code
Packages and Libraries
SWIRL- Get Started
Dataframes and Types of Data
Importing Data
Generative AI and R
Getting to Know Your Data
Numeric Summaries
Descriptive Visuals
Pie Chart
Bar Chart
Histogram
Box Plot
Automated Exploration
Data Wrangling
Adding Labels
Renaming Variables
Missing Data
Data Recodes
Row Functions
Concatenate
Lag Functions
Reshaping Data
Subsetting
Group Functions
Merging Data
Dates and Times
Duplicate and Unique Cases
Missing Data
Correlations
OLS Regression
Non-Linear Regression
Interactions and Moderation
Indirect and Mediation Effects
PROCESS packages
ANOVA
Statistical Power
Dimension Reduction
Relative Importance Analysis
GZLM
Logistic Regression
Linear Mix Models
Cross Validation
jamovi Resources
Getting Started
Import Data & Types
Modules & R Code
Wrangling Data
Data Exploration
Correlations
General, Mixed and Generalized Models
OLS Regression
Non-Linear Regression
Interaction-Moderation
Indirect and Mediation Effects
ANOVA
Linear Mix Models
Logistic Regression
Statistical Power
EFA and PCA
ROC, Sensitive, and Specificity
Understanding Confusion Matrix
When we get the data, after data cleaning, pre-processing, and wrangling, the first step we do is to feed it to an outstanding model and of course, get output in probabilities. But hold on! How in…
Understanding AUC - ROC Curve
In Machine Learning, performance measurement is an essential task. So when it comes to a classification problem, we can count on an AUC - ROC Curve. When we need to check or visualize the performance…
StatQuest- ROC and AUC, Clearly Explained! (16:16)
MedCram- Sensitivity and Specificity Explained Clearly (12:14)
Clinical Information Sciences- Medical Statistics: Calculating Sensitivity and Specificity using a 2x2 table (1:42)
Shaneyfelt- How to interpret ROC curves (5:25)
Report abuse
Report abuse