This page provides an overview of the available videos in the Radiant Tutorial Series. For each of the modules below, it is useful to leverage RStudio Projects to set up the environment to more easily access data and models from Radiant. Open RStudio and cut/paste the given command + URL into the console. This will download the assignment and supporting files and subsequently open a new RStudio project. You will know it is working if you look at the top right-hand corner of RStudio and see the module name (e.g., “decision_tree”) and see the relevant module files in the bottom right pane. From here, you will simply need to click on “Addins” on the top menu and then “Start radiant” to follow along with the tutorial.
In additional to the links below, you can access the tutorial playlist on Youtube.
Decision Analysis
Copy-and-paste the full command below into the RStudio console (i.e., the bottom-left window) and press return to gain access to all materials used in the decision tree module:
usethis::use_course("https://www.dropbox.com/sh/bit4p1ffbkb2dgh/AACm1RVy2BxBDiVbjoLiN5_Ea?dl=1")
- Introduction to Decision Analysis (#1)
- This video walks you through the required steps to construct and solve a basic decision tree by hand
- Topics List:
- Chance nodes vs. decision nodes
- Folding back the tree (i.e., start from the right-most nodes and work backwards to the left-most nodes)
- Introduction to Decision Analysis (#1)
- This video walks you through the required steps to construct and solve a basic decision tree by hand
- Topics List:
- Chance nodes vs. decision nodes
- Folding back the tree (i.e., start from the right-most nodes and work backwards to the left-most nodes)
- Using Radiant to Construct a Decision Tree (#2)
- This video demonstrates how to construct a basic decision tree in Radiant
- Topics List:
- Rename a tree file
- Construct a tree (following the rules for decision tree input)
- Interpret the results (initial tree vs final tree)
- Save the decision tree input .yaml file
- How to Write Decision Tree Results into a Report (#3)
- This video demonstrates how to construct a basic decision tree in Radiant and add the generated R-code to report
- Topics List:
- Construct a decision tree and define variables in the decision tree
- Add multiple trees to a report
- Demo some useful keyboard shortcuts
- Save the Radiant state file and the report
- Sensitivity Analysis of Decision Tree (#4)
- This video shows two ways to conduct sensitivity analysis of a decision tree in Radiant
- Topics List:
- Quick review of writing decision tree results to a report
- Method 1: manually update the value
- Method 2: use “variables”
- How to Debug Decision Tree Input (#5)
- This video demonstrates how to debug decision tree input if you see an error message
- Topics List:
- Colon missing
- Indent issue
- Probabilities don’t sum to 1
- Value missing
- Decision Trees with Imperfect Information (#6)
- This video shows how to determine the appropriate (conditional) probabilities to use in a decision tree when the available information is imperfect
- Topics List:
- Imperfect information
- Test
- Conditional probabilities
- Solving a Decision Tree with Imperfect Information (#7)
- This video shows how to use Radiant to construct and solve a decision tree when the available information is imperfect
- Topics List:
- Specify variables
- Build a tree with imperfect information
- Check the tree
- Interpret the decision tree result
- Writing Decision Tree with Sub-trees in Radiant (#8)
- This video shows how to construct a decision tree with sub-trees in radiant
- Topics List:
- Create a main tree that references a sub-tree
- Specify a sub-tree that references the main tree in the variables section
Probability Calculator
Copy-and-paste the full command below into the RStudio console (i.e., the bottom-left window) and press return to gain access to all materials used in the probability calculator module:
usethis::use_course("https://www.dropbox.com/sh/zw1yuiw8hvs47uc/AABPo1BncYv_i2eZfHQ7dgwCa?dl=1")
- Describing the Distribution of a Discrete Random Variable (#1)
- This video shows how to summarize information about a discrete random variable using the probability calculator in Radiant
- Topics List:
- Calculate the mean and variance for a discrete random variable by hand
- Calculate the mean, variance, and select probabilities for a discrete random variable in Radiant
- Describing Normal and Binomial Distributions in Radiant(#2)
- This video shows how to summarize information about Normal and Binomial distributions using the probability calculator in Radiant
- Topics List:
- Calculate probabilities of a random variable following a Normal distribution in Radiant
- Calculate probabilities of a random variable following a Binomial distribution by hand
- Calculate probabilities of a random variable following a Binomial distribution in Radiant
- Describing Uniform and Binomial Distributions in Radiant(#3)
- This video shows how to summarize information about Uniform and Binomial distributions using the probability calculator in Radiant
- Topics List:
- Calculate probabilities of a random variable following a Uniform distribution in Radiant
- Calculate probabilities of a random variable following a Binomial distribution in Radiant
- Providing Probability Bounds(#4)
- This video demonstrates how to provide probability bounds in Radiant
- Topics List:
- Use probabilities as input type
- Round up the cutoff value
Hypothesis Testing
Copy-and-paste the full command below into the RStudio console (i.e., the bottom-left window) and press return to gain access to all materials used in the hypothesis testing module:
usethis::use_course("https://www.dropbox.com/sh/0xvhyolgcvox685/AADSppNSIocrJS-BqZXhD1Kna?dl=1")
- Single Mean Hypothesis Test (#1)
- This video shows how to test a hypothesis about a single sample mean versus a population mean
- Topics List:
- Calculate summary statistics for a sample
- Setup a hypothesis test for a single mean in Radiant
- Use the p.value, confidence interval, or critical value to evaluate the hypothesis test
- Single Proportion Hypothesis Test (#2)
- This video shows how to test a hypothesis about a single sample proportion versus a population proportion
- Topics List:
- Setup a hypothesis test for a single proportion in Radiant
- Use the p.value, confidence interval, or critical value to evaluate the hypothesis test
- Compare Means Hypothesis Test (#3)
- This video shows how to conduct a compare means hypothesis test
- Topics List:
- Calculate summary statistics by groups
- Setup a hypothesis test for compare means in Radiant
- Use the p.value and confidence interval to evaluate the hypothesis test
- Compare Proportions Hypothesis Test (#4)
- This video shows how to conduct a compare proportions hypothesis test
- Topics List:
- Setup a hypothesis test for compare means in Radiant
- Use the p.value and confidence interval to evaluate the hypothesis test
- Cross-tabs Hypothesis Test (#5)
- This video demonstrates how to investigate associations between two categorical variables by a cross-tabs hypothesis test
- Topics List:
- Setup a hypothesis test for cross-tabs in Radiant
- Explain how observed, expected and contribution to chi-squared tables are constructed
- Use the p.value and critical value to evaluate the hypothesis test
Linear Regression
Copy-and-paste the full command below into the RStudio console (i.e., the bottom-left window) and press return to gain access to all materials used in the linear regression module:
usethis::use_course("https://www.dropbox.com/sh/s70cb6i0fin7qq4/AACje2BAivEKDx7WrLrPr5m9a?dl=1")
Data Exploration and Pre-check of Regression (#1)
- This video shows how to use Radiant to explore and visualize data before running a linear regression
- Topics List:
Interpretation of Regression Results and Prediction (#2)
- This video explains how to interpret the regression results and calculate the predicted value from a linear regression model
- Topics List:
- Interpret coefficients (numeric and categorical variables)
- Interpret R-squared and adjusted R-squared
- Interpret F-test result
- Predict from a regression model
Dealing with Categorical Variables (#3)
- This video shows how to deal with categorical variables in a linear regression model
- Topics List:
- Check the baseline category in Radiant
- Change the baseline category
Adding New Variables into a Regression Model (#4)
- This video demonstrates how to test if adding new variables will lead to a better model with significantly higher explanatory power
- Topics List:
- Set up a hypothesis test for adding new variables in Radiant
- Interpret the F-test results
- Compare this F-test to the default F-test in regression summary
Linear Regression Validation (#5)
- This video demonstrates how to validate a linear regression model
- Topics List:
- Linearity (scatter plots, same as the one in the pre-check)
- Normality Check (Normal Q-Q plot)
- Multicollinearity (VIF)
- Heteroscedasticity
Log-log Regression (#6)
- This video demonstrates when and how to run a log-log regression
- Topics List:
- Transform data with skewed distributions by natural log function
- Interpret the coefficients in a log-log regression
Simulation
Copy-and-paste the full command below into the RStudio console (i.e., the bottom-left window) and press return to gain access to all materials used in the simulation module:
usethis::use_course("https://www.dropbox.com/sh/72kpk88ty4p1uh5/AABWcfhrycLzCuCvI6FRu0zia?dl=1")
- Setting Up a Simulation in Radiant (#1)
- This video demonstrates how to use Radiant to set up a simulation
- Topics List:
- Brief introduction to the Poisson distribution
- Specifying a simulation
- Interpretation of the simulation summary
- Setting Up a Repeated Simulation in Radiant (#2)
- This video shows how to use Radiant to set up a repeated simulation
- Topics List:
- Specifying a repeated simulation
- Interpretation of the repeated simulation summary
- Using simulation to solve probability questions (#3)
- This video demonstrates how to use simulation to solve probability questions in Radiant
- Topics List:
- Review of setting up a (repeated) simulation
- Interpretation of the simulation summary
- Intuition of how repeated simulations work
- Simulation Formula Tips (#4)
- This video discusses some helpful functions that are commonly used in simulation formulas
- Topics List:
- Use
ifelse
to specify a simulation formula
- Use
pmax
to specify a simulation formula
- Using Grid Search in Simulation (#5)
- This video demonstrates how to use grid search in simulation
- Topics List:
- Find an optimal value by sorting simulated data or creating a plot
- Find an optimal value by using
find_max
function
© Vincent Nijs (2019)