Biostatistics 5 QA Exam Training

A general term that encompasses various AI systems, like ChatGPT, that excel in generating human-like text.

A specific type of generative AI model developed by OpenAI, known for its ability to generate human-like text, translate languages, and even write different kinds of creative content.

The specific type of neural network architecture used in ChatGPT.

A collection of related functions and subprograms that allow users to easily interact with ChatGPT's capabilities.

A statistical assumption that states there is a straight-line relationship between the predictor and response variable. This means changes in the predictor variable lead to proportional changes in the response variable.

A test used to check if the variance of the residuals (errors) in a regression model is constant across different values of the predictor variable.

A test used to detect if there is a relationship between the residuals (errors) in a regression model at different points in time. This occurs when residuals are not independent.

A statistical method used to adjust for the effects of a continuous variable (covariate) on the relationship between a predictor and response variable. This helps to improve the accuracy of the regression model.

A crucial assumption in ANCOVA. It means the relationship between the covariate and response variable is the same across all groups.

A technique used to evaluate the performance of a machine learning model by splitting the data into multiple sets and testing the model on each set independently.

A type of regression that employs a penalty term to shrink coefficients towards zero. This helps in selecting important variables and improving model performance.

A measure that combines goodness of fit and model complexity. A lower AIC suggests a better model with a balance between accuracy and simplicity.

A type of regression that is used when the data is independent and has a correlation structure. It accounts for individual subject variability.

An approach to regression modeling that aims to reduce dimensionality by using principal components for prediction. It helps to address multicollinearity.

A method for comparing means across multiple treatment groups while controlling for a single control group.

A statistical procedure for analyzing data with multiple factors (predictors). It's more sophisticated than ANOVA and allows for interaction effects.

A type of hypothesis test that assesses the significance of differences between means of multiple groups. It can be a one-way or two-way ANOVA.

A technique that considers how well a model predicts new, unseen data. It's important for assessing the generalizability of a model.

The process of creating and evaluating a statistical model with the goal of finding the best possible model based on available data.

A measure of the overall fit of a regression model. It indicates the proportion of variance in the response variable that is explained by the predictor variables.

The process of using AI systems, like ChatGPT, to generate code for various programming tasks, such as data analysis.

A type of error that occurs during the execution of code, mainly due to syntax issues.

A type of error that arises from misunderstandings between the prompt (user input) and the way ChatGPT interprets it.

The process of carefully crafting prompts for AI systems to elicit specific and relevant responses. It's about communicating effectively with AI.

A technique that involves refining prompts iteratively to obtain increasingly specific and focused outputs from ChatGPT.

A method for assessing the distribution of residuals (errors). If the residuals are not normally distributed, the model may not be accurate.

A potential problem that arises when predictor variables are highly correlated with each other. This can affect the accuracy and interpretation of regression models.

A measure that quantifies the degree of multicollinearity among predictor variables. High VIF values suggest strong correlations.

A type of plot that shows the residuals (errors) of a regression model against the predicted values. It helps to identify patterns that indicate problems with the model.

A data point that is significantly different from other data points in a dataset. Outliers can significantly affect the results of statistical analysis.

A method used to assess all possible combinations of group means and their differences. This helps to identify statistically significant contrasts, which are comparisons between groups that are of interest.