Fichas
Stat Test 1
Fichas del conjunto (23)
- 1What is a confounder?When investigating the relationship of X1 on Y, X2 is a confounder if it is associated with both (i.e. being breast fed --> success)
- 2What is one way to avoid confounding?Run a randomized experiment or adjust for confounders using multiple regression analysis
- 3RCT what does it stand for?Randomized Controlled Trial
- 4What is a control variable?Controls are the group that do not receive the treatment to compare them to the treatment population
- 5What is a blind study?Participants don't know if they are in the control or treatment group
- 6What is a double blind study?experimenters also don't know who is in the control or treatment group
- 7Why is randomization important?it means that the treatment variable, Z, is independent of all background variables (Z = 1 for treated, Z = 0 for control)
- 8What does randomization eliminate?1) eliminates selection bias (who gets treatment)
2) ensures that confounders are balanced across the two groups
3) allows for formal statistical procedures to analyze the results - 9What is selection bias?Who signs up or gets treatment within an experiment
- 10What does randomizing ensure regarding balance and confounders?The statistical distribution of any background var is same for treated as control group (i.e. diff of the distribution of a background variable - known and unknown looks the same for treatment and control groups --> if a difference in groups is found, it is because of the treatment and not the background vars)
- 11Quantile Plotshelps us to assess if a data set plausibly came from a theoretical distribution (i.e. Normal, exponential) --> line that's roughly straight = Normal
- 12difficulties with experimentsethical concerns, financial and time constraints, compliance, spillovers
sometimes, you have to use observational data - 13Difference between experimental vs. observational dataexperimental = run a study
observational = see it - 14What is the biggest problem with doing comparisons in observational datasetsconfounding variables
- 15why do confounding variables show up in observational data setsmostly self-selection
- 16How should you interpret data form an observational study?udy?cautiously, because of the possibility of confounding
- 17Most important question re: dataWhere did data come from?
- 18Survivorship biasSurvivorship bias or survivor bias is the tendency to view the performance of existing stocks or funds in the market as a representative comprehensive sample without regarding those that have gone bust.
- 19cross-sectional data studyA cross-sectional study is a type of observational research that analyzes data of variables collected at one given point in time across a sample population or a pre-defined subset.
- 20time series analysisTime series analysis is a specific way of analyzing a sequence of data points collected over an interval of time. In time series analysis, analysts record data points at consistent intervals over a set period of time rather than just recording the data points intermittently or randomly.
- 21panel data studyPanel data, sometimes referred to as longitudinal data, is data that contains observations about different cross sections across time. Examples of groups that may make up panel data series include countries, firms, individuals, or demographic groups.
- 22cohort studiesCohort studies are a type of longitudinal study—an approach that follows research participants over a period of time (often many years). Specifically, cohort studies recruit and follow participants who share a common characteristic, such as a particular occupation or demographic similarity.
- 23Simpson's paradoxSimpson's Paradox is a statistical phenomenon where an association between two variables in a population emerges, disappears or reverses when the population is divided into subpopulations
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- 12th grade Statistics Fichas sobre Stat Test 1, creado por Sara Ganz el 03/10/2022.
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- Sara Ganz
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