AP Stat Ch 4 Flashcards
Experiment
Investigates how a response variable behaves when the researcher manipulates one or more factors (or explanatory variables). The purpose is usually to determine if changes in the explanatory variable cause changes in the response variable (what you are measuring). An experiment deliberately imposes some treatment on individuals to observe their response
Observational study
Investigates characteristics of a sample in order to draw conclusions about a population
Does not attempt to influence responses.
Confounding variable
Variable related to both the explanatory variable and to the response variable
Simulation
A simulation consists of a collection of things that happen at random. There is a simulation that is repeated. These situations are called components of the simulation. Each component has a set of possible outcomes
Population
Entire group of individuals that we want information about in a statistical study
Sample
Part of the population from which we actually collect information. Use the info from the sample to draw conclusions about the entire population
Voluntary response
People who choose themselves by responding to a general appeal. This type of sample shows bias because people with strong opinions, often in the same direction, are most likely to respond.
Convenience sampling
Choosing the individuals easiest to reach. Biased
Bias
Favors some part of the population over others. The design of a study is biased if it systemically favors certain outcomes
When describing bias, identify the direction of the bias!
Simple random sample
Simple random sample (SRS) of size n consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance to be the sample actually selected.
Use calculator or tablet in textbook
Population of interest vs inference
Population of interest is the population we want to know about and the population of inference is the population we can actually make conclusions about based on the subjects chosen in the sample.
If there is selection bias, then these populations aren’t the same
Stratified random sample
Separate the population into like strata and then randomly pick from within each group and choose porpoprtiojallg.
Cluster sample
Cluster sampling divides the population into groups, which should mirror the characteristics of the population. Then choose an SRS of these clusters. All the individuals in the chosen clusters are selected to be in the sample.
Disadvantages of SRS
large sample is hard to do
Doesn’t guarantee sample will be reperesentative of the population. Possible certain groups are over or under represented by chance
Systematic sample
k= N / n where N is popilation size and n is sample size. Every kth person selected is chosen