STATISTICS - EXPERIMENT DESIGN

  • Convenience Sample: A sample of individuals easily accessible to the researcher. This method is quick but often leads to bias as it may not accurately represent the entire population.

  • Systematic Random Sample: A sample created by selecting every kth individual from an ordered list of the population. The starting point is chosen randomly.

  • Question of Interest: The specific question a researcher is trying to answer.

  • Statistic: A numerical value that describes a sample, like the average height of students in a randomly selected class.

  • Nonresponse: Occurs when an individual selected for a survey doesn't participate, which can introduce bias if those who don't respond differ from those who do.

  • Simple Random Sample: A method where every individual and every group of individuals in a population has an equal chance of being selected for the sample. This is the gold standard for unbiased sampling.

Image of simple random sampling
  • Multistage Random Sample: A sampling technique that involves multiple stages of random selection. For example, first randomly selecting states, then randomly selecting cities within those states, and finally randomly selecting households within those cities.

  • Geographic Limitation: A bias that occurs when a study is limited to a specific geographic area, making its findings difficult to generalize to other regions.

  • Census: A survey that attempts to collect data from every single member of a population.

  • Wording Effects: The influence of how questions are phrased, which can introduce bias by leading a person toward a particular answer.

  • Cluster Random Sample: A sampling method where the population is divided into groups (clusters), and a random sample of these clusters is chosen. All individuals within the selected clusters are then surveyed.

  • Parameter: A numerical value that describes an entire population, which is typically unknown. For example, the true average height of all students in a school.

  • Undercoverage: A bias that happens when some members of the population are not included in the sampling frame and thus have no chance of being selected.

  • Response Bias: The tendency of a person to give an inaccurate or untruthful answer, possibly due to social pressure or the desire to please the interviewer.

  • Stratified Random Sample: A sampling method where the population is divided into homogeneous subgroups (strata), and a simple random sample is taken from each stratum to ensure representation from all groups.

Image of stratified random sampling

  • Bias: A systematic error in a study that results in an over- or underestimation of the true population parameter.

  • Population: The entire group of individuals that a researcher is interested in studying.

  • Voluntary Response Sample: A sample made up of individuals who choose to participate in a survey. This often leads to strong bias because people with strong opinions are more likely to respond.

  • Statistical Inference: The process of using data from a sample to draw conclusions about a larger population.


Experimental Designs

  • Experiment: A study where the researcher deliberately applies a treatment to a group of subjects to observe the effect.

  • Factors: The independent variables that are manipulated by the researcher. For example, in a study on plant growth, the type of fertilizer and the amount of water could be factors.

  • Double Blind Test: An experiment where neither the subjects nor the researchers know who is receiving the treatment and who is in the control group. This prevents bias from both sides.

  • Statistically Significant: A result that is unlikely to have occurred by random chance.

  • Multiple Analysis: The practice of analyzing data in several different ways to ensure the findings are robust and not a result of a specific statistical method.

  • Control Group: The group that does not receive the treatment or receives a placebo. It serves as a baseline for comparison.

  • Replication: The process of repeating an experiment with different groups of subjects to confirm the original findings and ensure they were not due to chance.

  • Observational Study: A study where researchers observe and measure variables without attempting to influence the outcomes. This type of study can show correlation but not causation.

  • Lack of Realism: A limitation that occurs when the experimental setting is so artificial that the results can't be generalized to real-world situations.

  • Blind Test: An experimental procedure where the subjects do not know if they are receiving the treatment or a placebo. This helps to prevent the placebo effect.

  • Random Assignment: The process of assigning subjects to different experimental groups (treatment and control) by chance. This helps to create equivalent groups and reduces the impact of confounding variables.

  • Confounding Variables: Extraneous variables that influence both the independent and dependent variables, potentially creating a false association between them.

  • Treatment: The specific experimental condition applied to the subjects.

  • Media Bias: The tendency for news outlets to slant their reporting, which can influence public perception of a study's results.

  • Placebo: An inactive substance or treatment given to the control group to mimic the treatment and account for the psychological effects of receiving a treatment.

  • Anecdotal Evidence: Evidence based on personal accounts or stories, which is often unreliable and can't be used to make broad conclusions.

  • Response Variable: The dependent variable that is measured to see if it's affected by the treatment.

  • Psychological Effects: Changes in a person's health or behavior that are caused by their beliefs or expectations about a treatment.

  • Control: The overall effort to keep all conditions in an experiment constant except for the treatment.

  • Subjects: The individuals or units on whom the experiment is conducted.