Psych Statistics Chapter 5 and 6

• A random sample is where every member of the population has an equal chance of being selected into the study
• A convenience sample uses participants that are readily available
• Generalizability is the researchers ability to apply findings from one sample or in one context to other samples or contexts
• Generalizability is also known as External Validity
• Replication is the duplication of scientific results in a different context or with a sample that has different characteristics
• Replication is also known as Reproducibility
• A Volunteer (self-selected) Sample is a convenience sample in which participants actively choose to participate in a study
• Crowdsourcing occurs when a research team solicits input from a very large group of people, usually recruited online
• WEIRD Samples are samples of participants from countries what are

  • Western
  • Educated
  • Industrialized
  • Rich
  • Democratic
• A Constraints on Generality (COG) Statement is a statement of the target population to which the study results should generalize
• Confirmation Bias is our usually unintentional tendency to pay attention to evidence that confirms what we already believe and to ignore evidence that would disconfirm our beliefs
• Illusory Correlation is the phenomenon of believing one sees an association between variables when no such association exists
• Personal Probability is a persons own judgement about the likelihood an event will occur
• Personal Probability is also known as Subjective Probability
• Probability is the likelihood that a particular outcome -out of all possible outcomes- will occur
• Expected Relative-Frequency Probability is the likelihood of an event occurring, based on the actual outcome of many, many trials
• A trial is each occasion that a given procedure is carried out
• The outcome is the result of a trial
• Success is the outcome for which we're trying to determine the probability
• The Control Group is a level of the independent variable that does not receive the treatment of interest in a study
• The Experimental Group is a level of the independent variable that receives treatment to intervention of interest
• The null hypothesis is a statement that postulates that there is no difference between populations or that the difference is in a direction opposite to that anticipated by the researcher
• A Type I Error is where we reject the null hypothesis but the null hypothesis is correct (false positive)
• A Type II Error is where we fail to reject the null hypothesis but the null hypothesis is false (false negative)
• Descriptive Statistics describes one group of people or sample
• Inferential Statistics uses a sample data to make estimates about the larger population
• A normal curve is a specific bell-shaped curve that is unimodal, symmetric, and defined mathematically
• Standardization is a way to convert individual scores from different normal distributions to a shared normal distribution with a known mean, standard deviation, and percentiles
• The Z Score is the number of standard deviations a particular score is from the mean
• The only thing we need to convert any raw score to a z score is the mean and standard deviation
• Z Distribution or Standard Normal Distribution is a normal distribution of z scores
• Z Distributions allows us to:

  1. Transform raw scores into standardized scores called z scores
  2. Transform z scores back into raw scores
  3. Compare z scores to each other even when the underlying raw scores are measured in different scales
  4. Transform z scores into percentiles that are more easily understood
• Z Scores are useful because:

  1. Z Scores give us a sense of where a score falls in relation to the mean of its population (in terms of standard deviation of its population)
  2. Z Scores allow us to compare scores from different distributions
  3. Z Scores can be transformed into percentiles
• Central Limit Theorem: refers to how a distribution of a sample means ins more normal distribution than a distribution of scores, even when the population distribution is abnormal
• 2 Important Principles of Central Limit Theorem:

  1. repeated sampling approximates a normal curve, even when the original popular is not normally distributed
  2. a distribution of means is less variable than a distribution of individual scores
• A distribution of means is a distribution composed of many means that are calculated from all possible samples of a given size, all taken from the same population
• A distribution of means reduces the influence of individual outliers
• A distribution of means has the same mean as a distribution of scores from the same population, but a smaller standard deviation
• Standard Error is the name for standard deviation of a distribution of means
• 3 Characteristics of Distribution of Means:

  1. As sample size increases, the mean of a distribution of means remains the same
  2. As sample size increases, standard error becomes smaller
  3. The shape of distribution of means approximates the normal curve if the distribution of the population of individual scores has a normal shape or if the size of each sample that makes up the distribution is at least 30