Psych stat

• Statistics


  1. Organize Data

  2. Describe Data

  3. Make Inferences based upon the Data
• Qualitative Research


  • Understanding human behavior from the informant's perspective
  • Data are collected through participant observation and interviews
  • Is interpretative and does naturalistic approach to its subject matter
  • Aims to understand the social reality of individuals, groups and cultures
  • Focuses on "how" and "why" a particular phenomenon happens
• Quantitative Research


  • Discovering facts about social phenomena
  • Assumes a fixed and measurable reality
  • Data are collected through numerical comparisons
  • Puts data into categories, in rank order, or measured in units of measurement
  • Aims to establish general laws of behavior and phenomenon across different setting /context
  • Research is used to test a theory and ultimately support it or reject it
• Two main methods of research

  1. Deduction - general theory to particular data

  2. Induction - particular data to a general theory
• Theory


  Explanation or set of principles that is well substantiated by repeated testing and explains a broad phenomenon
• Hypothesis


  A proposed explanation for a fairly narrow phenomenon or set of observations
• Independent Variable


  The cause of some effect, manipulated by the experimenter
• Dependent Variable


  Affected by changes in an independent variable
• Levels of Measurement

  • Nominal - words, letters, and alpha-numeric symbols
  • Ordinal - ranking
  • Interval - distances between each interval on the scale
  • Ratio - equal intervals
• Correlational Research


  Provides a very natural view of the question we're researching
• Experimental Research


  An effect should be present when the cause is present as well, and an effect should be absent when the cause is also absent
• Randomization

  1. Random Selection - any member of a population has an equal chance of being selected as a participant

  2. Random Assignment - each participant in the experiment is randomly assigned to experimental treatments
• Practice effects


  Participants perform differently in the second condition because of familiarity with the experimental situation
• Boredom effects


  Participants may perform differently in the second condition because they are tired or bored from having completed the first condition
• Analyzing Data

  • Descriptive Statistics
  • Frequency Distribution
  • Stem and Leaf Plots
  • Box and Whisker Plots
  • Scattergram
  • Normal Distribution
• Skewness


  Lack of symmetry in a normal distribution, can be positively or negatively skewed
• Kurtosis


  Pointiness of a normal distribution, can be leptokurtic (+) or platykurtic (-)
• Measures of Central Tendency

  • Mode - the score that occurs most frequently
  • Median - the middle score
  • Mean - the sum of all scores divided by the number of scores
• Measures of Dispersion


  • Quartiles - three values that split the sorted data into four equal parts
  • Lower Quartile - median of the lower half of the data
  • Upper Quartile - median of the upper half of the data
  • Interquartile - difference between the upper and lower quartile
  • Mean Absolute Deviation (MAD) - average distance between each data value and the mean
  • Variance - sum of the squared deviations from the mean, divided by the number of scores
  • Standard Deviation - square root of the variance
• Probability


  Likelihood of a particular event of interest occurring
• Conditional Probability


  The probability of a particular event happening if another event (or set of conditions) has also happened
• Population


  A complete set of measurements (or individuals or objects) having some common observable characteristic
• Sample


  A subset of a population
• Types of Sampling

  • Probability Sampling - subjects of the population get an equal opportunity to be selected as a representative sample
  • Non-probability Sampling - it is not known that which individual from the population will be selected as a sample
• Types of Non-Probability Sampling

  • Judgmental Sampling - sample members are chosen only on the basis of the researcher's knowledge and judgment
  • Convenience Sampling - subjects are selected because of their proximity to the researcher
  • Snowball Sampling - used by researchers to identify potential subjects in studies where subjects are hard to locate
  • Quota Sampling - sample group represents certain characteristics of the population chosen by the researcher
• Types of Probability Sampling

  • Simple Random Sampling - a completely random method of selecting subjects
  • Systematic Sampling - you choose every "nth" participant from a complete list
  • Stratified Random Sampling - involves splitting subjects into mutually exclusive groups
  • Cluster Sampling - a random sample of these clusters are selected
• Counterbalancing is usually thought of as a method for controlling order effects in a repeated measures design
• Ability Sampling


  It is not known which individual from the population will be selected as a sample
• Judgmental Sampling


  Sample members are chosen only on the basis of the researcher's knowledge and judgment
• Convenience Sampling


  Subjects are selected because of their proximity to the researcher
• Snowball Sampling


  Used by researchers to identify potential subjects in studies where subjects are hard to locate
• Quota Sampling


  Sample group represents certain characteristics of the population chosen by the researcher
• Types of Probability Sampling


  • Simple Random Sampling
  • Systematic Sampling
  • Stratified Random Sampling
  • Cluster Sampling
• Simple Random Sampling


  A completely random method of selecting subjects, e.g. Fish Bowl Technique
• Systematic Sampling


  You choose every "nth" participant from a complete list
• Stratified Random Sampling


  Involves splitting subjects into mutually exclusive groups; alike to quota sampling
• Cluster Sampling


  A random sample of these clusters are selected; there is no need for choosing groups because they already exist, e.g. Rainbow Village > Red Street
• Homogeneity is within groups and between them, Heterogeneity is between groups and within them
• Degrees of Freedom


  e.g. 3 combination numbers that will have a mean of 3
• Uses the Standard Deviation formula