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Psychological Statistics Chapter 1

Intro to Stats for the Behavioral Sciences

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Psychological Statistics Chapter 1

  1. 1. Introduction to Statistics for the Behavioral Sciences
  2. 2. Statistics  It the practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample.
  3. 3. Statistics Branches of Statistics Descriptive -organizes, summarizes, and communicates a group of numerical observations. Inferential -uses sample data to make general estimates about the larger population.
  4. 4. Statistics • Observations drawn from a population of interest. It is described by a statistic. Sample • All possible observations about which we would like to know. It is described by a parameter. Population
  5. 5. Sampling Techniques  Random Sampling – every member of a population has an equal chance of being selected.  Systematic Sampling – taking the nth element from a given list.  Stratified Sampling – division according to categories  Cluster Sampling – the population is divided into clusters where samples are extracted.
  6. 6. Sampling Techniques  Non-random Sampling –recruitment of participants occur all of a sudden as the researcher may ought them to be useful despite of being unable to generalize the results found from such sample  Convenience Sampling – direct selection of participants until the desirable amount is reached by the researcher  Quota Sampling – similar to convenience sampling, but it ensures equal representativeness.  Snowball Sampling – a sampling based on recommendations.  Purposive Sampling – a sampling based on the knowledge of a given population and the research objective.  Self-selected Sampling – a sampling based on the desire of the people to identify themselves with the population being studied.
  7. 7. Variables  It is any observation of a physical, attitudinal, or behavioral characteristic that can take on different values
  8. 8. Variables • Can take on only specific values (e.g., whole numbers); no other values can exist between these numbers. Discrete • can take on a full range of values (e.g., numbers out to several decimal places); an infinite number of potential values exists. Continuous
  9. 9. Variables and Research • at least two levels that we either manipulate or observe to determine its effects Independent Variable • The outcome variable that we hypothesize to be related to, or caused by, changes Dependent Variable • systematically varies with the independent variable so that we cannot logically determine which variable is at work Confounding Variable
  10. 10. Levels of Measurement • variable used for observations that have categories, or names, as their values Nominal • variable used for observations that have rankings (i.e., 1st, 2nd, 3rd, . . .) as their values. Ordinal • variable used for observations that have numbers as their values; the distance (or interval) between pairs of consecutive numbers is assumed to be equal. Interval • a variable that meets the criteria for an interval variable but also has a meaningful zero point. Ratio

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