QM LESSON 1

• Quantitative research

  • an inquiry into an identified problem, based on testing a theory,measured with numbers.
• Three general types of quantitative methods

  • Experiments
  • Quasi-Experiments
  • Surveys
• Experiments

  • true experiments are characterized by random assignment.
• Quasi-Experiments

  • all the features of experimental designs except that they involve non-randomized assignment.
• Surveys

  • cross-sectional and longitudinal studies.
• Comparison of quantitative and qualitative research approaches6 Different Aspects:

  • Objective
  • Data Description
  • Sample
  • Data Gathering
  • Data Analysis
  • Outcome
• VARIABLES

  • research simply refers to a person, place, thing, or phenomenon
• 6 Types of variables

  • Independence
  • Dependence
  • Control
  • Moderator
  • Extraneous
  • Correlation
• Attributes

  • demographic information such as age, gender, education level, income,and ethnicity
• Quantitative

  • data is numeric
• Qualitative

  • data is based on human judgement.
• Units

  • ways that variables are classified.
• Independent Variables

  • antecedent conditions that are presumed to affect a dependentvariable.
• Dependent Variable

  • the outcome.- presumably affected by one or more independent variables that areeither manipulated by the researcher or observed.
• Control

  • experiment there may be many additional variables beyond themanipulated independent variable.
• Moderator

  • measured,manipulated, or selected by the experimenter to discover
• Extraneous

  • Those factors which cannot be controlled.
• Correlation

  • can be positive (increasing X increases Y), negative (increasing Xdecreases Y).
• Population

  • complete group with at least one characteristic in common.
• Sample

  • contains a few members of the population.
• Sampling Methods

  • access to the entire population is near on impossible, however, theresults from a survey.
• Two types of sampling

  • Probability Sampling
  • Non-Probability Sampling
• Probability Sampling

  • every member of the population has the chance of being selected.
• 4 TYPES OF PROBABILITY SAMPLING

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

  • researcher randomly selects a subset of participants from a population.
• Systematic Sampling

  • researchers select members of the population at a regular interval.
• Stratified Random Sampling

  • process of creating subgroups in a dataset according to various factors,such as age, gender.
• Cluster Sampling

  • researchers divide a population into smaller groups known as clusters.
• Non Probability Sampling

  • not every member of the population has equal chance of beingselected.
• 4 TYPES OF NON PROBABILITY SAMPLING

  • Convenience Sampling
  • Purposive Sampling
  • Quota Sampling
  • Snowball Sampling
• Convenience Sampling

  • selecting a sample based on the availability of the member and /orproximity to the researcher.
• Purposive Sampling

  • samples are chosen based n the goals of the study.
• Quota Sampling

  • The proportion of the groups in the population were considered in thenumber and selection of the respondents.
• Snowball Sampling

  • participants in the study were tasked to recruit other members for thestudy.
• Sample size

  • must be large enough
• Larger sample

  • more accurate results