Alternative to Experimentation Correlational Research

• A between-subjects design in which participants have not been randomly assigned to conditions.

  Non- Equivalent Group Design
• Linear Regression Analysis - uses regression equation to predict scores on the variable from scores on a second correlated variable.
• Once the correlation is known, it can be used to make predictions.

  Correlational Research
• Scatterplots are often the researcher's first step toward analyzing correlational data.
• Correlational research is non-experimental. It means there is no need to manipulate any of the variables through a scientific methodology.

  Non-experimental
• Used to establish relationships among pre-existing behaviors and can be used to predict one set of behaviors from others.

  Correlational Designs
• The relationship between pairs of scores from each subject.

  Simple Correlation
• Positive correlation tells that the relationship between the variables is positive.
• It can be used to explore the effects of different treatments on pre- existing groups of subjects or to investigate the same kinds of naturally occurring events, characteristics, and behaviors that we measure in correlational studies.

  Quasi-experimental Designs
• A pre-test needs to be administered first on the participants. This is followed by the treatment. A post-test will be conducted after the treatment.


  Pre-test and Post- Test Design
• It refers to a design that track the participants for a long time.

  Longitudinal Design
• A type of research design in which you collect data from different individuals at a single point in time.

  Cross-sectional Designs
• Correlational research also uses previous data and observes the actions and events of the past. The researcher can use it to spot and measure historical patterns between the variables.

  Backward-looking
• The Pearson R or Pearson Product moment correlation coefficient (r) is the most commonly used procedure for calculating simple correlations.
• Research who want to compare people exposed to a naturally occurring event with a comparison group often use quasi-experiment called natural experiment.
• Multiple Regression or Multiple Correlation - can be used to predict the score on one behavior from scores on the others.
• Correlational Study - designed to determine the correlation, or degree of relationship, between two traits, behaviors, or events.
• It is used to assess behavioral changes that can take place over periods, months years, or decades.

  Longitudinal Designs
• Quasi-experiments and correlations have different goals: In correlational studies, we are looking for relationships or associations between variables, whereas, Quasi-experiments are comparing different groups or subjects looking for differences between them or looking for changes over time in the same groups of subjects.
• In this relation, if one variable increases, we see the other variable also increase.

  Positive correlational research
• The lines drawn on the scatterplots are called regression line or lines of best fit.
• Correlation does not imply causation.
• In correlational research, the pattern between the variables is never stable, rather it constantly changes. The variables that had a positive relationship in the past, can have a negative relationship in the coming time because of various factors.

  Dynamic
• The higher the correlation, the more accurate our prediction will be.

  Correlational Research
• It investigates changes across time by measuring behavior of the same group of subjects at different points in time.

  Longitudinal Designs
• In a correlational study, selected traits or behaviors of interest are measured first. Next, the degree of relationship, or correlation, between the numbers is determined through statistical procedures.
• Linear Regression Analysis - When two behaviors are strongly related, the researcher can estimate a score on one of the measured behaviors from a score on the another.
• In quasi experiments, we can never know for certain what causes the effects we observe.
• Indicates the negative relationship between the variables.

  Negative correlational research
• When r is computed, there could be a three general outcomes: positive relationship, negative relationship, no relationship
• It explores the effects of an events by comparing behavior before and after the event.

  Pre-test and Post- Test Design
• How strong the relationship is between two or more independent variables and one dependent variable

  Multiple Regression or Multiple Correlation
• Quasi-experiments are most likely to be conducted in field settings in which random assignment is difficult or impossible. They are often conducted to evaluate the effectiveness of a treatment perhaps a type of psychotherapy or an educational intervention.
• Used to ensure that their groups are as similar as possible.

  Non- Equivalent Group Design
• In this relation, when one variable increases, the other will decrease.

  Negative correlational research
• It investigates changes across time by comparing groups of subjects already at different stages at a single point in time.

  Cross-sectional Designs
• In some quasi-experiments, the experimenter cannot exert control over who receives which treatment because random assignment is not possible.
• Zero correlational research


  Tells that the two variables have no relationship.
• If a change occurs in one variable, it doesn’t influence the other variable.

  Zero correlational research