# Pgs. 25 - 29.  GOAL: establish cause and effect relationship between two variables  Experiment:  Quantitative research (generates numerical data) 

## Presentation on theme: "Pgs. 25 - 29.  GOAL: establish cause and effect relationship between two variables  Experiment:  Quantitative research (generates numerical data) "— Presentation transcript:

Pgs. 25 - 29

 GOAL: establish cause and effect relationship between two variables  Experiment:  Quantitative research (generates numerical data)  Variables  Independent Variable (IV): variable being manipulated or changed in the study  Dependent variable (DV): the variable that is being measured Variables must be Operationalized, i.e. they must be measurable.

 Operationalize your variables by considering each of the following descriptions and deciding whether it is an example of aggression or not.  Two men fight over a parking space  A football player kicks the ball into a goal  Two girls give a boy the “silent treatment” on the playground  A man kicks the back of the car when it will not start  Three students have a heated debate about whether global warming is happening.  Know write a well worded definition of aggression.

 The Experimental Hypothesis predicts the relationships between the IV and the DV  Null Hypothesis: predicts that there will be no results or that the results will be due to chance.  The Control Group has no experimental actions applied to it.  WE CAN NEVER PROVE ANYTHING…..WE CAN ONLY DISPROVE.  Accept the null hypothesis  Refute the null hypothesis  Except experimental hypothesis if demonstrate effect due to IV manipulation.

 Identify the IV and DV in each of the experimental hypotheses: 1. People are more likely to make a risky decision when they are in a group than when they are alone. 2. An increase in carbohydrates decreases ones ability to concentrate. 3. People will react more quickly to an auditory stimulus than a visual stimulus. 4. Lack of sleep will affect learning new word negatively. 5. Children who have watched a film with a model hitting a blow-up doll will exhibit more aggressive acts toward a blow-up doll than children who have not watched the film.

 Laboratory experiments  Field experiments  Natural experiments

 Pros:  Easy to control  Easy to replicate  Cons  Artificial environment  What is the ecological value?  Would your result stand up outside of a lab setting?

 Pros  Used in Social Psychology  Takes place in natural environments, but IV is still manipulated.  e.g. Piliavin and Rodin (1969) helping behavior in a New York Subway. Piliavin and Rodin  Kitty Genevese 1964 Kitty Genevese  The bystander effectbystander effect  Cons  Cannot control all variables

 Natural experiment or quasi – the researchers have no control over the variables  Research on stoke patients  Cannot change gender  Children who have been separated from their parents due to war

 Confounding Variables: undesirable variables that influence the relationship between the IV and DV.  Artificiality – the situation is so unlikely that one has to wonder if there is any validity to the study

 Three of the most common confounding variables:  Demand characteristics or Hawthorn Effect – participants behave in a manner that they think they should to meet the demands of the study. To overcome – Single Blind control – participants do not know what the study is about.  Researcher Bias or observer bias- the researchers sees what he wants to see. To overcome – Double Blind control – the participants & researcher do not know who is in the control group vs. experimental group  Participant Variability – sample represents same characteristics Overcome – random sampling

 Not all experiments can be carried out, however, data can reveal relationships between two variables = Correlations  Correlation – as one variable changes the other variable changes. This does not mean there is a cause and effect.  Positive correlation: as X increases Y increases  Negative correlation: as X increases, Y decreases  Note – no IV is manipulated, thus there is not cause and effect.

1. They are simple and provide a numerical representations of the relationship that can be easily understood 2. They allow the study of a number of variables that cannot be manipulated experimentally.

Download ppt "Pgs. 25 - 29.  GOAL: establish cause and effect relationship between two variables  Experiment:  Quantitative research (generates numerical data) "

Similar presentations