Research Methods Steps in Psychological Research Experimental Design

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Presentation transcript:

Research Methods Steps in Psychological Research Experimental Design Variables – IV and DV Operational Hypothesis Extraneous Variables Participants

Study Design Dot Points - experimental research: construction of research hypotheses; identification of operational independent and dependent variables; identification of extraneous and potential confounding variables including individual participant differences, order effects, experimenter effect, placebo effects; ways of minimising confounding and extraneous variables including type of experiment, counterbalancing, single and double blind procedures, placebos; evaluation of different types of experimental research designs including independent-groups, matched-participants, repeated-measures; reporting conventions

Steps in Psychological Research Scientific research involves using a research method to collect information relating to a particular research area, then organising the results and reaching conclusions from that data This is often planned and conducted in a particular way known as the scientific method If the scientific method is not followed then it is difficult to reach valid conclusions regarding your research

1. Identify the research problem The first step is to identify an area of interest or a topic to be researched A literature search will aid the researcher in determining what prior research has been conducted and what areas of the topic might need further research This will allow the researcher to propose a research question which can be investigated and researched

2. Formulate a hypothesis A hypothesis is a testable prediction of the relationship between two or more variables It is usually based in prior knowledge of the area or topic to be researched and is formulated prior to the conduction of the research

3. Design the method The method needs to be designed based around the hypothesis and what you determine as being the best way to test it The research method will depend upon the topic and the hypothesis It must be decided what participants will be studies, how many, and how they will be allocated to the study The method to collect data also needs to be determined Ethical considerations also need to be taken into account here

4. Collect the data This step involves collecting the data which will be used to test the hypothesis Psychology uses many different data collection methods such as questionnaires, observations, interviews, and physiological recordings to obtain data Once again the method of data collection will depend upon the study

5. Analysing the data The data then needs to be collated and organised into a meaningful display This may involve collating large amounts of data and summarising into tables, graphs etc in order to better determine if the hypothesis is supported or rejected based upon the results

6. Interpret the data The data then needs to be interpreted and explained so conclusions can be formed A conclusion is a judgement about what the results of an investigation mean Statistical tests can be used to help determine the significance of the results and whether the hypothesis is supported or rejected based upon the research

7. Report the findings The final step is to report the findings to others who may be interested in the research A strict format is followed to report the findings of psychological research This step is important as it allows others to examine the validity of your research and allow them to replicate the study if needed

The first thing I would like you to do now is to create a flow-chart demonstrating how psychological research is conducted Make sure you include some important points about each step and why they are important

Experimental Design An experiment is used to test a cause-effect relationship between two or more variables Research can be conducted to determine if one variable (a possible cause) has an effect on another variable Write down two examples of where you think there could be a cause-effect relationship between two variables

Variables A variable is any factor which can change or vary over time Below write down 5 examples of a variable – it can be anything which varies over time

Independent Variable The independent variable (IV) is the variable in the research which is manipulated or changed by the researcher to measure its affects on the participants responses or results It is called the independent variable because the researcher can independently vary it is some way during the research

Dependent Variable The dependent variable (DV) shows any effects of the IV and is expected to change as a result of manipulation of the IV It is called the dependent variable because whether or not it will change and the way in which it changes is dependent on the IV In the cause-effect relationship, the IV is the possible cause, while changes in the DV are the possible effects

Recognising the IV and the DV It is important that you are able to recognise the IV and the DV in particular scenarios Using the following research question, determine the IV and the DV… Does smoking marijuana affect driving performance?

Recognising the IV and the DV In this particular scenario the IV is whether or not the participant has smoked marijuana while the DV is the participants driving performance Driving performance is dependent on whether or not the individual has smoked marijuana or not

Recognising the IV and DV It is important you are able to recognise what variable constitutes the IV and the DV in a research question It is handy to have a memory device to enable you to remember how to recognise the IV and DV

What you wear depends on the weather What you wear (the DV) is dependent on the weather (the IV)

Worksheet Complete the worksheet Independent and Dependent Variables For each of the research questions, see if you can determine the IV and the DV

IV and DV Simple experiments use one IV with two values or levels (usually referred to as an experimental condition and a control condition) In the experimental condition the IV is present or and tested while in the control condition the IV is removed The control provides a comparison for the experimental condition where the IV was present Without a control it would not be possible to determine if the IV has caused a change in the DV

Operational Hypothesis As we have previously seen, a hypothesis is a testable prediction between two or more variables For our research question example… It is predicted that smoking marijuana will affect driving performance

Operational Hypothesis But how do we know the levels or values which will be used in our variables? The previous research hypothesis doesn’t tell us who will be studied or what values the variables will be

Operational Hypothesis Looking at our research hypothesis again – It is predicted that smoking marijuana will affect driving performance How do we know how much marijuana is smoked, and when? How will we determine what driving performance will be measured? Who are we measuring? An operational hypothesis expresses the research hypothesis in terms of how the experimenter will determine the presence and levels of the variables under investigation – how the experimenter is going to put the hypothesis into operation and who it will be studying

Operational Hypothesis We therefore need to operationalise our variables – that is show how they will be in operation, as well as showing what the population is which will be studied Variables which need to be operationalised IV – Whether or not marijuana is smoked DV – Driving performance We also need to determine what population we will be studying

Operational Hypothesis An example of how we could operationalise our variables… IV – Smoking marijuana: Smoking one joint containing 500mg of pure marijuana (not mixed with tobacco) 20 minutes before taking a driving test DV – Driving performance: % score on the Vic Roads “Are you ready?” driving simulator And the population… Males aged 18-25years of age

Operational Hypothesis Now we can formulate our operational hypothesis… It is predicted that males aged 18-25 years of age who have smoked marijuana (smoking one joint containing 500mg of pure marijuana 20 minutes before taking a driving test) will perform worse on a driving test (obtain a lower % score on the Vic Roads “Are you Road Ready?” driving simulator) compared to participants who have not smoked marijuana.

Worksheet The best way to learn how to create an operational hypothesis is to do it yourself Complete the worksheet “Writing an operational hypothesis”

How can you remember what you need to include in an operational hypothesis? A good way to remember what you need to include is to use the acronym… I - P - O - D -

Extraneous Variables Extraneous variables are any variable other than the independent variable that can cause a change in the DV affect the results of the research in an unwanted way Think back to the previous research scenario regarding smoking marijuana affecting driving performance, what could some possible extraneous variables be in this research question?

Extraneous Variables It is important that the influence of any extraneous variables are minimised or eliminated If an extraneous variable is not controlled for it can cause confusion in the results and the researcher cannot be sure if any change in the DV has come about as a result of the IV When an extraneous variable is uncontrolled and causes confusion in the results it is referred to as a confounding variable

Extraneous Variables For our research question (does smoking marijuana affect driving performance?) what are some possible extraneous variables which could cause a change in the DV?

Methods to Control Extraneous Variables Participant selection Experimental design Placebo effects (single-blind) Experimenter effects (double-blind)

Participant Selection When we conduct research we may want to draw conclusions which are relevant to a particular group or groups of people This group is referred to as the population It is very rare for research to be conducted on every member of a population therefore we use a representation of that population known as the sample

Participant Selection It is important that the sample is an accurate representation of the population To achieve this accurate representation researchers use random sampling and stratified random sampling Random sampling is a procedure in which every member of the population has an equal chance of being selected Stratified random sampling involves dividing the population in sub- groups based on the value of a certain variable which may be confounding, the sample is then taken randomly from each group so as to create a sample with an equal proportion as each group exists in the population This could be any personal variable such as age, gender, weight etc

Participant Selection For example if the population of people who did yoga in FTG was 5000 people, then it is very unlikely that there would be 50-50 male to female In fact (to use a generalisation) there is probably a great deal more females which means if we took a random sample it is unlikely to be a complete representation of the population We can stratify the population so as to include equal proportions of the gender as they appear in the population Stratified random sampling is very time consuming as you need to identify the relevant factors which need to be stratified and the proportions in the population calculated