PS219 Research Methods in Psychology Lecture 2 PDF

PS219: Research Methods in Psychology Lecture 2 - The basics of research January 14th, 2025 Rory Coyne PS219 Module Coordinator [email protected] Project title: “Influences on the uptake of and engagement with digital cancer rehabilitation services” Today we...

PS219: Research Methods in Psychology Lecture 2 - The basics of research January 14th, 2025 Rory Coyne PS219 Module Coordinator [email protected] Project title: “Influences on the uptake of and engagement with digital cancer rehabilitation services” Today we 01 The Scientific method of research will cover... 02 Independent and dependent variables 03 Different types of research 04 Scales of measurement 05 Measures of dispersion 06 Measures of central tendency  Identify a research question. May begin with previous research or theory, or a researcher's own experience. Draw Conclusions. Data are analysed and published, leading to new hypotheses and the development of theories. Propose a Hypothesis. A hypothesis is one possible answer to the main research question. "The Scientific Method" Collect data. The sample should be representative of the population of interest. Choose a Research Method/Design. Research methods include questionnaires and interviews; research designs may involve one point in time or many.  Hypothesis Testing in Psychology The first step in psychological research is to define the variables that you are interested in. These variables are referred to as: The independent variable (IV) is the variable which has been identified as a possible cause of the phenomenon being researched. The variable being manipulated. Woodworth,1938 The dependent variable (DV) is expected to change in response to changes in the IV. The variable dependent on changes in the independent variable. Independent variable. (What is manipulated) Amount of water Amount of fertilizer Value of the Little water A lot of water Little fertilizer A lot of fertilizer independent variable Dependent variable Height of plant Height of plant Effect/result Short Long Short Long  Independent and dependent variables The IV is the variable that is manipulated - in a true experimental design, it is totally independent of any other variable. The DV is measured rather than manipulated, since the experimental manipulation is expected to influence how the participants in the experiment behave.  Hypothesis Testing Hypotheses are predictions made about the outcome of an investigation/experiment. Two hypotheses are always constructed: 1.The null hypothesis 2.The alternate (experimental) hypothesis The null hypothesis (H0) always makes a statement of no (null) difference between the values of a population (e.g. means), meaning: H0 = There is no difference between the means for each of the two groups sampled. Expanding on yesterday’s class: Ho = There in no difference in levels of anti-social behaviour between the couples that stay together V those that don’t in Married At First Sight Australia. The alternate hypothesis (H1)provides the alternative to the null hypothesis. It always makes exactly the opposite statement about two values of a population (e.g. mean) by saying that there is a difference between them, meaning: H1 = There is a difference between the means for each of the two groups sampled. Expanding on yesterday’s class: H1 = There is a difference in levels of anti-social behaviour between the couples that stay together V those that don’t in Married At First Sight Australia.  Hypothesis Testing 1. If, and only if, the evidence is sufficiently strong, the alternate hypothesis may be supported, and the null hypothesis rejected. 2. In all other cases (i.e., when the evidence is not sufficiently strong), the alternate hypothesis is not supported, and you ‘fail to reject’ the null hypothesis. It is really important to use this terminology when discussing research in psychology!  Remember... some things are impossible to study scientifically...  There are two main approaches to research design: Quantitative research methods: Used to gather numerical data, or at least categories Qualitative research methods: used to gather non-numerical data Naturalistic Observation Looking at a behaviour as it occurs in a natural setting No attempts at intervention on the part of the researcher Used when experiments are either difficult to carry out, or not as informative  Survey Approach Can be quantitative or qualitative, but is mostly quantitative. Often used when we want to gather data from a large number of people in a relatively short span of time. Very flexible - can be used to collect lots of different kind of information.  Descriptive Designs Naturalistic observation, surveys, and case studies (used to record the behaviour of a person, group or situation) are all examples of descriptive research designs. Here, the aim is to observe and describe - the ‘what’ rather than ‘why’…  Cross-sectional versus longitudinal studies Cross-sectional study. Basically, a number of different variables are measured more or less simultaneously for a sample of individuals. Generally, the strategy is to examine the extent to which these variables are associated with one another.  Cross-sectional versus longitudinal studies Longitudinal Study. Research in which variable(s) are measured at two or more points in time. The distinction between IVs and DVs can get confusing when discussing non-experimental designs. Example: If we were comparing young people and older adults in terms of their computer literacy, then age group would be the independent variable. Computer literacy is the dependent variable. Why? We want to see if computer literacy changes depending on which age group the participant belongs to. Of course, age cannot be manipulated by the researcher - it is a fixed characteristic of the participant. Experimental Approach Tightly controlled by researcher Less likely to have other variables at play True Experimental Design – random assignment, control group Double blind experiment - both participant and researcher are blind to the condition the participant is assigned to.  True experiments versus quasi experiments A distinction can be drawn between ‘true’ & ‘quasi’ experiments A true experiment is one which is capable of identifying a causal relationship between an independent and dependent variable To qualify as a true experiment the following are required: 1.Random assignment to conditions 2. Equal treatment of subjects 3. Presence of a control condition  Experimental and control conditions Experimental Condition: The ‘intervention’ condition which represents changes to the values of the independent variable away from the set level of the control condition in order to see whether any changes occur in the dependent variable. Control Condition: The ‘nil intervention’ and occurs when the value of the independent variable is such that the research participants have received no treatment at all.  Quasi Experiments A quasi experiment will not permit a causal relationship to be established. They enable data to be collected which could not be acquired by means of a true experiment. A quasi experimental design is used where the independent variable cannot be manipulated by the researcher for ethical reasons, e.g., self esteem. In this case, data could be collected on self-esteem and people assigned to groups as a result.  Which Method To Choose? What design you choose depends on different factors: 1. What information do you want? - The aims of the study 2. The nature of the phenomenon - Is it feasible to collect the data, and if so, would it be valid/reliable? 3. Is it ethical to conduct the study? 4. The cost of the design 5. Is there little or much current scientific theory and literature on the topic? Scaling (N.O.I.R.) Four types of data measurement: Nominal – favourite food/gender/type of pet Data can only be classified Ordinal – placement in a race Can be ranked in some kind of way Degrees of difference between ranks ignored Interval – temperature Meaningful differences between values No true zero Ratio – weight/age Meaningful zero, ratio between values  Some terms to know: Raw Data. Consists of the measurements of a variable as collected directly from source during an investigation and before any statistical processing takes place. Statistics. Are values computed from a sample (e.g. mean, median, mode, SD, etc.).  Measures of Central Tendency The Mean. The arithmetic average of a set of data, represented in statistical notation by the symbol X. The Median. The positional average of a set of scores which represents their central tendency in a very literal way (i.e. the midpoint when the scores are placed in ascending order). The mode. The value that occurs most often in a set of data.  Distributions of Data A distribution is the name given to any collection of data once the values have been organised in a way which enables the ‘shape’ of the data to be seen. Cumulative frequency allow us to ascertain where a particular value lies in relation to the sample as a whole. A frequency distribution is obtained by counting the number of times each of the possible values occurs in the set of score (represented on a graph or chart). Negative skew: More values on the right-hand side. Normal distribution: Perfect bell-shaped curve. Positive skew: More values on the left-hand side. Real-life data often does not follow a normal distribution!  Examples Positive skew Negative skew  Measures of spread Range. The difference between the largest and smallest score of a variable. Variance. Measures how far the data is spread out from the mean. If the variance is small, the data is concentrated around the mean. Standard deviation. Conceptually, the average amount by which scores differ from the mean. Standard deviation is the square root of variance. Standard deviation is expressed in the same units as the original values, whereas the variance is expressed in squared units. Guess the variable quiz  If I add more milk, the tea will get a lighter color. The two variables: 1. Amount of milk 2. Color of the tea Which one is the independent variable?  If I add more milk, the tea will get a lighter color. The two variables: 1. Amount of milk 2. Color of the tea Which one is the independent variable?  Mosquito repellent is sprayed on one arm and the other arm is not sprayed. The number of mosquito bites is counted after 2 hours. The two variables: 1. Mosquito bites. 2. Repellent sprayed. Which one is the independent variable?  Mosquito repellent is sprayed on one arm and the other arm is not sprayed. The number of mosquito bites is counted after 2 hours. The two variables: 1. Mosquito bites. 2. Repellant sprayed. Which one is the independent variable? Javier sleeps 9 hours the night before his science exam. His twin sister has the same exam and sleeps 6 hours the night before the test. Afterwards, they compare their scores. The two variables: 1. Hours slept. 2. Exam scores. What is the dependent variable? Javier sleeps 9 hours the night before his science exam. His twin sister has the same exam and sleeps 6 hours the night before the test. Afterwards, they compare their scores. The two variables: 1. Hours slept. 2. Exam scores. What is the dependent variable? New houses are spayed on the outside with an insulating paint. After a year, researchers determine how much energy each house used. What is the dependent variable? New houses are spayed on the outside with an insulating paint. After a year, researchers determine how much energy each house used. What is the dependent variable?  Recommended Reading Chapter 1 - 'The Role of Research in Chapter 2 - 'Some basics' Psychology' Chapter 4- 'Describing Variables Chapter 2 - 'Aims and Hypotheses in Research' Numerically' Chapter 3 - 'Variables, Concepts and Measures'  Thank you! For questions, email me at [email protected]