Week 3 Notes - Validity - are measuring what you think you're measuring (are you measuring depression or something else?) - Reliability- are you consistent in your measurements? ( Scale not valid, but measured correctly) - DESCRIBE WITH EXAMPLES>>> - Know Cronbach's alpha symbol - IN THE FIRST ASSESSMENT - YOU WILL BE ASKED TO: - 1) Define variables and give details other individual variables of the study - you will also be asked to describe the overall design of study as well Types of Research Design · Major Distinctions in Types of Research Design Experimental . Cause and Effect · Manipulation · Control · Quasi-Experimental · Similar to experimental designs, however less randomisation of key independent variables. · Non-Experimental . Relationships but NOT Cause and Effect · Quantitative: Information gathered numerically from a large number of participants e.g. surveys · Qualitative: In-depth information gathered from small number of participants e.g. case studies Quasi - kind of experimental and kind of not experimental Non experimental is correlation focused - establish those basic relationship between both - Slide 11 - there is a going to be a whole section on external and internal validity !! SO, PRACTICE A LOT - - in the assessment, you have to argue how internally valid the study is - use words like low, moderate, high internal validity - use qualitative terms
- In this unit, most of our IV is assumed to be all categorical, not numerical - DV is going to be continuous in the assessment - The design on our assessment is going to be factorial (more than 1 IV , do some research about that) - pick between repeated measures IV or between group IV - The definition of factorial design is an experiment that has multiple factors or independent variables. It requires a minimum of two independent variables, whereas a basic experiment only requires one independent variable. A factorial design allows the researcher to examine the main effects of two or more independent variables simultaneously. It also allows the researcher to determine interactions among variables. - Factorial design has a bivariate design because there is 2 IV'S interacting with each other (2x2) - Minimum is 2 variables - more IV's added, the more abstract design and purpose of design becomes - In the factorial design, we can see the main effect of the IV's on the DV (1 and 2 IV) and then we can see the interactive effect - how both IV's impact the DV Factorial Design Notation · 2 x 2 design · number of numerals = number of IVs = 2 . each number indicates the number of levels for each IV · IV1 = 2 levels · IV2 = 2 levels · 2 x 3 design . 2 IVs · IV1 = 2 levels · IV2 = 3 levels You will practice this in the tutorials! Merge all design descriptors into a sentence
Varlation between Frequency groups Variation within groups Score - THE DIFFERENCES IN THE PEAK