# Data analysis lecture 1-3 part 1

version from 2017-10-15 15:40

## Section 1

An experimental research design is a balance between what (5 points)1. Appropriate Sample and Sample Size 2. Accurate/appropriate variables to reduce error 3. Validity of the measuring instrument(s) 4. Practicality of conducting the experiment 5. Costs/Budgets
Scale variables are continuous variables
Values within a range or a variable that only take a finite number of values discrete variables
Values that the variable can take are categories or categorical categorical variables
Levels of measurement; interval This allows us to put scores in some sort of order of magnitude and we also have equal intervals between adjacent points on the scale. e.g. temperature
Levels of measurement; ratio Ratio scales have all the features of interval-level data but with the addition of having an absolute zero point, e.g. timing a Formula 1 race
Levels of measurement; nominal An example of a nominal scale is gender - (male/female). Put people into categories and the data we obtain are in the form of frequency counts (e.g. ethnicity).
Levels of measurement; ordinal Ratings scales to measure participants’ responses, e.g. measure how nervous a student is before taking an exam by using a scale
What are extraneous variables are those variables that might have an impact on the other variables that we are interested in but we may have failed to take these into account when designing our study
What are confounding variables is a specific type of extraneous variable that is related to both of the main variables that we are interested in.

## Section 2

3 types of experimental primary research designs correlational, experimental, quasi experimental.
What is a correlational research designA design where we measure the variables of interest and then see how each variable changes in relation to the changes in the other variables.those that investigate relationships (or measures of association) between variables. The sorts of statistical technique we will use for correlational design are the Pearson product moment correlation coefficient, or perhaps Spearman’s rho correlation coefficient, simple and multiple linear regression.
Problems with correlational research designCausation. Researchers are trying to discover causal relationships between variables. In a correlational designs, however, it is difficult to establish whether a change in one variable causes a change in another variable. The reason for this is that in such designs we are simply observing and recording changes in variables and trying to establish whether they co-vary in some meaningful way. One of the golden rules of correlational designs is that we cannot infer causation from correlations.
What is a experimental research designs one of the most widely used designs in science. Experimental designs are those where the experimenter manipulates one variable called the Independent Variable (IV) to see what effect this has upon another variable called the Dependent Variable (DV). In experimental designs we are usually looking for differences between conditions of the IV. Uses research hypothesis and participants and randomly allocated into conditions.
What is a research hypothesis our prediction of how specific variables might be related to one another or how groups of participants might be different from each other.
What is a quasi experimental design involve seeing if there are differences on the dependent variable (DV) between conditions of the independent variable (IV). Unlike experimental designs there is not random allocation of participants to the various conditions of the IV.
What statistical technique do you use for experimental or quasi-experimental design are the t-test (also known as the Student t-test), the Mann–Whitney U test, the Wilcoxon test and ANalysis Of VAriance (ANOVA
Structure of an experimental design obs 1 (Timing 1) - exp - obs 2(T2) at the same time as Obs 3 (T1) - No exp - Obs 4(T2). The difference between each groups pre and post test scores is then analysed to establish whether or not Exp has made a difference.