Question1 ( 2Points ) In causal models you attempt to identify other variables which cause the fluctuation in the variable of interest. examine the relationship between these other variables and the variable of interest. express the relationship in a mathematical form, which can be used for prediction. All of the above. Causal models can be subdivided into (9 correlation and regression analysis. quantitative and qualitative analysis. simple and multiple regression analysis. None of the above. Question3 l 2Points ) When you look at the relationship between two variables to determine whether there is any relationship between them, and how strong that relationship is, you are performing random sampling qualitative analysis regression analysis correlation analysis When drawing a graph, which variable goes on the y-axis? It depends on the purpose of the researcher. It does not matter which variable is chosen for the yaxis. The independent variable. The dependent variable. The following type of relationships can be analyzed by regression analysis. Exponential curves Parabolic equations (9 Linear relationships Non-linear relationships If the points on a scatter diagram of data are very close together, and seem to follow a line, there is a correlation. negative If the correlation coefficient is calculated to be 0.15, it shows that: ([9 15% in the variation of the analysis have not been explained. 15% in the variation of the analysis have been explained. (9 there is practically no correlation between the variables. there is a positive correlation between the variables. Simple random sampling is best used when there is: ([9 an easily accessible sampling frame that lists the entire population. access to random numbers which can then be used to codify the population. (9 an indication on what the sample size is. (D) positive correlation between the variables of interest in the sample