A. Multiple Baseline B. Small n C. AB D. Control E. Experimental F. ABA G. Between Subject H. Quasi-Experimental I. Changing Criterion J. Within Subject Matching Read the following scenarios and match each scenario with the correct type of experimental design.
Procedure Include a step-by-step procedure for what you did in the lab, written in your own words. Data and Observations Include an organized and labeled data table that lists all measurements taken during the lab. Be sure that all measurements have the correct number of sig-figs and the correct units. Also include any observations (not measured) that you made during the course of the investigation. Calculations Write out all steps of the calculations that you conducted in order to solve for the formula of the hydrate.
Although this research has helped many psychologists (Erickson et al, Everett waters) with their experiments this one may not be very valid, because the results may not apply to infants with different cultures and beliefs, therefore we cannot generalize the results as it was only tested on middle-class US children. Another fault in the experiment was that it didn’t take into account the extraneous variables which may have
5. Which group's test scores had the least amount of variability or dispersion? Provide a rationale for your answer. Ans: The control group had the least amount of variability (SD 10.34) because the control group was not provided the same resources that the experimental group was provided. 6.
According to both rules, the sample size is small. (d) Why might collinearity account for the lack of significance of some predictors? Collinearity refers to a strong correlation between two variables. This strong correlation makes it difficult or impossible to estimate their individual regression coefficients reliably (Statistics.com, 2010). In this case rebounds and points are highly
This is when the experimenting or observing is done, all the raw data is recorded and compiled to be analyzed c. Analyzing and Interpreting Data: Once the questions are created, the planning and carrying out of the investigation has happened, the data is analyzed and interpreted. This is when all the raw data is manipulated mathematically, categorically, graphically, or other ways to be able to make sense of the scientific inquiry. This is when the original questions are answered either that they were correct or incorrect. What went wrong and explaining what the results of the data mean. 2.
Experimental is when the research attempts to control and manipulate the variables in the study and ex post facto research designs are investigators in which they have no control over the variables in the sense of being able to manipulate them. (Pg. 141) C. Descriptive research is concern with finding out, who, what, where, when, or how much and causal studies seek to discover the effect that a variables has on another or others or why certain out comes are obtained. (Pg. 141) 2) A.
CONFOUND: A confound means that there is an alternative explanation beyond the experimental variables for any observed differences in the dependent variable EXTRANEOUS VARIABLES: Variables that naturally exist in the environment that may have some systematic effect on the dependent variable DEMAND CHARACTERISTIC: Experimental design element or procedure that unintentionally provides subjects with hints about the research hypothesis DEMAND EFFECT: Occurs when demand characteristics actually affect the dependent variables HAWTHORNE EFFECT: People will perform differently from normal when they know they are experimental subjects PLACEBO: A false experimental condition aimed at creating the impression of an effect PLACEBO EFFECT: The effect in a dependent variable associated with the psychological impact that goes along with knowledge of some treatment being administered CONSTANCY OF CODITIONS: Means that subjects in all experimental groups are exposed to identical conditions except for the differing experimental treatments COUNTERBALANCING: Attempts to eliminate the confounding effects of order of presentation by requiring that one-fourth of the subjects be exposed to treatment A first, one-fourth to treatment B first, one-fourth to treatment C first, and finally one-fourth to treatment D
Furthermore, empirical results are often unclear or confusing. For instance, one statistical test might indicate one thing while another the opposite. Likewise, an explanatory variable that is significant in one regression might be insignificant in another regression. There is nothing you can do