Presentation on theme: "Chapter 2 – Experimental Design and Data Collection Math 22 Introductory Statistics."— Presentation transcript:
Chapter 2 – Experimental Design and Data Collection Math 22 Introductory Statistics
Error Due to Bias and Chance Bias - A systematic tendency to misrepresent the population. The object of any experimental design is to eliminate bias and reduce chance error as much as possible.
Types of Design Confounding factor (lurking variable) – a hidden factor that has an effect on the response we are attempting to measure. Experimental (treatment) Group – those persons or objects that receive the treatment of interest in an experimental design. Control Group – those persons or objects that do not receive the treatment of interest. Rather, they may receive the “old” treatment or a placebo.
Statistical Designs Experiments - Attempts to determine a cause and effect relationship between two or more variables. Blind Experiment – the test subjects do not know if they are getting the experimental treatment or the placebo. Double Blind Experiment – neither the test subject nor the experimenter measuring the response knows to which group the test subjects have been assigned (treatment or placebo).
Statistical Designs Prospective Study – Study of future events. Randomization – An excellent way to reduce bias. Retrospective Study - Study of past events. Cross Sectional Study – Study of events at the current time (one point in time). Data represents what is going on at a certain cross section of time.
Collecting Data To obtain reliable information that will help answer your research questions, follow these steps: Determine the objectives of the study you are undertaking. Define the population of interest. Choose the variables that you will measure in the study.
Collecting Data Decide on an appropriate design for producing data. Collect the data. Determine the appropriate descriptive and/or inferential data analysis techniques.
Types of Random Sampling Simple Random Sample - To select the sample in such a way that every sample of that size has the same chance of being chosen. Systematic Random Sample Stratified Random Sample
Surveys A properly designed survey reports the following information: A description of the sampled population A description of the method of contact for interviews The response rate The exact wording of the questions
Surveys The timing of the interview. The size of the sample (or the margin of error) The sampling technique