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### Math_145_design_terms_handout2

Course: MATH 145, Fall 2009
School: Wisc La Crosse
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Word Count: 586

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of Review Methods Acquiring Data: 1. Census obtaining information from each individual in the population. 2. Sampling obtaining information from a part of the population (sample) in order to gain information about the whole population. Observational Study observes individuals and measures variables of interest but does not attempt to influence the responses. Experiments deliberately imposes some treatment...

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of Review Methods Acquiring Data: 1. Census obtaining information from each individual in the population. 2. Sampling obtaining information from a part of the population (sample) in order to gain information about the whole population. Observational Study observes individuals and measures variables of interest but does not attempt to influence the responses. Experiments deliberately imposes some treatment on individuals in order to observe their responses. Examples of Designed Experiment Example 1 : Consider the problem of comparing the effectiveness of 3 kinds of diets (A, B, C). Forty males and 80 females were included in the study and were randomly divided into 3 groups of 40 people each. Then a different diet is assigned to each group. The body weights of these 120 people were measured before and after the study period of 8 weeks and the differences were computed. Example 2 : In a classic study, described by F. Yates in the The Design and Analysis of Factorial Experiments, the effect on oat yield was compared for three different varieties of oats (A, B, C) and four different concentrations of manure (0, 0.2, 0.4, and 0.6 cwt per acre). Terminologies in Experiments Experimental Units These are the individuals on which the experiment is done. Subjects human beings. Response variables Measurement of interest. Factors Things that might affect the response variable (explanatory variables). {new drug} Levels of a factor {different concentration of the new drug; no drug, 10 mg, 25 mg, etc.} Treatment A combination of levels of factors. Repetition putting more than one experimental units in a treatment. Example 1 : Diet Study Example 1 : Consider the problem of comparing the effectiveness of 3 kinds of diets (A, B, C). Forty males and 80 females were included in the study and were randomly divided into 3 groups of 40 people each. Then a different diet is assigned to each group. body The weights of these 120 people were measured before and after the study period of 8 weeks and the differences were computed. a) Experimental units : People b) Response variable : Weight lost c) Factor(s) : Diet d) Levels : diet A, diet B, diet C e) Treatments : diet A, diet B, diet C Example 2 : Oat Yield Study Example 2 : In a classic study, described by F. Yates in the The Design and Analysis of Factorial Experiments, the effect on oat yield was compared for three different varieties of oats (A, B, C) and four different concentrations of manure (0, 0.2, 0.4, and 0.6 cwt per acre). a) Experimental units : Fields b) Response variable : Oat yield c) Factor(s) : Oat variety, Manure concentration d) Levels : Oat A, B, C ; Concentration 0, .2, .4, .6 e) Treatments : (A, 0), (A, .2), ..., (C, .6) Designs of Experiments Completely Randomized Experimental units are allocated at random among all treatments, or independent random samples are selected for each treatment. Double-Blind Study Neither the subjects nor the medical personnel know which treatment is being giving to the subject. Matched Pair Used for studies with 2 ...

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