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1. An in” rel=”nofollow”>interaction occurs when considerin” rel=”nofollow”>ing the relationship among three or more variables, and describes a situation in” rel=”nofollow”>in which the simultaneous in” rel=”nofollow”>influence of two variables on a third is not additive. The simplest situation is when the effect of each in” rel=”nofollow”>independent variable is completely separate from the other in” rel=”nofollow”>independent variables. The more complicated situation is when the effect of one in” rel=”nofollow”>independent variable depends on another in” rel=”nofollow”>independent variable(s). We are familiar with examples in” rel=”nofollow”>in the area of drugs. A drug X might be desirable for treatin” rel=”nofollow”>ing a certain” rel=”nofollow”>in condition, but not if you are takin” rel=”nofollow”>ing drug Y, because if you do take drugs X and Y together there is a bad consequence from their combin” rel=”nofollow”>ination, a bad drug “in” rel=”nofollow”>interaction. The issue of statistical in” rel=”nofollow”>interaction potentially arises when there are two or more in” rel=”nofollow”>independent variables. The issue concerns how the effects of the in” rel=”nofollow”>independent variables cumulate.(Stipa), Your response

2. Sources of Variance in” rel=”nofollow”>in an Experiment
Watch “ANOVA (Part A) – Sources of Variance in” rel=”nofollow”>in an Experiment” on the YouTube website located at What are some of the sources of variance in” rel=”nofollow”>in an experiment? Your response

3. There is a lot of medical research bein” rel=”nofollow”>ing done on medications, diagnostics, medical equipment, and other technologies besides health care that must be tested before production and utilization. When testin” rel=”nofollow”>ing the difference in” rel=”nofollow”>in populations it is almost impossible to test whole populations so samples gathered. There will always be samplin” rel=”nofollow”>ing error because of this, which may brin” rel=”nofollow”>ing false results. Tests are done to identify if the subject is effective or in” rel=”nofollow”>ineffective. When there are multiple groups, samples, or items that are bein” rel=”nofollow”>ing tested, it is necessary to use a comparison formula ANOVA because of false results that can occur. This formula compares the variation between groups and within” rel=”nofollow”>in groups. It allows you to conclude if the difference between the groups is more than random variation.
I have to schedule a lot of funraisers throughout the year and sometimes it is difficult to determin” rel=”nofollow”>ine which one is effective. I break them down in” rel=”nofollow”>into catagories and time of year. The best is to have seasonal fundraisin” rel=”nofollow”>ing. Another unique part of fundraisin” rel=”nofollow”>ing is bein” rel=”nofollow”>ing aware of the population and community in” rel=”nofollow”>interests. You can have a false positive fundraisin” rel=”nofollow”>ing event on a schedule if you were not thin” rel=”nofollow”>inkin” rel=”nofollow”>ing about the time of year because if one fundraiser made a 1,000 dollars profit in” rel=”nofollow”>in the summer but did not do so well in” rel=”nofollow”>in the fall and nothin” rel=”nofollow”>ing was changed in” rel=”nofollow”>in that fundraiser, then it is important to take in” rel=”nofollow”>into consideration the time of year. In this buisness it is good to analyze results by catagories of community, time, and community in” rel=”nofollow”>interests. Each fundraiser acts like a sample test to determin” rel=”nofollow”>ine if communities are in” rel=”nofollow”>interested in” rel=”nofollow”>in it or not through the year. Your response
4I am usin” rel=”nofollow”>ing my teenager as test model because she has never had a statistics class as of yet. Explain” rel=”nofollow”>ined analysis of variance or ANOVA in” rel=”nofollow”>in terms of the big picture and the little pictures that are within” rel=”nofollow”>in: categories. She has an older ford truck she is remodelin” rel=”nofollow”>ing. She loves loves her truck, but it is expensive and thus she has a budget of expenses for it. Sin” rel=”nofollow”>ince it is already paid for, the categories are: Insurance/fees, engin” rel=”nofollow”>ine repair, body repair, fluids/replaceables and ect. When she looks at the multitude of work to be done, she gets overwhelmed! But by breakin” rel=”nofollow”>ing it in” rel=”nofollow”>into categories and then lookin” rel=”nofollow”>ing at the whole (her beloved truck) it seems much more manageable. The Min” rel=”nofollow”>initab blog said it best The whole purpose of Analysis of Variance is to break up the variation in” rel=”nofollow”>into component parts, and then look at their significance. But there’s a catch: in” rel=”nofollow”>in statistics, Variance (the square of Standard Deviation) is not an “additive” quantity—in” rel=”nofollow”>in other words, you can’t just add the variance of two subsets and use the total as the variance of the combin” rel=”nofollow”>ination” (Min” rel=”nofollow”>initab, 2013).

Analysis of variance is a way to study a large chunk of in” rel=”nofollow”>information, to see it as not only categories, but the trends and thus gives you a tool for analysis. Your response

5.When two or more in” rel=”nofollow”>independent variables are in” rel=”nofollow”>involved in” rel=”nofollow”>in a research design, there is more to consider than simply the “main” rel=”nofollow”>in effect” of each of the in” rel=”nofollow”>independent variables (also termed “factors”). That is, the effect of one in” rel=”nofollow”>independent variable on the dependent variable of in” rel=”nofollow”>interest may not be the same at all levels of the other in” rel=”nofollow”>independent variable. Another way to put this is that the effect of one in” rel=”nofollow”>independent variable may depend on the level of the other in” rel=”nofollow”>independent variable.

In order to fin” rel=”nofollow”>ind an in” rel=”nofollow”>interaction, you must have a factorial design, in” rel=”nofollow”>in which the two (or more) in” rel=”nofollow”>independent variables are “crossed” with one another so that there are observations at every combin” rel=”nofollow”>ination of levels of the two in” rel=”nofollow”>independent variables.
For example, if you were in” rel=”nofollow”>interested in” rel=”nofollow”>in the effects of practice and stress level on memory task performance, you might decide to employ a factorial design. You manipulate practice by havin” rel=”nofollow”>ing participants read a list of words either once or five times. You also manipulate stress level by havin” rel=”nofollow”>ing two conditions: in” rel=”nofollow”>in one (low stress), participants are told that the number of words that they recall is unimportant, and in” rel=”nofollow”>in the other (high stress), participants are told that most people can recall all words in” rel=”nofollow”>in the list, and that they are expected to be able to do so as well. Your dependent variable is the number of words recalled from the 30-word list.

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