I need help with ANOVA
Running Head: ANALYSIS OF VARIANCE 1
ANALYSIS OF VARIANCE 4
RUNNING Header: ANALYSIS OF VARIANCE 3
Analysis of Variance
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Analysis of variance (ANOVA) is one of the most used statistical techniques in educational and psychological research. (Kim, 2017). By doing the research, the research is trying to show that if a sample of a population is taking an experiment is done on it; the result is similar to the rest of the group. The research is also trying to provide to show that the effect of factor leads to the other. For example, use pesticides on the crop will affect them on their growth. The research tries to measure the isolation between the different group that is cities, small town, and suburbs
The hypothesis is the expectation that research creates in mind before he/she goes to the field to correct data. Hypothesis may be alternative or null. While coming with a hypothesis one is supposed to brainstorm to come up with the correct picture or the issues that one is likely to face. From the test, the researcher tries to come up with a hypothesis about the effect of children when they watch television and their behavior afterward. (Judd, & McClelland, & Ryan, 2017)The research also tries to look at how children will behavior after observing adults and whether they will emulate them. The hypothesis is directional. This is due to children emulate what they see an adult doing. Therefore, their behavior character will determine how the adult behaves and carry themselves. Beside children learn by observing. Those children will likely behavior on how they watch on the television.
The independent variable is whether the children watch the television. The dependent variable is how the children behave after watching the video. That is the behavior change in children. The type of ANOVA used is a one-way analysis of variance. The sample size is 3.5 in a small town, 6.7 in suburbs and 7.250 in cities. There groups that are small-town, suburbs and towns.
While using the ANOVA test some assumptions are applied such that each group sample is usually drawn from a normal distribution population and the population must have a common variance. Also, the sample being used must be drawn independently from each other. However, each sample is observed independently of each other. (Henson, 2015). ANOVA has some limitations. The test assumes that the sample has the same characteristic and a similar standard deviation. If two sample is taken from the same group and yet they have a very large standard deviation difference, then the test is concluded as incorrect. (Blanca, & Alarcón, & Arnau, & Bono, & Bendayan, 2017)
The result indicates that respondents from small-town express a low level of social isolation as compared to those in cities and suburbs. Result also shows that suburban and city groups indicate that social isolation scores are higher in the city than in the suburbs, but the difference is not large enough to be statistically significant.
Reference
Blanca, M., Alarcón, R., Arnau, J., Bono, R., & Bendayan, R. (2017). Non-normal data: Is ANOVA still a valid option?. Psicothema, 29(4), 552-557.
Henson, R. N. (2015). Analysis of variance (ANOVA). Brain Mapping: an encyclopedic reference. Elsevier, 477-481.
Judd, C. M., McClelland, G. H., & Ryan, C. S. (2017). Data analysis: A model comparison approach to regression, ANOVA, and beyond. Routledge.
Weerahandi, S., & Krishnamoorthy, K. (2019). A note reconciling ANOVA tests under unequal error variances. Communications in Statistics-Theory and Methods, 48(3), 689-693.