Please respond to these discussions with reference

Discussion 1

Analysis of Variance also referred to as ANOVA very simply put is atest used to determine if survey or experiment results are significantor not. It helps you figure out whether you should reject thenull hypothesis or possibly accept an alternate hypothesis or not inan experiment. You are testing groups to find if there is anydifference between them. An example of this would be if you weretrying three different procedures to test male urinary retention oneprocedure may be catheterization, while the next may be a voidingschedule and the last may be medication. If you have run theseexperiments, then the ANOVA can help you to choose which of theseinterventions worked best for the patients.

There are also different types of the ANOVA test listed as one-wayANOVA and two-way ANOVA. The one-way ANOVA has one independentvariable. So, if we were testing catheters a one-way test would lookat type of catheter. While a two-way has two independent variables sofor example catheter testing may have the type of catheter and theFrench of the catheter. ("ANOVA Test: Definition, Types, Examples")

Another factor to consider when using ANOVA is levels. Levels aredifferent groups in the same variable. For example, if we were lookingat the type of catheter used a level may be the brand of that type ofcatheter. ("ANOVA Test: Definition, Types, Examples")

Reference

ANOVA Test: Definition, Types, Examples. (n.d.). Retrieved May 21,2018, from http://www.statisticshowto.com/probability-and-sta…

Discussion 2

ANOVA- Analysis of variance is used for testing treatments. The ANOVAis used when there are two or more treatments that have to be testedfor efficacy. To apply ANOVA, all individuals are to be affected bythe treatment similarly. The one-way ANOVA differentiates three ormore populations when there is one factor of interest (Anders, 2017).There are certain requirements that are need before the use of one-wayANOVA is appropriate. The population distribution normal, thepopulations having the same variance, simple random samples ofquantitative data, samples are independent, different and classifiedin only one way (Wall, 2017). There are limitations to using ANOVAwhich is not showing if there is a difference in the treatments. Oncean ANOVA has been calculated, analysis of variance components fromsummary data becomes possible. Simple calculations based on summarydata provide inference on significance testing. Examples are givenfrom laboratory management and method comparisons. It is emphasizedthat the usual criteria of the underlying distribution of the raw datamust be fulfilled. By using a post hoc test which is a test that showsthe difference in treatment and minimizes error and bias (Grove &Cipher, 2017). A post hoc test should only be run when you have ashown an overall statistically significant difference in group means.

References

Anders, K. (2017). Resolution of Students t-tests, ANOVA andanalysis of variance components from intermediary data. BiochemiaMedica, 27(2), 253-258. doi:10.11613/BM.2017.026

Grove, S. K., Cipher, D. J. (2017). Statistics for NursingResearch: A Workbook for Evidence-Based Practice, 2nd Edition.Retrieved from https://pageburstls.elsevier.com/#/books/978032335…

Wall Emerson, R. (2017). ANOVA and t-tests. Journal of VisualImpairment & Blindness, 111(2), 193-196.

Discussion 3

If I had to explain analysis of variance (ANOVA) to an audiencewho has never taken a statistics course, memorizing the definitionis easy, but working on some practice example problems and coming upwith examples on my own will make it easier to explain theimportance of ANOVA. After I have an overallunderstanding of ANOVA, I will attempt to teach the subject tosomeone who has taken a statistics course to determine if there isanything I am missing in the information I am providing. I would also need to consider that there may be someterminology I would need to address first before implementing it inmy teaching. For example, I would need to go overwhat the “mean” is and how to calculate a group ofnumbers or “data set” to come up with the mean. Anotherterm is variance which is important to understand because it willassist with coming up with inferences about the mean. The null hypothesis will be another term that will I willneed to spend some time explaining before moving on to ANOVA.

I would first define what Analysis of Variancemeans. It is a “statistical method totest the difference between two or more means (Lane,2016).”Analyzing the variance will helpto determine the inference about the means.Iwould engage the audience by telling me what the null hypothesiswould be for the example being used since null and alternativehypotheses were discussed prior to discussing ANOVA. The example I use will be something everyone can relate tolike measuring the stress level among several groups ofemployees. The first sample are 5 people undernormal times, another group with announced layoffs, and anothergroup during layoffs (same 5 people in each sample), this measuresthe impact of announced layoffs. It allows you tocompare samples at different points of times. (Explorable.com,2009).In my opinion, I would not expect theaudience to calculate ANOVA after one day of teaching analysis ofvariance, although I would expect the audience to understand why itis used and be able to come up with scenarios in which ANOVA can beused. After I am finished with my explanationof Analysis of Variance, I would recommend to everyone to take astatistics course.

References

Explorable.com. (2009, June 6). ANOVA. Retrieved fromExplorable.com: https://explorable.com/anova

Lanve, D. (2016). Chapter 15: Analysis of Variance. Retrievedfrom onlinestatbook: http://onlinestatbook.com/2/analysis_of_variance/i…

Discussion 4

It is always hard to explain a technical issue to somebody withoutknowledge about it. However, any fast learner can understand analysisof variance easily. Analysis of variance (ANOVA) is a technique thathelps to study the variation between two or more groups to determineif there are disparities in the mean of those individual groups. Atthe same time, it can be used to study general as opposed to specificvariation between means and in that case the samples used must betaken from a population with a normal distribution.

ANOVA tests can be either one-way or two-way. In one -way ANOVA,what is measured is the variations among different groups and thistype is the easiest type because you only use one grouping to describethe groups. This is applicable in different circumstances such as whenchecking how tutorial performance is related with a student’sfinal grade. In that case, you can compare the grades of the studentsthat learnt through type A tutorial technique against the grades forthe ones that learnt through type B tutorial technique. On the otherhand, two -way ANOVA is used when handling complex groupings. Forinstance, you can compare teaching methodologies in overseas ascompared to local institutions.

References

Statistics Solutions. (2013). ANOVA (Analysis of Variance).Retrieved from http://www.statisticssolutions.com/academic-soluti…

Discussion 5

Varianceis the measure of how far numbers in a set are far from the mean; itis common in statistics for the probability distribution. Varianceis obtained by the differences of each number in a set and the mean,squaring the difference and diving the sum of the squares by thenumber of values in the set. Practically, variance assists investorsin measuring the risk in the purchase of securities. Significantvariations show that numbers in the set are far from the mean, thesmaller the variance the closer the numbers are to the average inthe set (Weiss 6). However, the deviation is necessary forstatistics to show the relation between numbers within the group. Aprimary parameter in asset allocation, variance assists investors tocreate optimal portfolios by optimizing the return to volatilitytrade-off in investment portfolios. Standard deviation is primarilyused to express risk or volatility due to its naturalinterpretation.

DavidWeiss recognizes the importance of analysis of variance assist infinding out if the results of research are significant. Furthermore,he explains acquiring the analysis of variance skilled is easythrough a practical approach (Weiss 3). For example, throughvariance analysis investor understand the causes of variation inearnings and expenditure throughout the budget plan period. Thereexist three kinds of analysis variance, two-way, one-way, and N-wayanalyses. One-way variance analysis has one independent variable,two-way on the other hand has two undependable variables. Whenresearchers use more than two separate variables, they are said tohave used the N-way variance analysis. Extensively used inprobability theories, difference allows researchers to makegeneral conclusions from a small set of the population. It isbecause of the ability of variance to provide a general idea of thedata distribution

Reference

Weiss,David. Analysis of Variance and Functional Measurement: APractical Guide. New York : Oxford University, 2006. Print

Discussion 6

An interaction arises when one isconsidering the relationship between three or even more variables.It describes situations where the simultaneous influence of twovariables basically on a third is not additive. They are mostlyconsidered in the field of regression analyses. When there are 2or even more variables that are independent within any study,there is likelihood for concern for statisticalinteraction. The central area of target herewould be whether one independent factor results to alter or affectthe performance of other elements. This is about the considerationif an interaction exists between the two most important factors.

A good example includes relatingto a patient having type 2 of Diabetes. One of the primary factorswould be to use oral medication for the condition like Metforminversus a placebo. Another factor could be the usage of a 1500 to1800 calorie ADA diet. This means that when we are looking forinteraction, we will result to examine if the placebo ormedication factor had affected the 1500-1800 calorie ADA factor ofdiet.

Reference:

www.statisticshowto.com/interaction-effect-interac…