Elements of Variance Analysis, Evaluation of Difficulties by Questionnaire (original) (raw)

Assessing psychology students’ difficulties in elementary variance analysis

2016

In this paper we present a study directed to assess the students’ difficulties in understanding elementary variance analysis. Responses from 224 undergraduate psychology students who had previously studied this topic to a questionnaire are analysed. Contents of the questionnaire include the selection of a variance analysis model, understanding of assumptions and the associated linear model in this procedure, the computations involved in variance analysis and the interpretation of results. While the understanding of computations, the selection of the model, and the understanding of the decomposition of the variance in the linear model were easy, the students had difficulties in understanding the assumptions of variance analysis and in interpreting the results in the problem context. These results provide information in an area where little prior research is available.

Analysis of variance: Comfortless questions

2017

In this paper the simplest variant of analysis of variance is under consideration. Three examples from textbooks by Lakin (1990) and Rokitsky (1973) were re-considered. It was obtained that traditional one-way ANOVA and Kruskal – Wallis criterion can lead to unreal results about factor’s influence on value of characteristics. Alternative way to solution of the same problem is under consideration too.

Analysis of Variance: The Fundamental Concepts and Application with R

International Journal of Mathematics and Computer Research, 2021

The Analysis of Variance (ANOVA) test has long been an essential tool for researchers conducting studies on multiple experimental groups with or without one or more control groups. This article encapsulates the fundamentals of ANOVA for an intended benefit of the reader of scientific literature who does not possess expertise in statistics. The emphasis is on conceptually-based perspectives regarding the use and interpretation of ANOVA results, with minimal coverage of the mathematical foundations. Data entry, checking basic parametric assumptions of ANOVA, descriptive statistics of the data by treatment groups, fitting ANOVA model, statistical significance of the test based on p-value, and post-hoc analysis are all explored using R-software.

Naïve Statistics: Intuitive Analysis of Variance

2008

Naive Statistics: Intuitive Analysis of Variance David L. Trumpower (david.trumpower@uottawa.ca) Olga Fellus (ofell070@uottawa.ca) University of Ottawa, Faculty of Education, 145 Jean-Jacques-Lussier Street Ottawa, ON K1N 6N5 Canada example, subjects’ estimates of the mean of skewed distributions are typically biased toward the median. Similarly, Kareev, Arnon, and Horwiz-Zeliger (2002) have shown that estimates of variance tend to be low. It is well known that we are often biased toward making use of the most salient data when making judgements about averages (i.e., the availability heuristic; Kahneman & Tversky, 1973) and correlations (Chapman & Chapman, 1969). It is also well known that we tend to make use of data which confirms our preconceived hypotheses about such things as correlations between variables (i.e., confirmation bias, Wason & Johnson-Laird, 1972; for a review, see Klayman & Ha, 1987). If students do hold certain intuitive biases or misconceptions which affect stati...

TEACHING VARIANCE AND DEGREE OF FREEDOM THROUGH COMPUTER-ASSISTED INSTRUCTION

The principle objective of the current study is to teach variance and degree of freedom by means of computer-assisted instruction. Variance is regarded as one of the most important topics to learn, degree of freedom is a concept considered as one of the most difficult concepts to teach and learn. The preliminary results on 15 faculty members showed that they had limited knowledge related to these concepts. Based on this need analysis, we developed a video tutorial to teach these concepts using Flash and Camtasia Studio software. We also considered visual design and instruction principles when developing the tutorial. The tutorial is made up of three parts: population variance, degree of freedom and sample variance. The effectiveness of our tutorial was tested on these 15 faculty members. The findings revealed substantial improvement in their knowledge about these two concepts. They were very satisfied with the tutorial and gave us valuable insight into what can be done to promote the instructional value of our tutorial. We strongly believe that the video tutorial we developed has a great potential to help learners of statistics to grasp these concepts.

ANOVA/TT: Analysis of variance teaching template for lotus 1-2-3

Behavior Research Methods, Instruments, & Computers, 1988

Inferential statistics courses often require students to conduct multifactor analysis of variance (ANOVA) problems by hand and then employ a computer to check results. Many microcomputer programs perform twofactor ANOVAs (

Development of the concept of statistical variation: An exploratory study

Mathematics Education Research Journal, 2000

An appreciation of variation is central to statistical thinking, but very little research has focused directly on students' understanding of variation. In this exploratory study, four students from each of grades 4, 6, 8, and 10 were interviewed individually on aspects of variation present in three settings. The first setting was an isolated random sampling situation, whereas the other two settings were real world sampling situations. Four levels of responding were identified and described in relation to developing concepts of variation. hnplicatioris for teaching and future research on variation are considered.

Analysis of Variance Used in the Study of the Relationship Between Variables

2008

The paper “Analysis of Variance Used in the Study of the Relationship between Variables” presents an introduction in ANOVA, which has a different methodology depending on the number of factors taken into study. The paper emphasizes that ANOVA can be used in the case in which for the independent variable has used a simple group, but the dependent variable is presented under the form of variants in case of each group or when was used a combined group for both variables. The ANOVA involved also the used of Fischer -Snedecor test for testing the signification of group factors. The paper present the basic concepts and methodology of ANOVA and the unifactorial and bifactorial methodology of analysis of variance.