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Gorard, Stephen; White, Patrick – Statistics Education Research Journal, 2017
In their response to our paper, Nicholson and Ridgway agree with the majority of what we wrote. They echo our concerns about the misuse of inferential statistics and NHST in particular. Very little of their response explicitly challenges the points we made but where it does their defence of the use of inferential techniques does not stand up to…
Descriptors: Statistical Inference, Statistics, Statistical Significance, Probability
Nicholson, James; Ridgway, Jim – Statistics Education Research Journal, 2017
White and Gorard make important and relevant criticisms of some of the methods commonly used in social science research, but go further by criticising the logical basis for inferential statistical tests. This paper comments briefly on matters we broadly agree on with them and more fully on matters where we disagree. We agree that too little…
Descriptors: Statistical Inference, Statistics, Teaching Methods, Criticism
White, Patrick; Gorard, Stephen – Statistics Education Research Journal, 2017
Recent concerns about a shortage of capacity for statistical and numerical analysis skills among social science students and researchers have prompted a range of initiatives aiming to improve teaching in this area. However, these projects have rarely re-evaluated the content of what is taught to students and have instead focussed primarily on…
Descriptors: Statistical Inference, Statistics, Teaching Methods, Social Science Research
Aaberg, Shelby; Vitosh, Jason; Smith, Wendy – Mathematics Teacher, 2016
A classic TV commercial once asked, "How many licks does it take to get to the center of a Tootsie Roll Tootsie Pop?" The narrator claims, "The world may never know" (Tootsie Roll 2012), but an Internet search returns a multitude of answers, some of which include rigorous systematic approaches by academics to address the…
Descriptors: Statistics, Hypothesis Testing, Mathematics, Mathematics Education
Vaughan, Timothy S. – Journal of Statistics Education, 2015
This paper introduces a dataset and associated analysis of the scores of National Football League (NFL) games over the 2012, 2013, and first five weeks of the 2014 season. In the face of current media attention to "lopsided" scores in Thursday night games in the early part of the 2014 season, t-test results indicate no statistically…
Descriptors: Team Sports, Success, Scores, Statistics
Niculescu, Alexandra C.; Templelaar, Dirk; Leppink, Jimmie; Dailey-Hebert, Amber; Segers, Mien; Gijselaers, Wim – Electronic Journal of Research in Educational Psychology, 2015
Introduction: This study examined the predictive value of four learning-related emotions--Enjoyment, Anxiety, Boredom and Hopelessness for achievement outcomes in the first year of study at university. Method: We used a large sample (N = 2337) of first year university students enrolled over three consecutive academic years in a mathematics and…
Descriptors: College Freshmen, College Mathematics, Psychological Patterns, Predictor Variables
Buchanan, Taylor L.; Lohse, Keith R. – Measurement in Physical Education and Exercise Science, 2016
We surveyed researchers in the health and exercise sciences to explore different areas and magnitudes of bias in researchers' decision making. Participants were presented with scenarios (testing a central hypothesis with p = 0.06 or p = 0.04) in a random order and surveyed about what they would do in each scenario. Participants showed significant…
Descriptors: Researchers, Attitudes, Statistical Significance, Bias
Hoekstra, Rink; Johnson, Addie; Kiers, Henk A. L. – Educational and Psychological Measurement, 2012
The use of confidence intervals (CIs) as an addition or as an alternative to null hypothesis significance testing (NHST) has been promoted as a means to make researchers more aware of the uncertainty that is inherent in statistical inference. Little is known, however, about whether presenting results via CIs affects how readers judge the…
Descriptors: Computation, Statistical Analysis, Hypothesis Testing, Statistical Significance
Kozak, Marcin – Teaching Statistics: An International Journal for Teachers, 2010
Asterisks should not be used to indicate if the result of a hypothesis test is significant.
Descriptors: Hypothesis Testing, Statistics, Mathematical Concepts, Mathematics Instruction
LeMire, Steven D. – Journal of Statistics Education, 2010
This paper proposes an argument framework for the teaching of null hypothesis statistical testing and its application in support of research. Elements of the Toulmin (1958) model of argument are used to illustrate the use of p values and Type I and Type II error rates in support of claims about statistical parameters and subject matter research…
Descriptors: Hypothesis Testing, Relationship, Statistical Significance, Models
Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2009
A common mistake in analysis of cluster randomized experiments is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects.…
Descriptors: Data Analysis, Statistical Significance, Statistics, Experiments
Eisenhauer, Joseph G. – Teaching Statistics: An International Journal for Teachers, 2009
Very little explanatory power is required in order for regressions to exhibit statistical significance. This article discusses some of the causes and implications. (Contains 2 tables.)
Descriptors: Statistical Significance, Educational Research, Sample Size, Probability
Serlin, Ronald C. – Psychological Methods, 2010
The sense that replicability is an important aspect of empirical science led Killeen (2005a) to define "p[subscript rep]," the probability that a replication will result in an outcome in the same direction as that found in a current experiment. Since then, several authors have praised and criticized 'p[subscript rep]," culminating…
Descriptors: Epistemology, Effect Size, Replication (Evaluation), Measurement Techniques
Vaughn, Brandon K.; Wang, Pei-Yu – Journal on School Educational Technology, 2009
The use of visual aids is expected to have a positive effect on students' learning. However, not all visual aids work equally well. A recent meta-analytic research which examined 42 studies has found that the use of animated visuals does not facilitate learning (Anglin, Vaez & Cunnincham, 2004). The failure of visual aids can be attributed to…
Descriptors: Visual Aids, Introductory Courses, Statistics, Instructional Design
Lawton, Leigh – Journal of Statistics Education, 2009
Hypothesis testing is one of the more difficult concepts for students to master in a basic, undergraduate statistics course. Students often are puzzled as to why statisticians simply don't calculate the probability that a hypothesis is true. This article presents an exercise that forces students to lay out on their own a procedure for testing a…
Descriptors: Hypothesis Testing, Probability, Learning Activities, Statistics