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Christos Giannoulis

Should Confidence Intervals or Tests of Significance be Used?

by Christos Giannoulis Leave a Comment

What is a Confidence Interval?

Any sample-based findings used to generalize a population are subject to sampling error. In other words, sample statistics won’t exactly match the population parameters they estimate.

[Read more…] about Should Confidence Intervals or Tests of Significance be Used?

Tagged With: confidence interval, p-value, sampling error, significance testing, statistical significance

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How to Reduce the Number of Variables to Analyze

by Christos Giannoulis 1 Comment

by Christos Giannoulis

Many data sets contain well over a thousand variables. Such complexity, the speed of contemporary desktop computers, and the ease of use of statistical analysis packages can encourage ill-directed analysis.

It is easy to generate a vast array of poor ‘results’ by throwing everything into your software and waiting to see what turns up. [Read more…] about How to Reduce the Number of Variables to Analyze

Tagged With: common factor analysis, dependent variable, Factor Analysis, independent variable

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How to Interpret the Width of a Confidence Interval

by Christos Giannoulis 2 Comments

One issue with using tests of significance is that black and white cut-off points such as 5 percent or 1 percent may be difficult to justify.

Significance tests on their own do not provide much light about the nature or magnitude of any effect to which they apply.

One way of shedding more light on those issues is to use confidence intervals. Confidence intervals can be used in univariate, bivariate and multivariate analyses and meta-analytic studies.

[Read more…] about How to Interpret the Width of a Confidence Interval

Tagged With: Bivariate Statistics, confidence interval, multivariate analysis, sample size, standard error, Univariate statistics

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