Making inferences from data

Article Abstract:

Analyzing sample data allows inferences to be made about the wider population. When making these inferences, it is important to take the size of the sample into consideration. The accuracy of the inferences will be directly related to the size of the sample, with larger samples providing more accurate conclusions. Attention must also be given to the sampling methods used, as the method employed can have a significant impact on the data generated. The sample statistics must be presented with confidence intervals, thus allowing the reader to see the variation that will probably occur in the wider population.

Methods, Analysis, Statistical sampling, Sampling (Statistics), Inference

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Data and data summaries

Article Abstract:

Health care workers will benefit from an understanding of statistical techniques. It will help them in their reading and in their own data presentation. Statistical techniques concern the presentation and analysis of quantitative data which may be nominal, ordinal, interval or ratio. Consideration of the type of data is important, as it determines the choice of statistical method. Nominal or ordinal data, for example, is best suited to a tabular presentation. Other useful statistical techniques include calculation of the arithmetic mean, the median, and the standard deviation.

Management, Statistics, Statistics (Data)

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Tests for categorical data

Article Abstract:

The relationships between variables are of interest in research, and statistical hypotheses tests can help to draw conclusions of the significances of relationships between categorical variables. Such a test is the 'chi-squared test for association'. Variations of the chi-squared test that could be used to consider the links between categorical variables, are examined.

Usage, Chi-square test (Test)

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