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- Understanding Statistical Concepts

This guide will assist you to locate relevant statistics for your assignments.

Chi-square tests are used to investigate whether distributions of categorical variables differ from one another.

Confidence intervals : In statistics, a confidence interval is a measure of the reliability of an estimate.

Correlation : one of the most common and most useful statistics. A correlation is a single number that describes the degree of relationship between two variables.

Descriptive Statistics are used to describe the basic features of the data in a study and together with simple graphics analysis, form the basis of virtually every quantitative analysis of data.

Dispersion (also called **variability**, **scatter**, or **spread**). Dispersion measures how the various elements behave with regards to some sort of central tendency, usually the mean. Measures of dispersion include range, interquartile range, variance, standard deviation and absolute deviation.

Inferential Statistics are used to reach conclusions that extend beyond the immediate data alone. For e.g. use inferential statistics to try to infer (conclude) from the sample data what the population might think.

Linear regression consists of finding the best-fitting straight line through the points. The best-fitting line is called a regression line.

Measures of central tendency : This is a summary measure that attempts to describe a whole set of data with single value representing the middle (or centre) of its distribution)

One and two sample hypothesis tests : An introduction to one and two tail tests used in hypothesis testing using a standard bell curve with a population mean and sample mean. It includes introduction to the rejection region, p-value, and alpha.

One way analysis of variance : In statistics, one-way analysis of variance is a technique used to compare means of two or more samples. This technique can be used only for numerical data.

Probability and probability distributions (a table or an equation that links each outcome of a statistical experiment with its probability of occurrence)

Types of distributions:

- Demystifying Statistics: Fitting ModelsLecture given at the University of Sussex September 2012. Describes why statistics is an important topic to study, describes why statistics is a useful life skill (really!), looks at how we choose statistical tests to analyze data, and introduces the idea of the general linear model.
- Bozeman Science: Chi-Squared TestAn 11 minute YouTube video with a great example of how to apply the Chi-Square test.
- Statistics review 9: One-way analysis of variancean interesting free article about this statistical concept