Essentials

These Essential Guides are designed for students new to statistics, covering 8 key areas: (1) descriptive and inferential statistics; (2) types of varialbes; (3) measures of central tendency; (4) measures of spread; (5) frequency distributions; (6) the standard score (z-score); (7) hypothesis testing; and (8) sampling. If you are new to statistics, we recommend that you read these in order from guides 1 through 8.

1. Descriptive and inferential statistics

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When analysing a group of data, such as the marks that 100 students received for a piece of coursework, it is possible to use both descriptive and inferential statistics to summarize and describe that data. This guide aims to discuss these two types of statistics.

2. Types of variable

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All experiments examine some kind of variable(s). Variables can be characterised as dichotomous (or nominal), discrete (or qualitative / categorical / ordinal), and continuous (or quantitative / interval / ratio). This guide aims to explain these variables, as well as the differences between indpendent and dependent variables.

3. Measures of central tendency

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Measures of central tendency are ways of describing the central position of a frequency distribution for a group of data. This guide aims to set out and explain the three mean measures of central tendency, namely the mode, median and mean.

4. Measures of spread

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Measures of spread are ways of summarizing a group of data by describing how spread out the scores are. This guide aims to set out and explain the main meaures of spread, namely the range, quartiles, variation (both absolute deviation and variance) and standard deviation.

5. Frequency distributions

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Frequency distributions are tabular and graphical ways of summarizing a group of data. This guide aims to set out and explain different types of frequency distributions, including the normal distribution, standard normal distribution, and a number of other common frequency distributions.

6. Standard score (z-score)

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The standard score (more commonly referred to as a z-score) provides a way of calculating the probability that a given score will occur within a normal distribution. This guide aims the standard normal distribution and z-score, as well as show how it is calculated and how it can be used.

7. Hypothesis testing

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Whilst all pieces of quantitative research have some dilemma, issue or problem that they are trying to investigate, the focus in hypothesis testing is to find ways to structure these in such a way that we can test them effectively. This guide aims to explain how to do this.

8. Sampling

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When conducting quantitative research it is very important that a sample is as representative as possible to the population being studied. This guide aims to discuss probabiliy and non-probability sampling techniques, as well as how to calculate the sample mean and standard deviation, and standard error of the mean.