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Apprenticeship Learning Support

Statistics

As part of the dissemination and awareness process we'll be sharing videos from external sources.

The following video is from the Khan Academy, and walks through how to calculate a number of descriptive statistics; mean, mode, median.

These measure averages and are regularly used as the starting point in understanding the dataset.

As the data set becomes larger, and more complex calculating by hand becomes more problematic (and prone to errors). Therefore, you can calculate the descriptive statistics using a spreadsheet. The following (silent) video walks through how to calculate a number of different descriptive statistics using Google Spreadsheets.

This is informed by a Level 5 Adult Nurse student who asked the question as an outcome of the module she is studying on Research for Practice (Qualitative Methods and Tools).

  • What is the difference between descriptive and inferential statistics?
  • What are descriptive statistics?

The videos answer these questions, and give some really useful background to the different types of data, based on examples, what tests you can perform based on the type of data, and how to apply it to your research or when reading research papers.

As part of the dissemination and awareness process we'll be sharing videos from external sources. To start the process I've selected the Statistics 101 Course on YouTube, by Brandon Foltz (https://www.youtube.com/user/BCFoltz/videos). He regularly publishes videos around statistical techniques. I'll admit, these are more directed towards the final year / dissertation students.

The following video explores the concept of correlation. Given it is part of a series, the start makes reference to the previous video. Therefore, I'd suggest, sit back, relax and give it time.

Correlation is a very useful statistical test for exploring two data sets which have no causal relationship. Excel (and Google Spreadsheet) includes an inbuilt function for calculating correlation coefficient. The following video outlines how this is done.

A requirement is the use of statistics to help us either accept or reject a hypothesis (A hypothesis is a proposed explanation for a phenomenon. For a hypothesis to be a scientific hypothesis, the scientific method requires that one can test it. Wikipedia, http://en.wikipedia.org/wiki/Hypothesis).

The accepting or rejecting of a Null Hypothesis, often involves a T Test (where the sample is less than 30) or a Z Test (where the sample is greater than 30).

The following video walks through an illustration of what this means and how to complete a T Test. Although the software application often calculates the actual number, it is really useful for us to understand how it is calculated to help our interpretation. The following video is from the Khan Academy (https://www.khanacademy.org/).

Currently, one of the most frequent requests we receive is around, "what is a p value? what does it mean?"

The following videos have been selected to answer the following questions;

  • what is a p-value?
  • when and where are thy used?
  • what do they show?

The videos use lots of terminology, a key one to remember, is "Null hypothesis, refers to a general statement or default position that there is no relationship between two measured phenomena." If we reject the Null hypothesis, (indicated by a low p-value) we can accept the alternate hypothesis"