### What can I get from this site?

• Help in developing your project plan, experiment design and data analysis
• Guidance in identifying appropriate methods of hypothesis testing (also included in project plan, above)
• Video tutorials on the use of Excel, Minitab and SPSS for data analysis, data presentation and hypothesis testing

### Developing your Project Plan and Data Analysis

#### >>Click here for help to Create your own Project Plan <<

The above link will help you plan your project, step-by-step, by building up the necessary mathematical and statistical techniques.

### Identifying an appropriate Hypothesis Test

Before attempting to identify an hypothesis test, it is necessary for you to be clear about the experimental factors involved in your project, the distribution and uncertainties of your measurement variables, and your detailed objectives. This preparative work is covered in the project plan (above),  stages 1 to 3, and must be completed before clicking below:

### Video tutorials on using Analytical Techniques

Use the following links for specific guidance and video tutorials in data analysis and the presentation and interpretation of results. (This content will be developed over the next 12 months)

 Data analysis Conversion of units and SI units Describing data and results Reporting data in text Summarizing data Confidence interval Selecting the best chart/graph Use of Excel for x-y graphs Adding error bars to graphs/charts Modelling data Summarizing data Analysing straight line (linear) data Exponential data Analysing non-linear data Hypothesis testing Selecting the right test (to be developed as an interactive web page) Interpreting the results and p-values Power of the hypothesis test Experimental design Replication and randomization Sample size Accuracy and data uncertainty

#### Introduction to Research Planning

When you first think about your research project, you will probably have some general idea that you will make some measurements, which you will then analyse in such a way that you can present your results and arrive at a conclusion.

Click here to view a short video example

As the above example shows, it is at the start of the project that you need to think very carefully about exactly what you will measure - how often, how accurately, and under what experimental conditions.
Expand/Reduce - additional text: >>

General Principle – Collecting more data (provided that it is planned in advance) will increase the quality and/or range of conclusions that you can extract from that data. However, you must not try to collect more data than is reasonably possible in the time available.

#### Initial Planning Constraints

Approvals - ethics, health and safety
Identifying analytical techniques to match experimental data
Access to resources - equipment, technical support
Availability of materials
Booking experimental time
Unexpected problems and results

#### Consider this ....

Choice of measurements must match the available data analysis software
Frequency counts for chi-squared
Requirements for normal distribution
Use of repeated measures (pairs)
Uncertainty - number of replicates - precision - power of test - available time/resources - no of factor levels

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