Try evaluating your data using similar tests. By default, Excel simply puts a count on the x-axis.
Full Answer An analysis should begin be explaining what happened in the experiment. By looking at the data from various perspectives, trying different ways of organizing the data and representing it visually and mathematically, you might stumble upon connections or trends of which you were unaware when starting the project.
Discuss exactly how your project supports this, and what may be gained from the additional research. Statistics are the third general way of examining data.
They allow complex data to be represented in a way that is easier to spot trends by eye. There are two broad categories of statistics: In Microsoft Excel, the "line graph" chart type generates a time series.
Another advantage is their versatility. For more details on how successful data analysis and good experimental design are co-dependent, see the Science Buddies guide to Experimental Design for Advanced Science Projects. To generate a time series plot with your choice of x-axis units, make a separate data column that contains those units next to your dependent variable.
For example, if you test what kinds of foods ants like to eat by offering different foods to ants, and 70 of them chose donuts instead of potato chips, you might interpret that to mean that ants prefer foods containing sugar.
Descriptive statistics are used to summarize the data and include things like average, range, standard deviation, and frequency. Use charts and graphs to help you analyze the data and patterns.
You might also find it useful to consult with statistical textbooks, math teachers, your science project mentor, and other science or engineering professionals. Instead discuss whether you accept or reject your hypothesis, and what that means.
Compare Your Results to Others Take the time to discuss how your results compare to the findings of others who have done similar projects or sought to answer similar questions.
What did you find out from your experiment? Did you make any mistakes? It can also help you to identify outliers. Or, is it better to display your data as individual data points? The more variables you test, the longer this "playing" takes.
Three Different Ways to Examine Data Generally speaking, scientific data analysis usually involves one or more of following three tasks: It is helpful to look for patterns in the data that either support or negate your original hypothesis. For any type of graph: Data analysis occurs only after you are done collecting all your data.
None of these things could be further from the truth.In a science project, the data analysis process occurs after a person performs an experiment to determine whether the hypothesis, an educated guess, is true or false.
Analyzing the data consists of reviewing, calculating and charting the results of the experiment.
To achieve averages, multiple. How to analyze data and prepare graphs for you science fair project. Scientific research reports are an important part of finishing up science projects and sharing your results. The standard format for these types of reports includes an abstract, introduction, materials and methods, results, and an analysis or discussion section.
Taking quantitative data and analyzing it is an important part of a science fair project and scientific research in general.
Use these guide to help you make sense of your data and organize it in a clear, readable format so that you can reach a.
A data analysis is where you discuss and interpret the data collected from your project and explain whether or not it supports your hypothesis.
The analysis may discuss mistakes made while conducting the experiment or ways in which the project could be improved in the future. An analysis should. Data analysis tips and techniques for advanced science projects and other scientific research.Download