1. Chapter 19: Planning your Data Collection
““Hear, O sons, a father's instruction, and be attentive, that you may gain insight, for I give you good precepts; do not forsake my teaching.”
Proverbs 4: 1-2

2. Work though the following PowerPoint to help you make those decisions.
Introduction
Methods and Procedures (your plans for executing your project) are never complete without deciding how you are going to collect that data.
Work though the following PowerPoint to help you make those decisions.

3. Collecting Data 1. Write down what the goal of your experiment is!
Try to do this exercise with a partner if possible!
1. Write down what the goal of your experiment is!  
2. Make a list of every possible piece of information you can think of that you might want to collect about each subject.
(Challenge each other to see who can write the longest list)
You must collect all pertinent data. Don’t miss collecting data such as age, medical conditions, time of day, and any other things that could affect your experiment. Collect more data than you need. It is much harder to go back and get it later.

4. Collecting Data – Part 2
I’m collecting
Data
3. Make a data collection chart or a data worksheet.
Draw one to fit your experiment on a sheet of paper to help you get some ideas on paper.
Make sure you have a space to write in the subjects name or subject identifier.
Make a space for the data.
Make columns for all the data you’re collecting. (Label it with units!!)
Make sure you have space for each writing comments about each subject as
you test.
Data
Data
Data
Data
Data
Sample Data Collection Chart
Subject
Speed 1
Speed 2
Speed 3
Notes
Ralphie
5 Km/hr
5 Km / hr
4 Km / hr
Refused at first.
Marie
4 Km/hr
3 Km / hr Ok
Sam
Got sick at end.
Sparky
Needed more water.
Tooky
Very small dog.

5. Collecting Data – Part 3 4. Get access to Microsoft Excel.
4. Get access to Microsoft Excel.
If you do not yet know how to use it, find someone to help you learn how to enter data and turn it into a graph.
It will make your graphing so much easier and will give you important skills for the future.
Plan out the type of presentation you might like to use for your data. Graphs and charts are most common but you can get high marks for originality if you present your data in an unusual but clear way. An example of a unique way of presenting data would be to measure color change by comparing your samples to paint chips.

6. Planning A Statistical Analysis
This is for high school students or advanced middle school students!
If you completed a sample size calculation, you should easily be able to use statistics to analyze your data.
Going this extra step will definitely improve your overall score if you follow some simple steps. Although many statistical tests exist, the ones presented here are basic introductions to those most commonly used in research.

7. What Statistical Tests Should You Use??
What statistical tests are there and when should you use them?
Such a good question!!
Student T test - This is a test that compares 1 group against another. It is appropriate to use this when you have 2 groups you want to compare.
ANOVA - This is an acronym for Analysis of Variance. This test compares more than 2 groups against each other. This test is appropriate when you are comparing 3 or more study arms against each other.
Which of these tests would be appropriate for your data?
Why?

8. Vocabulary Vocabulary! Vocabulary!
P value - stands for probability and is a term that tells you how much of a chance of being wrong you are willing to take. Typically anything equal to or less than p= 0.05 is considered statistically significant.
Before you run your statistical tests, it is important to decide what you define as statistically significant for your study.
It should not be a number greater than p = 0.05
P > 0.10
No evidence against the null hypothesis. The data appear to be consistent with the null hypothesis.
0.05 < P < 0.10
Weak evidence against the null hypothesis in favor of the alternative.
0.01 < P < 0.05
Moderate evidence against the null hypothesis in favor of the alternative.
0.001 < P < 0.01
Strong evidence against the null hypothesis in favor of the alternative.
P < 0.001
Very strong evidence against the null hypothesis in favor of the alternative.
Vocabulary!
Statistically Significant - if something is statistically significant, it means
there is a real true difference between the groups being compared to each other.
Fortunately, there are computer programs that will run all the mathematics for you!!! You will need to locate a research lab or a statistician who has access to these programs. They may be willing to run them for you for free if you explain you are a student doing a science fair project.
You will need to provide them with your data and instruct them to run either the Student T test or the ANOVA.

9. Remember to write in your prayer journal and scientific notebook!!
Record your plan for data collection.
Gluing in a blank data collection form to your notebook is a good idea.
If you are going to use statistics, make sure to record those plans as well.