Science Research Project
Data and Statistics
Directions: This assignment is designed to help you devise correct tables, charts, and graphs/figures for your data collection and statistical analysis plan.
What to turn in:
1. Please include DRAFT copies of all tables/charts, graphs/figures, including statistical analysis.
Note: See guidelines below for explanations about Tables and Graphs, as well as examples.
TABLES
Make a table(s) for your raw data as well as a summary of the statistics done (see examples below).
Your raw data goes in the data section of your notebook, but NOT in the results section of your SRP Paper. ONLY the summary of statistics goes in the results section of the SRP Paper and on your Display Board. (Again, see below for examples of statistical tables.)
Columns and rows must be straight and neat (typed).
Headings (with UNITS) are required on all columns and rows.
Titles go above the table, typed in ALL CAPS
Ex: TABLE 1: PLANT HEIGHT (cm) VERSUS LIGHT EXPOSURE
GRAPHS
Can be either a line graph or a bar graph. Line graphs show trends or relationships.
Bar graphs are used for comparison.
Do not make line or bar graphs for RAW data. Only graph the means (averages) for each variable or condition you are testing, as well as the control group (s).
The independent variable goes on the X-axis, the dependent variable goes on the Y-axis. Label axes with names and units. Include a key.
Titles go below the graph, typed in ALL CAPS
Ex: FIGURE 1: PLANT HEIGHT (cm) VERSUS LIGHT EXPOSURE
Use software packages to create graphs when possible. No graphs are to be done on loose leaf paper with hand drawn lines. (See directions/hints/examples in below).
Examples of Statistical Data Tables
Quantitative
TABLE 10.5 Effect of Fertilizer on the Mean Height (cm) of Bean Plants
DescriptiveInformation / Commercial / Compost / Control
Mean
Variance
Standard Deviation
Number / 7.0
3.6
1.9
10 / 5.0
2.2
1.5
10 / 4.0
2.0
1.4
10
Results of ttest / Commercial vs. Compost
t = 2.6 0.01<p<0.05 / Compost vs.Control
t = 1.5 p >0.01 / Commercial vs. Control
t = 4.0 p <0.00
At df 18; µ of 0.01; t =2.878 for significance
Table from “Students and Research”, 2nd Edition, Cothron, Julia, Giese, Ronald, Rezba, Richard. Kendall/Hunt PublishingCompany. Dubuque, Iowa. 1993.
Sample Statistical Analysis for Quantitative Data
FOR EXAMPLE - A student tested the effect of different types of fertilizers on plants. Below is his data for his control and fertilizer A.
Trial Number / Control GroupHeight of plant (mm) / Fertilizer A
Height of plant (mm)
1 / 45.0 / 47.4
2 / 46.2 / 48.5
3 / 51.4 / 55.2
4 / 43.2 / 49.1
5 / 44.1 / 52.3
6 / 42.7 / 56.2
7 / 41.8 / 51.9
8 / 42.6 / 52.9
9 / 41.8 / 51.6
10 / 42.4 / 49.8
11 / 43.1 / 52.7
12 / 44.3 / 56.1
13 / 43.2 / 57.3
14 / 42.6 / 56.2
15 / 43.4 / 58.2
Steps for Using Excel for Statistics
1. Enter the data above into your Excel spreadsheet. It should look like the spreadsheet below.
2. Set up a table below your data table for your descriptive statistics. You should include mean, range, variance, and standard deviation.
3. Click in the cell for the mean of the control.
4. Click on Formula on the Tool Bar. Click on fx and the insert function will box will open. This will allow you to insert a formula into the spreadsheet. The Mean of a set of numbers is the Average. In the select category box, select Statistics. Under select a function, select Average and then click OK
5. A box titled Function Arguments will open.
6. Take the mouse and highlight the numbers. A dotted line will appear around the column.
7. You will see that the average has been calculated to be 43.85333. Click OK. The average will be transferred to the mean cell in the spreadsheet.
8. Repeat steps 3 – 7 to calculate the mean for the data for Fertilizer A. The mean value you calculate for Fertilizer A should be 53.02667.
9. To calculate the Range, subtract the smallest number from the largest number. Enter the value into the cell for that value.
10. To calculate the variance, repeat steps 3 – 7 selecting VAR from the menu.
11. To calculate the standard deviation, repeat steps 3 – 7 selecting STDEV from the menu.
12. Your calculations should give you the following values:
Control / Fertilizer AMean / 43.8533 / 53.0267
Range / 9.6000 / 10.8000
Variance / 5.7627 / 11.5192
Standard Deviation / 2.4006 / 3.3940
13. We are going to calculate a value for the t-test. In the area below the standard deviation value, type the word T-Test.
14. Click on the cell next to the T-Test cell.
15. Click on Formula on the Tool Bar. Click on fx and the insert function will box will open.
16. In the selection area, select TTEST. Your screen should look like this:
17. Click on OK. Your screen should look like this:
18. Click in the box next to Array1. Highlight the numbers in the control column.
19. Click in the box next to Array2. Highlight the numbers in the Fertilizer A column.
20. Click in the box next to Tails. If you have a one-tailed test, type in one. If you have a two-tailed test, type in two.
21. What is the meaning of a two-tailed test? If you are using a significance level of alpha = 0.05, a two-tailed test allots half of your alpha to testing the statistical significance in one direction and half of your alpha to testing statistical significance in the other direction. This means that .025 is in each tail of the distribution of your test statistic. When using a two-tailed test, regardless of the direction of the relationship you hypothesize, you are testing for the possibility of the relationship in both directions.
22. For a one tailed test, you are testing for the possibility of the relationship in either the left-tail area or the right tail area.
23. We are doing a two-tailed test so you need to enter a two next to tails.
24. Click in the box next to Type. If you are doing a paired test, enter 1. If you are doing a t-test in which the two samples have equal variances, you would type a 2. If the two samples have unequal variances, type 3. Our variances are not equal, so type 3.
25. Your screen should look like this:
26. Click on OK.
27. You get a value of 6.46129E-09. This is the probability that the results happened by chance. Since the p-value is so small, you would reject the null hypothesis.
Making a graph of your data.
You want to graph your descriptive statistics. Highlight your descriptive statistics.
1. Click on Insert on the Toolbar.
2. Click on the type of graph your want. Click on the columns.
3. Click on 2-D columns.
4. If your graph covers your data, you can click on the graph and move the graph.