Advanced Science Fair Projects AWS
Advanced Science Fair Projects – Expectations for Top Projects and Tips on Getting There – – Statistics –
Teacher Workshops for CUSEF/SLVSEF 2011
The Top Competitions Intel Science Talent Search • Seniors, individual projects only • New online system • Application DUE November 17th Siemens Competition • Seniors or teams • Application DUE October 1st
The Top Competitions (cont.) Junior Science and Humanities Symposium • All high school grade levels • Intermountain region hosted at the U Other Opportunities • Davidson Fellows • USA Today Academic High School Team • Dr. Bessie F. Lawrence ISSI • Research Science Institute (RSI) • MASTERS & ISWEEP
A Few Basics… It involves A LOT of hard work and motivation! Students need mentors Can use up to 12 months of continuous research
Maintain a detailed/complete project notebook • eCAT is an electronic lab notebook. An ELN is a valid form of a lab notebook.
Characteristics of ISEF Winners Winning projects tend to have 3 characteristics: •
Sound methodology
•
Useful applications and meaningful implications
•
Contribute something new to science
A Look at the Scientific Method
Environmental Science, 10th ed, by Wright and Boorse
Research and Question Research will help you find a topic and a meaningful question College/University libraries Google scholar Follow passion, not a “hot topic”
Hypothesis and Methods Always include the “why”, not just the “what” Include your statistical hypothesis Procedures should be similar to that used by science and engineering professionals—ask them! As many replicates as possible—aim for 30
Analysis and Conclusions Analysis is the key to sound conclusions Use statistics to help you analyze your data State your conclusions (not just “I was right.”)
Support your conclusions with your analysis State the “why”—explain the outcome
Presentation and Communication Communicate clearly, concisely, and correctly Discuss project and adjacent areas of science Know the current state of things in your field
Dress for success Consult journals/style guides to help with format
Statistics is Your Friend! Begin with the end in mind Think stats when: • Developing a hypothesis • Designing an experiment • Analyzing your data • Framing conclusions • Presenting results
Three Principles of Design Replication • 30 is a great goal Control • Positive and negative Randomization • Let chance choose for you (SRS) • e.g. - coin, dice, random number table
Design: An Example 100 bits of granite need to be split into 2 groups Why randomize? How randomize? • Number for 000 to 099. First 50 random numbers go in control group.
Exploratory Data Analysis First step in analyzing data – do not skip it! Start with graphs • Histogram • Boxplot • Scatterplot Then use numbers • Mean, median, mode, standard deviation
Why Graphs? 3.60 10.28 3.74 5.05 3.60 8.80 9.84 3.10 3.00 5.00 14.25 11.00 2.80 9.00 2.10 5.00 32.00 8.50 2.99 20.93
8.00 4.63 6.50 2.05 1.21 2.00 3.00 2.40 21.11 1.55 8.50 3.90 9.00 14.00 10.00 16.00 18.50 12.50 6.75 2.75
21.35 15.39 10.03 18.00 22.98 21.45 13.21 36.60 9.51 25.95 15.43 12.00 10.00 18.00 12.00 8.00 13.01 18.00 3.50 2.30
13.00 8.75 8.90 5.75 2.30 3.88 2.20 3.20 3.00 3.13 3.57 1.40 4.70 8.50 15.00 6.20 17.50 1.15 9.88 6.00
7.00 7.20 4.94 1.20 1.55 6.40 3.00 8.70 5.60 4.80 1.30 5.30 3.50 12.62 6.15 5.25 5.60 5.60 2.45 4.00
18.00 3.50 14.00 12.00 9.50 10.85 33.00 1.18 1.60 9.20 17.00 10.50 2.40 1.75 8.50 3.00 8.60 10.50 8.50 5.97
17.70 11.00 7.35 10.50 5.75 3.70 3.60 2.68 1.75 21.32 2.05 1.95 8.74 1.31 23.40 4.37 8.21 9.30 3.25 1.75
6.48 1.50 19.00 3.50 6.10 12.21 21.97 1.51 11.99 10.70 3.30 8.59 17.22 23.37 3.05 7.50 11.56 14.05 3.80 11.00
9.00 8.00 4.10 9.50 10.00 6.60 2.47 3.22 7.90 2.65 1.83 2.60 2.22 7.17 3.10 2.75 2.10 8.50 7.55 2.25
6.45 4.75 2.10 26.00 5.75 6.00 3.70 2.20 3.00 2.40 4.10 2.44 5.62 4.50 5.00 4.50 3.00 4.60 11.00 3.70
11.83 2.30 3.50 11.62 18.53 24.36 14.00 19.50 17.00 28.63 13.28 21.35 8.60 14.17 11.15 22.45 10.90 21.53 13.74 18.76
9.68 21.56 22.43 7.83 15.02 16.80 23.71 31.00 7.91 66.00 37.00 9.12 14.69 14.00 27.00 68.00 7.00 12.30 11.75 5.75
10.60 3.20 12.80 13.00 7.00 37.37 42.25 8.88 43.70 36.34 23.51 12.31 15.00 8.94 16.00 21.63 31.62 27.75 25.00 21.63
2.90 16.50 3.00 2.64 6.70 7.00 3.80 10.26 14.80 32.35 14.22 17.87 27.84 18.66 8.10 9.03 3.80 6.10 5.50 6.00
10.30 8.00 50.46 16.55 2.25 16.50 6.50 8.00 22.00 6.75 8.00 5.90 2.70 2.65 4.35 3.25 15.01 2.10 7.00 12.25
5.30 5.50 6.10 7.00 11.93 14.65 11.75 9.14 11.98 22.66 24.27 15.78 13.50 76.93 21.94 55.68 2.20 1.20
Histogram Shows distribution of quantitative data
100
Median
120
Mode
Distribution of Caldera Sizes in the Basin and Range
Mean
Frequency
80
60
40
20
0 5
10
15
20
25
30
35
40
45
50
Caldera Size (km)
55
60
65
70
75
80
Discipline-Specific Graphs
Tulane University
Moving Toward Inference Inference uses the language of probability How we approach inference is based on EDA Hypothesis testing
P-values Statistical significance
Resources TI 83 Plus, 84 Plus, and 89 calculators Microsoft Excel R (free!)
S- PLUS, SPSS, Minitab, etc. MYSTAT
Teacher Workshops for CUSEF/SLVSEF 2011
The Top Competitions Intel Science Talent Search • Seniors, individual projects only • New online system • Application DUE November 17th Siemens Competition • Seniors or teams • Application DUE October 1st
The Top Competitions (cont.) Junior Science and Humanities Symposium • All high school grade levels • Intermountain region hosted at the U Other Opportunities • Davidson Fellows • USA Today Academic High School Team • Dr. Bessie F. Lawrence ISSI • Research Science Institute (RSI) • MASTERS & ISWEEP
A Few Basics… It involves A LOT of hard work and motivation! Students need mentors Can use up to 12 months of continuous research
Maintain a detailed/complete project notebook • eCAT is an electronic lab notebook. An ELN is a valid form of a lab notebook.
Characteristics of ISEF Winners Winning projects tend to have 3 characteristics: •
Sound methodology
•
Useful applications and meaningful implications
•
Contribute something new to science
A Look at the Scientific Method
Environmental Science, 10th ed, by Wright and Boorse
Research and Question Research will help you find a topic and a meaningful question College/University libraries Google scholar Follow passion, not a “hot topic”
Hypothesis and Methods Always include the “why”, not just the “what” Include your statistical hypothesis Procedures should be similar to that used by science and engineering professionals—ask them! As many replicates as possible—aim for 30
Analysis and Conclusions Analysis is the key to sound conclusions Use statistics to help you analyze your data State your conclusions (not just “I was right.”)
Support your conclusions with your analysis State the “why”—explain the outcome
Presentation and Communication Communicate clearly, concisely, and correctly Discuss project and adjacent areas of science Know the current state of things in your field
Dress for success Consult journals/style guides to help with format
Statistics is Your Friend! Begin with the end in mind Think stats when: • Developing a hypothesis • Designing an experiment • Analyzing your data • Framing conclusions • Presenting results
Three Principles of Design Replication • 30 is a great goal Control • Positive and negative Randomization • Let chance choose for you (SRS) • e.g. - coin, dice, random number table
Design: An Example 100 bits of granite need to be split into 2 groups Why randomize? How randomize? • Number for 000 to 099. First 50 random numbers go in control group.
Exploratory Data Analysis First step in analyzing data – do not skip it! Start with graphs • Histogram • Boxplot • Scatterplot Then use numbers • Mean, median, mode, standard deviation
Why Graphs? 3.60 10.28 3.74 5.05 3.60 8.80 9.84 3.10 3.00 5.00 14.25 11.00 2.80 9.00 2.10 5.00 32.00 8.50 2.99 20.93
8.00 4.63 6.50 2.05 1.21 2.00 3.00 2.40 21.11 1.55 8.50 3.90 9.00 14.00 10.00 16.00 18.50 12.50 6.75 2.75
21.35 15.39 10.03 18.00 22.98 21.45 13.21 36.60 9.51 25.95 15.43 12.00 10.00 18.00 12.00 8.00 13.01 18.00 3.50 2.30
13.00 8.75 8.90 5.75 2.30 3.88 2.20 3.20 3.00 3.13 3.57 1.40 4.70 8.50 15.00 6.20 17.50 1.15 9.88 6.00
7.00 7.20 4.94 1.20 1.55 6.40 3.00 8.70 5.60 4.80 1.30 5.30 3.50 12.62 6.15 5.25 5.60 5.60 2.45 4.00
18.00 3.50 14.00 12.00 9.50 10.85 33.00 1.18 1.60 9.20 17.00 10.50 2.40 1.75 8.50 3.00 8.60 10.50 8.50 5.97
17.70 11.00 7.35 10.50 5.75 3.70 3.60 2.68 1.75 21.32 2.05 1.95 8.74 1.31 23.40 4.37 8.21 9.30 3.25 1.75
6.48 1.50 19.00 3.50 6.10 12.21 21.97 1.51 11.99 10.70 3.30 8.59 17.22 23.37 3.05 7.50 11.56 14.05 3.80 11.00
9.00 8.00 4.10 9.50 10.00 6.60 2.47 3.22 7.90 2.65 1.83 2.60 2.22 7.17 3.10 2.75 2.10 8.50 7.55 2.25
6.45 4.75 2.10 26.00 5.75 6.00 3.70 2.20 3.00 2.40 4.10 2.44 5.62 4.50 5.00 4.50 3.00 4.60 11.00 3.70
11.83 2.30 3.50 11.62 18.53 24.36 14.00 19.50 17.00 28.63 13.28 21.35 8.60 14.17 11.15 22.45 10.90 21.53 13.74 18.76
9.68 21.56 22.43 7.83 15.02 16.80 23.71 31.00 7.91 66.00 37.00 9.12 14.69 14.00 27.00 68.00 7.00 12.30 11.75 5.75
10.60 3.20 12.80 13.00 7.00 37.37 42.25 8.88 43.70 36.34 23.51 12.31 15.00 8.94 16.00 21.63 31.62 27.75 25.00 21.63
2.90 16.50 3.00 2.64 6.70 7.00 3.80 10.26 14.80 32.35 14.22 17.87 27.84 18.66 8.10 9.03 3.80 6.10 5.50 6.00
10.30 8.00 50.46 16.55 2.25 16.50 6.50 8.00 22.00 6.75 8.00 5.90 2.70 2.65 4.35 3.25 15.01 2.10 7.00 12.25
5.30 5.50 6.10 7.00 11.93 14.65 11.75 9.14 11.98 22.66 24.27 15.78 13.50 76.93 21.94 55.68 2.20 1.20
Histogram Shows distribution of quantitative data
100
Median
120
Mode
Distribution of Caldera Sizes in the Basin and Range
Mean
Frequency
80
60
40
20
0 5
10
15
20
25
30
35
40
45
50
Caldera Size (km)
55
60
65
70
75
80
Discipline-Specific Graphs
Tulane University
Moving Toward Inference Inference uses the language of probability How we approach inference is based on EDA Hypothesis testing
P-values Statistical significance
Resources TI 83 Plus, 84 Plus, and 89 calculators Microsoft Excel R (free!)
S- PLUS, SPSS, Minitab, etc. MYSTAT
