Module 03 - What Does My Data Look Like.pdfView Download

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Module 3: What Does

My Data LOOK Like?

Data Tables

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• Data Tables are used to present your Science

Fair information in a concise and clear

manner.

• It will help you and the judges better

understand all of the work you have done.

• Tables are created with Columns and Rows.

• Each Row and Column will have a meaningful

title to help understand the data that is in that

row/column location.

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Data Tables

Column 1 Column 2 Column 3 Column 4 Row 1

Row 2

Row 3 Location (Row 3, Column 2)

Row 4 Row 5 Row 6

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Science Fair Example

• Using our Popcorn Experiment the Data Table would look like this:

* NOTE: Brand A only has 5 sample bags to test. Brand B only has 4 sample bags to test.

# Popped Kernels / Sample bag Brand A Brand B Brand C Sample Bag 1 ₈₆ ₈₈ ₈₁ Sample Bag 2 ₈₂ ₈₅ ₇₉ Sample Bag 3 ₈₄ ₉₆ ₈₂ Sample Bag 4 ₇₈ ₁₀₁ ₇₇

Sample Bag 5 ₉₁ _* ₇₅

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Science Fair Example

• Continuing our Popcorn Experiment, another Data Table would look like this:

% of Popped Kernels / Sample bag Brand A Brand B Brand C Sample Bag 1 ₂₂ ₂₈ ₁₁ Sample Bag 2 ₁₆ ₃₀ ₁₂ Sample Bag 3 ₁₈ ₂₄ ₁₂ Sample Bag 4 ₁₄ ₂₅ ₁₀

Sample Bag 5 ₁₅ _* ₁₃

Sample Bag 6 _* _* ₁₂

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Science Fair Example

• Since we are interested in the number of Popped Kernels, we would add onto the Data Table with the statistics we calculated in earlier steps.

# of Popped Kernels Brand A Brand B Brand C Sample Bag 1 86 88 81

Sample Bag 2 82 85 79

Sample Bag 3 84 96 82

Sample Bag 4 78 101 77

Sample Bag 5 91 * 75

Sample Bag 6 * * 84

Mean = 84.2 92.5 79.7

Standard Deviation = _4.82 _7.33 _3.33

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Science Fair Example

Data Table Conclusions

• Brand A was in the middle, with the average number of popped kernels and the

amount of variation of the number of popped kernels • Brand B, on average, has

the most number of popped kernels from the samples tested. Brand B also has the most amount of variation in the number of popped

kernels in a sample bag.

• Brand C, on average had the least amount of popped

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• Bar charts are a very simple way of presenting data, with bars that represent the number of occurrences of a value.

• Bar charts can be made with vertical bars or horizontal bars.

• Histograms are a slightly more sophisticated bar chart that shows the frequency of the values (% Occurrence).

• The values are usually grouped into intervals.

Typically, if < 50 samples, then 5 – 7 intervals are needed. (Refer to Memory Jogger II, First Edition, by M. Brassard & D. Ritter)

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Bar Chart Example

• For example we have the following hourly

temperature readings in Detroit, Michigan:

Dec 9th --29, 30, 29, 28, 28, 27, 26, 24, 23, 22, 21, 21 & 21 Dec 10th – 18, 19, 21, 22, 22, 22,

22, 21, 21, 21, 21, 21 & 21 Dec 11th – 21, 23, 22, 21, 21, 20,

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Histogram Example

• For example, we have the following hourly

temperature readings in Detroit, Michigan:

Dec 9th --29, 30, 29, 28, 28, 27, 26, 24, 23, 22, 21, 21 & 21 Dec 10th – 18, 19, 21, 22, 22, 22,

22, 21, 21, 21, 21, 21 & 21 Dec 11th – 21, 23, 22, 21, 21, 20,

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Science Fair Example

• Going back to our Science Fair

Example, we may want to plot the following data on a bar chart.

Sample Bag 2 82 85 79

Sample Bag 3 84 96 82

Sample Bag 4 78 101 77

Sample Bag 5 91 * 75

Sample Bag 6 * * 84

Mean = 84.2 92.5 79.7

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Science Fair Example

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Science Fair Results

• The Bar chart on the left provides us a visual

representation of our data results.

• The Histogram on the right shows us a little

more about the distribution of the data

results.

– Brand C had a very tight distribution, with a low standard deviation or spread of data. Therefore, it popped the most consistently.

– Brand B had a peak at the far right side of the graph indicating that 50% of the Brand B bags had the most fully popped kernels.

• Note, make sure you use axis titles and unit descriptions

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• Line charts are another very simple way of presenting data.

• Line charts are typically used to indicate data changes over a factor, such as, time.

• Line charts can show valleys or peaks in the data. • Or Line charts can show a trend of the data over a

factor, like time.

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Line Chart Example

• For example, we have the hourly temperature readings in Detroit,

Michigan from Noon to Midnight:

Dec 9th --29, 30, 29, 28, 28, 27, 26, 24, 23, 22, 21, 21 & 21 Dec 10th – 18, 19, 21, 22, 22, 22,

22, 21, 21, 21, 21, 21 & 21 Dec 11th – 21, 23, 22, 21, 21, 20,

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Line Chart Example

• Or using the same data, we could make a line chart comparison by time of day

Dec 9th --29, 30, 29, 28, 28, 27, 26, 24, 23, 22, 21, 21 & 21 Dec 10th – 18, 19, 21, 22, 22, 22,

22, 21, 21, 21, 21, 21 & 21 Dec 11th – 21, 23, 22, 21, 21, 20,

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Line Charts Results

• Both charts use the same data, but represent

the data in different ways.

– The first chart shows an overall trending of data over a 3 day period. – The second chart compares the temperatures at the same time of day

for the 3 day period.

• Make sure you understand what you are

trying to represent with your data, so the

graph can give you an accurate and clear

picture.

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Science Fair Example

• Going back to our Science Fair

Example, we may want to plot the following data on a line chart.

Sample Bag 2 82 85 79

Sample Bag 3 84 96 82

Sample Bag 4 78 101 77

Sample Bag 5 91 * 75

Sample Bag 6 * * 84

Mean = 84.2 92.5 79.7

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Science Fair Results

• Although, the data is represented in a line graph, it is not very useful.

• There is no relative meaning to compare the individual sample bags to each other. • And there is no time