
Data Presentation and Analysis
Presentation
•
Science
•
8th Grade
•
Practice Problem
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Hard
R. SIMMONDS-GORDON
Used 13+ times
FREE Resource
14 Slides • 3 Questions
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Data Presentation and Analysis: Anomalies and Experimental Errors
Mrs. Simmonds-Gordon
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Lesson Objectives
At the end of this lesson you should be able to:
identify and explain experimental errors
Construct results tables
Construct pie charts using results from observations or other sources of data
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Anomalies
Definition: RESULTS THAT DO NOT FIT WITH THE GENERAL PATTERN.
Caused by experimental errors
These errors occur when the recorded reading is different from what it is supposed to be (true value).
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Example of Anomalous Data
A farmer with a large mango orchard hired some workers to assist with picking the mangoes from his trees. The following are the data he collected over the space of a week. See if you can find the anomaly.
Monday: 2 workers ---- 10 mangoes
Tuesday: 4 workers ---- 20 mangoes
Wednesday: 6 workers --- 30 mangoes
Thursday: 8 workers --- 4 mangoes
Friday: 10 workers --- 50 mangoes
WRITE DOWN YOUR ANSWER. A QUESTION IS COMING.
5
Multiple Choice
On which day was the anomalous data recorded?
Monday
Tuesday
Wednesday
Thursday
Friday
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TAKE ANOTHER LOOK AT THE DATA
A farmer with a large mango orchard hired some workers to assist with picking the mangoes from his trees. The following are the data he collected over the space of a week. See if you can find the anomaly.
Monday: 2 workers ---- 10 mangoes
Tuesday: 4 workers ---- 20 mangoes
Wednesday: 6 workers --- 30 mangoes
Thursday: 8 workers --- 4 mangoes
Friday: 10 workers --- 50 mangoes
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Multiple Choice
What is the expected number of mangoes for Thursday?
60
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40
6
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What should you do with/about anomalous data?
- Do not ignore it
- Try to figure out what went wrong and where.
- Remember to be honest! Your "error" may be a new discovery.
Home work: Read about how Roy Plunkett invented Teflon®.
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Types of Experimental Errors
Systematic errors
Random Errors
Human Errors
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Systematic Errors
These errors are usually caused by repeating the same error throughout the experiment. The error is usually due to taking measurement with faulty or inaccurate instruments. Some faults with instruments that may lead to this are:
- poor calibration - the instruments have not been adjusted and tested to ensure that they give accurate readings. Eg. a scale that does not go to 0 when not in use.
- damage or overuse: Eg. if the spring in a scale is worn out, it will stretch much lower in response to weight and give an incorrect reading
- parallax: when an instrument is read from a bad angle. Eg. reading an analogue clock from the side rather than from the front.
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Multiple Choice
Teacher said to measure and cut a piece of string that was 10 cm long. When all the strings were compared, Dahlia's was much shorter than all the others? What could have caused this?
parallax
damaged or overused instrument
poor or no calibration of instrument
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Parallax - Dahlia did not read her ruler correctly. Maybe she read it from a bad angle.
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Random Error
These errors occur due to changes in environmental conditions that the experimenter cannot change or control and is usually unaware of. Though these changes may be very small, they are significant enough to affect measurements taken during an experiment.
Eg. a 1 degree change in the temperature of the air outside
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Random Error continued
Random errors may also come about by making estimations during measurements.
Eg. Trying to measure between the millimetre marks on a ruler
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How to minimise random errors
This can be done by repeating your experiment at least 3 times and taking the average of readings or measurements that you take.
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Human Error
There a myriad (many, many) such errors. This can range from not following the experimental procedure or method correctly to writing down a wrong number or word.
eg. missing a step or substituting/improvising recording the wrong data not using instruments correctly many others...
Can you think of any?
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Thank you for your attention.
Head on over to Google Classroom for your activity.
BYE!! :)
Data Presentation and Analysis: Anomalies and Experimental Errors
Mrs. Simmonds-Gordon
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