A group of students have noted that the sidewalks on Temple Street have more cracks than those located on Cambridge and Beacon Streets. 1. Develop a hypothesis that might explain this observation and design an experimental system to test this hypothesis. Include the following in your design: a) The type of measurements of sidewalk surface b) How these measurements are to be made and documented c) The number of measurements required for a significant evaluation d) The types of samples (experimental systems) that will be measured e) Which samples will serve as controls. f) Which samples will serve as a model for your experimental system. Make up some results and decide whether these results support or negate your hypothesis? Why? (Justify your decision.) Here's a helpful hint on how to report your data. A typical graph representing the relationship between dependent and independent variables. Number of Cracks- Dependent Variable Proposed Cause of Cracks- Independent Variable In order to establish cause and effect, the dependent and independent variables should be correlated. If they are not correlated, then the independent variable is not the cause. If they are correlated then the independent variable may be the cause. Further experimentation is always necessary to establish causation especially in Biology.

Traffic and Highway Engineering
5th Edition
ISBN:9781305156241
Author:Garber, Nicholas J.
Publisher:Garber, Nicholas J.
Chapter19: Design Of Flexible Highway Pavements
Section: Chapter Questions
Problem 15P
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Don’t use these causes and come up with a different causes. - foot traffic - freeze thaw cycles on walkway surfaces - salt deposition
A group of students have noted that the sidewalks on Temple Street have more cracks than
those located on Cambridge and Beacon Streets.
1.
Develop a hypothesis that might explain this observation and design an experimental
system to test this hypothesis.
Include the following in your design:
a) The type of measurements of sidewalk surface
b) How these measurements are to be made and documented
c) The number of measurements required for a significant evaluation
d) The types of samples (experimental systems) that will be measured
e) Which samples will serve as controls.
f) Which samples will serve as a model for your experimental system.
Make up some results and decide whether these results support or negate your
hypothesis? Why? (Justify your decision.)
Here's a helpful hint on how to report your data.
A typical graph representing the
relationship between dependent
and independent variables.
Number of Cracks-
Dependent Variable
Proposed Cause of Cracks-
Independent Variable
In order to establish cause and effect, the dependent and independent variables should be
correlated. If they are not correlated, then the independent variable is not the cause. If they are
correlated then the independent variable may be the cause. Further experimentation is always
necessary to establish causation especially in Biology.
Transcribed Image Text:A group of students have noted that the sidewalks on Temple Street have more cracks than those located on Cambridge and Beacon Streets. 1. Develop a hypothesis that might explain this observation and design an experimental system to test this hypothesis. Include the following in your design: a) The type of measurements of sidewalk surface b) How these measurements are to be made and documented c) The number of measurements required for a significant evaluation d) The types of samples (experimental systems) that will be measured e) Which samples will serve as controls. f) Which samples will serve as a model for your experimental system. Make up some results and decide whether these results support or negate your hypothesis? Why? (Justify your decision.) Here's a helpful hint on how to report your data. A typical graph representing the relationship between dependent and independent variables. Number of Cracks- Dependent Variable Proposed Cause of Cracks- Independent Variable In order to establish cause and effect, the dependent and independent variables should be correlated. If they are not correlated, then the independent variable is not the cause. If they are correlated then the independent variable may be the cause. Further experimentation is always necessary to establish causation especially in Biology.
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