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Analyzing Data

Students analyze data collected in the last segment and interpret that data by constructing an argument that explains whether the data shows that their hypothesis should be supported or rejected. Significant figures are mentioned and the importance of data replication is also discussed.

Host introduces the Science and Engineering Practice: Analyzing and Interpreting Data and Science and Engineering Practice: Using Math and Computational Thinking. Teacher explains the importance of data replication to minimize sources of error. Teacher defines significant figures and students create a data table.

Premiere Date: July 10, 2016 | Runtime: 00:08:30

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Unit 1F Note Taking Guide & Segment Questions

Science & Engineering Practices

Analyzing and Interpreting Data

Once collected, data must be presented in a form that can reveal any patterns and relationships and that allows results to be communicated to others. Because raw data as such have little meaning, a major practice of scientists is to organize and interpret data through tabulating, graphing, or statistical analysis. Such analysis can bring out the meaning of data—and their relevance—so that they may be used as evidence.
Engineers, too, make decisions based on evidence that a given design will work; they rarely rely on trial and error. Engineers often analyze a design by creating a model or prototype and collecting extensive data on how it performs, including under extreme conditions. Analysis of this kind of data not only informs design decisions and enables the prediction or assessment of performance but also helps define or clarify problems, determine economic feasibility, evaluate alternatives, and investigate failures. (NRC Framework, 2012, p. 61-62)

Constructing Explanations and Designing Solutions

The goal of science is the construction of theories that provide explanatory accounts of the world. A theory becomes accepted when it has multiple lines of empirical evidence and greater explanatory power of phenomena than previous theories.”(NRC Framework, 2012, p. 52)

Using Mathematics and Computational Thinking

Although there are differences in how mathematics and computational thinking are applied in science and in engineering, mathematics often brings these two fields together by enabling engineers to apply the mathematical form of scientific theories and by enabling scientists to use powerful information technologies designed by engineers. Both kinds of professionals can thereby accomplish investigations and analyses and build complex models, which might otherwise be out of the question. (NRC Framework, 2012, p. 65)


 constant - also known as the controlled variable, any factor that is kept the same during an experiment. 

hypothesis - a tentative explanation or prediction that can be tested by further investigation. 

manipulated variable - also know as the independent variable, the one factor that changes within an experimental group.

meniscus - the curved surface at the top of the liquid in a tube. 

model - a physical, conceptual, or mathematical representation of a real phenomenon whose purpose is to explain and predict what happens in real life. 

observation - any information gathered using any of your five senses or lab instruments.

qualitative data - measurements that do not include numbers.

quantitative data - measurements that include numbers.

replication - data collected by different teams from samples gathered at the same location. 

responding variable - also known as the dependent variable, the variable that is being measured as a result of the experiment. 

significant figures - a term that represents the precision of a measurement. 

Georgia Standards of Excellence

SC6Obtain, evaluate, and communicate information about the properties that describe solutions and the nature of acids and bases.

SC6.cUse mathematics and computational thinking to evaluate commercial products in terms of their concentrations (i.e., molarity and percent by mass).

SC6.fUse mathematics and computational thinking to compare, contrast, and evaluate the nature of acids and bases in terms of percent dissociation, hydronium ion concentration, and pH. (Clarification statement: Understanding of the mathematical relationship between negative logarithm of the hydrogen concentration and pH is not expected in this element. Only a conceptual understanding of pH as related to acid/basic conditions is needed.)

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