u1l4 - representing data

Unit 1 Lesson 4 Representing Data

Copyright © Houghton Mifflin Harcourt Publishing Company


Indiana Standards


• NOS 8.3 Collect quantitative data with appropriate tools or technologies and use appropriate units to label numerical data.

• NOS 8.8 Analyze data, using appropriate mathematical manipulation as required, and use it to identify patterns and make inferences based on these patterns.

• NOS 8.11 Communicate findings using graphs, charts, maps and models through oral and written reports.

Modeling Data with Graphs


How do scientists make sense of data?

• All of the different types of scientific investigations involve the collection of data.

• Data are the facts, figures, and other evidence scientists gather when they conduct an investigation.

• Scientists organize and record their data in data tables.



• Data tables often have two columns.

• One column lists the independent variable, which is the variable that is deliberately manipulated in an investigation.

• The other column lists the dependent variable, which is the variable that changes as a result of manipulation of the independent variable.




• Scientists often analyze data for patterns or trends by constructing graphs of the data.

• The type of graph they construct depends upon the data they collected and what they want to show.




• A scatter plot is a graph with points plotted to show a possible relationship between two sets of data.

• In a scatter plot, the horizontal x-axis usually represents the independent variable.

• The vertical y-axis usually represents the dependent variable.

• To show the general relationship between the two variables, a “line of best fit” may be used.



More Graphing!


What do graphs show?

• Scientists use different types of graphs to show different types of information about data.

• A bar graph is used to display and compare data in a number of separate categories.

• A circle graph is used to show how each group of data relates to all of the data.


Throw Me a Curve!


What kinds of patterns can be shown using graphs?• When you graph data, you can identify what the

pattern, or trend, of the data is.

• A trend shows the relationship between the two variables studied in the experiment.

• Graphs make it easy to tell if something is increasing, decreasing, or staying the same.


What kinds of patterns can be shown using graphs?• In some cases, a line can be used to show the

trend of data on a graph.

• If the relationship between the independent and dependent variables can be shown with a straight line, the graph is called a linear graph.

• A straight line shows that the rate of change of the dependent variable with respect to the independent variable is constant.



What kinds of patterns can be shown using graphs?



• The density of water as a function of temperature is a linear relationship.

What kinds of patterns can be shown using graphs?• A graph in which the relationship between the

variables cannot be shown with a straight line is called a nonlinear graph.

• If the product of variables remains constant, the variables are said to have an inverse relationship.

• A graph of an inverse relationship is a smooth curve that becomes nearly vertical and horizontal at opposite ends.



What kinds of patterns can be shown using graphs?



• The relationship between volume and pressure for a gas at a constant temperature is a nonlinear relationship.

The Perfect Model


How do scientists select models?

• Scientists use many different kinds of models.

• Some are physical models, such as maps and globes.

• Others are mathematical models, including equations and simulations of movement.



• A model is a representation of an object or a process that allows scientists to study something in greater detail.

• A model that is too simple or too complicated may not be useful.

• The best models are those that most closely resemble the system, process, or other entity they represent.




• Scientists select models based on how much the models can explain.

• In addition, scientists select models based on how few limitations they have.

• Today, many phenomena in science can be modeled with great sophistication.



u1l4 - representing data

Science

sense of data

trend of data

data tables

quantitative data

modeling data

collection of data

numerical data

sets of data