# Data USA

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- graphing
- statistics

- biology

- citizenship
- geography
- government
- the economy

- Special Needs

###### Pros

The data is extensive, relevant, and interesting, and it's presented in a way that's easy to read and understand.###### Cons

While extensive, there are still limitations -- you won’t find data for all industries, occupations, cities, schools, or other countries.###### Bottom Line

An efficient research tool that makes it easier to incorporate stats into a host of lessons or projects focusing on the U.S.None

With a little guidance, students will enjoy digging into the data and find interesting stats about various U.S. topics. Teachers can find many tidbits to spruce up presentations, activities, or discussions.

The sleek design makes digging into this trove of research a breeze. All the stats are clearly laid out, accompanied by colorful graphs or maps so students don't have to wade through a lot of text or tables to find useful data.

There's some explanation of stats and links to the original sources but no lessons. Teachers can embed graphs on websites or share them via social media. Great site for diverse learners as the text and visuals are clear and simple.

One way to kick off Data USA in your classroom is to have students explore one specific data set (for instance, looking at poverty rates on the Maps feature). Task students with finding something they think is interesting about the data, and then have them draft a question they'd like to explore based on what they found.

That's only the tip of the iceberg, though. Teachers from many subject areas can find uses for Data USA, whether they be in social studies, science, math, or career planning. Social studies, government, and economics teachers will like it for projects or discussions related to U.S. demographics, economics, and government indicators. Science and math teachers can get students to practice graph interpretation, map analysis, and statistical calculations. The occupation and education research pages are ideal for college and career planning research -- never too early for students to start this! Teachers will like that they can download any of the graphs, embed graphs on their websites, or share via social media (if they use this with students). The site seems like an ideal resource for a cross-curricular project in social studies, science, and math.

Read more Read lessData USA is a data-search and -visualization website that aims to make U.S. government data more accessible to the public. Data sources include the U.S. Census, the U.S. Department of Labor, the University of Wisconsin Population Health Institute, and the National Center for Education Statistics. Data USA removes the tedium of finding and sorting through often esoteric and unappealing sets of data across disparate websites, instead giving students a one-stop shop for well-visualized research on a range of topics such as the economy, demographics, education, housing and living, health, and safety. They can find information organized by location, industry, occupation, and post-secondary school.

The site is clean and intuitive, which makes searching for common data/stats very easy. The results are displayed in a simple, well-organized way, with colorful graphs. There's a map-search page that will show data for a number of topics overlaid on a U.S. map. There are also several short articles that highlight stats related to various topics as well.

Read more Read lessData USA was not designed for classrooms necessarily, but teachers and students will find its super-easy search functions and simple visualizations useful to teach statistics and data analysis; to kick off research projects; or to supplement lessons on a range of content with real and relevant statistics. All graphs have interactive keys and rollover info that displays data and margin of error. Users can find explanations of various stat calculations (including some formulas). You also have the option to see data tables and link to the data sources used to make each graph. Students will be able to look at two data sets side by side using the Add Comparison button. All these features make this site a reliable and easy-to-use research tool that is great for all students, including visual learners and English learners. Still, don't expect any plug-and-play lessons or classroom-specific support, and, while there's tons here to explore, the data is limited to the U.S.

Read more Read less## Key Standards Supported

## Reading Science/Technical | |

RST.9-10: Integration of Knowledge and Ideas | |

RST.9-10.7 | Translate quantitative or technical information expressed in words in a text into visual form (e.g., a table or chart) and translate information expressed visually or mathematically (e.g., in an equation) into words. |

## Writing HS/S/T WHST.6-8 | |

Text Types and Purposes: Research to Build and Present Knowledge | |

WHST.6-8.7 | Conduct short research projects to answer a question (including a self-generated question), drawing on several sources and generating additional related, focused questions that allow for multiple avenues of exploration. |

WHST.6-8.8 | Gather relevant information from multiple print and digital sources, using search terms effectively; assess the credibility and accuracy of each source; and quote or paraphrase the data and conclusions of others while avoiding plagiarism and following a standard format for citation. |

WHST.9-10: Research to Build and Present Knowledge | |

WHST.9-10.7 | Conduct short as well as more sustained research projects to answer a question (including a self-generated question) or solve a problem; narrow or broaden the inquiry when appropriate; synthesize multiple sources on the subject, demonstrating understanding of the subject under investigation. |

WHST.9-10.8 | Gather relevant information from multiple authoritative print and digital sources, using advanced searches effectively; assess the usefulness of each source in answering the research question; integrate information into the text selectively to maintain the flow of ideas, avoiding plagiarism and following a standard format for citation. |

WHST.11-12: Research to Build and Present Knowledge | |

WHST.11-12.7 | Conduct short as well as more sustained research projects to answer a question (including a self-generated question) or solve a problem; narrow or broaden the inquiry when appropriate; synthesize multiple sources on the subject, demonstrating understanding of the subject under investigation. |

WHST.11-12.8 | Gather relevant information from multiple authoritative print and digital sources, using advanced searches effectively; assess the strengths and limitations of each source in terms of the specific task, purpose, and audience; integrate information into the text selectively to maintain the flow of ideas, avoiding plagiarism and overreliance on any one source and following a standard format for citation. |

## Statistics And Probability | |

6.SP: Develop Understanding Of Statistical Variability. | |

6.SP.1 | Recognize a statistical question as one that anticipates variability in the data related to the question and accounts for it in the answers. For example, “How old am I?” is not a statistical question, but “How old are the students in my school?” is a statistical question because one anticipates variability in students’ ages. |

6.SP.2 | Understand that a set of data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape. |

6.SP.3 | Recognize that a measure of center for a numerical data set summarizes all of its values with a single number, while a measure of variation describes how its values vary with a single number. |

Summarize And Describe Distributions. | |

6.SP.4 | Display numerical data in plots on a number line, including dot plots, histograms, and box plots. |

6.SP.5 | Summarize numerical data sets in relation to their context, such as by: |

6.SP.5.a | Reporting the number of observations. |

6.SP.5.b | Describing the nature of the attribute under investigation, including how it was measured and its units of measurement. |

6.SP.5.c | Giving quantitative measures of center (median and/or mean) and variability (interquartile range and/or mean absolute deviation), as well as describing any overall pattern and any striking deviations from the overall pattern with reference to the context in which the data were gathered. |

6.SP.5.d | Relating the choice of measures of center and variability to the shape of the data distribution and the context in which the data were gathered. |

7.SP: Use Random Sampling To Draw Inferences About A Population. | |

7.SP.1 | Understand that statistics can be used to gain information about a population by examining a sample of the population; generalizations about a population from a sample are valid only if the sample is representative of that population. Understand that random sampling tends to produce representative samples and support valid inferences. |

7.SP.2 | Use data from a random sample to draw inferences about a population with an unknown characteristic of interest. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions. For example, estimate the mean word length in a book by randomly sampling words from the book; predict the winner of a school election based on randomly sampled survey data. Gauge how far off the estimate or prediction might be. |

Draw Informal Comparative Inferences About Two Populations. | |

7.SP.3 | Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability. For example, the mean height of players on the basketball team is 10 cm greater than the mean height of players on the soccer team, about twice the variability (mean absolute deviation) on either team; on a dot plot, the separation between the two distributions of heights is noticeable. |

7.SP.4 | Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations. For example, decide whether the words in a chapter of a seventh-grade science book are generally longer than the words in a chapter of a fourth-grade science book. |

Investigate Chance Processes And Develop, Use, And Evaluate Probability Models. | |

7.SP.5 | Understand that the probability of a chance event is a number between 0 and 1 that expresses the likelihood of the event occurring. Larger numbers indicate greater likelihood. A probability near 0 indicates an unlikely event, a probability around 1/2 indicates an event that is neither unlikely nor likely, and a probability near 1 indicates a likely event. |

7.SP.6 | Approximate the probability of a chance event by collecting data on the chance process that produces it and observing its long-run relative frequency, and predict the approximate relative frequency given the probability. For example, when rolling a number cube 600 times, predict that a 3 or 6 would be rolled roughly 200 times, but probably not exactly 200 times. |

7.SP.7 | Develop a probability model and use it to find probabilities of events. Compare probabilities from a model to observed frequencies; if the agreement is not good, explain possible sources of the discrepancy. |

7.SP.7.a | Develop a uniform probability model by assigning equal probability to all outcomes, and use the model to determine probabilities of events. For example, if a student is selected at random from a class, find the probability that Jane will be selected and the probability that a girl will be selected. |

7.SP.7.b | Develop a probability model (which may not be uniform) by observing frequencies in data generated from a chance process. For example, find the approximate probability that a spinning penny will land heads up or that a tossed paper cup will land open-end down. Do the outcomes for the spinning penny appear to be equally likely based on the observed frequencies? |

7.SP.8 | Find probabilities of compound events using organized lists, tables, tree diagrams, and simulation. |

7.SP.8.a | Understand that, just as with simple events, the probability of a compound event is the fraction of outcomes in the sample space for which the compound event occurs. |

7.SP.8.b | Represent sample spaces for compound events using methods such as organized lists, tables and tree diagrams. For an event described in everyday language (e.g., “rolling double sixes”), identify the outcomes in the sample space which compose the event. |

7.SP.8.c | Design and use a simulation to generate frequencies for compound events. For example, use random digits as a simulation tool to approximate the answer to the question: If 40% of donors have type A blood, what is the probability that it will take at least 4 donors to find one with type A blood? |

8.SP: Investigate Patterns Of Association In Bivariate Data. | |

8.SP.1 | Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association. |

8.SP.2 | Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line. |

8.SP.3 | Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height. |

8.SP.4 | Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table. Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns to describe possible association between the two variables. For example, collect data from students in your class on whether or not they have a curfew on school nights and whether or not they have assigned chores at home. Is there evidence that those who have a curfew also tend to have chores? |

## Key Standards Supported

## Ecosystems: Interactions, Energy, and Dynamics | |

## HS-LS2 | |

HS-LS2-2 | Use mathematical representations to support and revise explanations based on evidence about factors affecting biodiversity and populations in ecosystems of different scales. |