Learning Activities (1) | Classroom Resources (4) |

View Standards
**Standard(s): **
[ELA2015] (6) 35 :

[ELA2015] (7) 34 :

[MA2019] (6) 24 :

[DLIT] (6) 5 :

[DLIT] (6) 6 :

[DLIT] (6) 29 :

[DLIT] (7) 6 :

[DLIT] (7) 22 :

[DLIT] (7) 29 :

35 ) Include multimedia components (e.g., graphics, images, music, sound) and visual displays in presentations to clarify information. [SL.6.5]

[ELA2015] (7) 34 :

34 ) Include multimedia components and visual displays in presentations to clarify claims and findings and emphasize salient points. [SL.7.5]

[MA2019] (6) 24 :

24. Represent numerical data graphically, using dot plots, line plots, histograms, stem and leaf plots, and box plots.

a. Analyze the graphical representation of data by describing the center, spread, shape (including approximately symmetric or skewed), and unusual features (including gaps, peaks, clusters, and extreme values).

b. Use graphical representations of real-world data to describe the context from which they were collected.

[MA2019] (6) 23 : 23. Calculate, interpret, and compare measures of center (mean, median, mode) and variability (range and interquartile range) in real-world data sets.

a. Determine which measure of center best represents a real-world data set.

b. Interpret the measures of center and variability in the context of a problem.

[MA2019] REG-7 (7) 10 : 10. Examine a sample of a population to generalize information about the population.

a. Differentiate between a sample and a population.

b. Compare sampling techniques to determine whether a sample is random and thus representative of a population, explaining that random sampling tends to produce representative samples and support valid inferences.

c. Determine whether conclusions and generalizations can be made about a population based on a sample.

d. Use data from a random sample to draw inferences about a population with an unknown characteristic of interest, generating multiple samples to gauge variation and making predictions or conclusions about the population.

e. Informally explain situations in which statistical bias may exist.

[MA2015] (7) 18 : 18 ) 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. [7-SP2]

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.

[DLIT] (6) 5 :

R5) Locate and curate information from digital sources to answer research questions.

[DLIT] (6) 6 :

R6) Produce, review, and revise authentic artifacts that include multimedia using appropriate digital tools.

[DLIT] (6) 29 :

23) Discuss how digital devices may be used to collect, analyze, and present information.

[DLIT] (7) 6 :

R6) Produce, review, and revise authentic artifacts that include multimedia using appropriate digital tools.

[DLIT] (7) 22 :

16) Construct content designed for specific audiences through an appropriate medium.

Examples: Design a multi-media children's e-book with an appropriate readability level.

[DLIT] (7) 29 :

23) Demonstrate the use of a variety of digital devices individually and collaboratively to collect, analyze, and present information for content-related problems.

Infogram allows you to easily take data and create infographics. Use charts as well as pictures to display data into an easy to read and understand and attractive digital poster that can be displayed alone or embedded into a website.

View Standards
**Standard(s): **
[MA2015] (7) 18 :

[MA2015] PRE (9-12) 45 :

[MA2015] PRE (9-12) 46 :

[MA2015] PRE (9-12) 48 :

[MA2015] PRE (9-12) 49 :

[MA2019] REG-7 (7) 10 :

18 ) 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. [7-SP2]

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.

[MA2015] PRE (9-12) 45 :

45 ) Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation. [S-IC2]

Example: A model says a spinning coin falls heads up with probability 0.5. Would a result of 5 tails in a row cause you to question the model'

[MA2015] PRE (9-12) 46 :

46 ) Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each. [S-IC3]

[MA2015] PRE (9-12) 48 :

48 ) Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant. [S-IC5]

[MA2015] PRE (9-12) 49 :

49 ) Evaluate reports based on data. [S-IC6]

[MA2019] REG-7 (7) 10 :

10. Examine a sample of a population to generalize information about the population.

a. Differentiate between a sample and a population.

b. Compare sampling techniques to determine whether a sample is random and thus representative of a population, explaining that random sampling tends to produce representative samples and support valid inferences.

c. Determine whether conclusions and generalizations can be made about a population based on a sample.

d. Use data from a random sample to draw inferences about a population with an unknown characteristic of interest, generating multiple samples to gauge variation and making predictions or conclusions about the population.

e. Informally explain situations in which statistical bias may exist.

[MA2019] REG-7 (7) 12 : 12. Make informal comparative inferences about two populations using measures of center and variability and/or mean absolute deviation in context.

Statistics and sampling are important for human performance experiments. Students will learn several sampling types including census, random, stratified random, and convenience. Examples of real-life sampling and experimental design are also shown.

*Note: This video is available in both English and Spanish audio, along with corresponding closed captions.*

View Standards
**Standard(s): **
[MA2015] (7) 18 :

[MA2019] REG-7 (7) 10 :

18 ) 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. [7-SP2]

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.

[MA2019] REG-7 (7) 10 :

10. Examine a sample of a population to generalize information about the population.

a. Differentiate between a sample and a population.

b. Compare sampling techniques to determine whether a sample is random and thus representative of a population, explaining that random sampling tends to produce representative samples and support valid inferences.

c. Determine whether conclusions and generalizations can be made about a population based on a sample.

d. Use data from a random sample to draw inferences about a population with an unknown characteristic of interest, generating multiple samples to gauge variation and making predictions or conclusions about the population.

e. Informally explain situations in which statistical bias may exist.

Learn how the CyberSquad uses sampling and data analysis to help solve a city's trash problem in this interactive from WNET. In the accompanying classroom activity, students watch a series of video clips in which the CyberSquad works to get rid of a mountain of trash by reducing, reusing, and recycling. Students use sampling, multiplication, and fractions to help determine the amount of trash for each method of removal and then complete a sampling and data analysis activity of their own design. This resource is part of the Math at the Core: Middle School Collection.

[MA2019] REG-7 (7) 10 :

10. Examine a sample of a population to generalize information about the population.

a. Differentiate between a sample and a population.

e. Informally explain situations in which statistical bias may exist.

Gather random samples and use them to make inferences about the percentage of blue candies in a jar in this interactive from MPT. In the accompanying classroom activity, students use interactive and then use random sampling to explore a question involving hands-on materials in the classroom. They compare results from different samples and then make appropriate inferences. To get the most from the lesson, students should be comfortable expressing a fraction as a percentage and be familiar with the notion of a random sample. For a longer self-paced student tutorial using this media, see "Simple Random Sampling" on *Thinkport* from Maryland Public Television.

[MA2019] REG-7 (7) 10 :

10. Examine a sample of a population to generalize information about the population.

a. Differentiate between a sample and a population.

e. Informally explain situations in which statistical bias may exist.

In Module 5, Topics C and D, students focus on using random sampling to draw informal inferences about a population (7.SP.A.1, 7.SP.A.2). In Topic C, they investigate sampling from a population (7.SP.A.2). They learn to estimate a population means using numerical data from a random sample (7.SP.A.2). They also learn how to estimate a population proportion using categorical data from a random sample.