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.

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.

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.