Classroom Resource

Central Tendency | Targeted Math Instruction

Subject Area

Mathematics

Grade(s)

9, 10, 11, 12

Overview

One way we analyze data is to look at measures of central tendency—mean, median, and mode. They are the tools to look at the information for the purpose of answering the question, “What is normal?” Understanding the measures of central tendency can help us make important life decisions. For example, averages can help us set goals or plan budgets. At the end of this lesson about central tendency, students will be able to recognize and apply the concepts of mean, median, and mode in real-life problems. 

Mathematics (2019) Grade(s): 09-12 - Geometry with Data Analysis

MA19.GDA.9

Represent the distribution of univariate quantitative data with plots on the real number line, choosing a format (dot plot, histogram, or box plot) most appropriate to the data set, and represent the distribution of bivariate quantitative data with a scatter plot. Extend from simple cases by hand to more complex cases involving large data sets using technology.

Unpacked Content

UP:MA19.GDA.9

Vocabulary

  • Dot plots
  • Histograms
  • Box plots
  • Scatter plots
  • Univariate data
  • Bivariate data

Knowledge

Students know:
  • Techniques for constructing dot plots, histograms, scatter plots and box plots from a set of data.

Skills

Students are able to:
  • Choose from among data display (dot plots, histograms, box plots, scatter plots) to convey significant features of data.
  • Accurately construct dot plots, histograms, and box plots.
  • Accurately construct scatter plots using technology to organize and analyze the data.

Understanding

Students understand that:
  • Sets of data can be organized and displayed in a variety of ways each of which provides unique perspectives of the data set.
  • Data displays help in conceptualizing ideas and in solving problems.
Mathematics (2019) Grade(s): 09-12 - Geometry with Data Analysis

MA19.GDA.10

Use statistics appropriate to the shape of the data distribution to compare and contrast two or more data sets, utilizing the mean and median for center and the interquartile range and standard deviation for variability.

Unpacked Content

UP:MA19.GDA.10

Vocabulary

  • Center
  • Median
  • Mean
  • Spread
  • Interquartile range
  • Standard deviation
  • Absolute mean deviation

Knowledge

Students know:
  • Techniques to calculate the center and spread of data sets.
  • Techniques to calculate the mean absolute deviation and standard deviation.
  • Methods to compare data sets based on measures of center (median, mean) and spread (interquartile range and standard deviation) of the data sets.

Skills

Students are able to:
  • Accurately find the center (median and mean) and spread (interquartile range and standard deviation) of data sets.
  • -Present viable arguments and critique arguments of others from the comparison of the center and spread of multiple data sets.
  • Explain their reasoning on how standard deviation develops from the mean absolute deviation.

Understanding

Students understand that:
  • Multiple data sets can be compared by making observations about the center and spread of the data.
  • The center and spread of multiple data sets are used to justify comparisons of the data.
  • Both the mean and the median are used to calculate the mean absolute and standard deviations
Mathematics (2019) Grade(s): 09-12 - Geometry with Data Analysis

MA19.GDA.11

Interpret differences in shape, center, and spread in the context of data sets, accounting for possible effects of extreme data points (outliers) on mean and standard deviation.

Unpacked Content

UP:MA19.GDA.11

Vocabulary

  • Outliers
  • Center
  • Shape
  • Spread
  • Mean
  • Standard deviation

Knowledge

Students know:

  • Techniques to calculate the center and spread of data sets.
  • Methods to compare attributes (e.g. shape, median, mean, interquartile range, and standard deviation) of the data sets.
  • Methods to identify outliers.

Skills

Students are able to:

  • Accurately identify differences in shape, center, and spread when comparing two or more data sets.
  • Accurately identify outliers for the mean and standard deviation.
  • Explain, with justification, why there are differences in the shape, center, and spread of data sets.

Understanding

Students understand that:

  • Differences in the shape, center, and spread of data sets can result from various causes, including outliers and clustering.
Mathematics (2019) Grade(s): 09-12 - Algebra II with Statistics

MA19.A2.25

From a normal distribution, use technology to find the mean and standard deviation and estimate population percentages by applying the empirical rule.

Unpacked Content

UP:MA19.A2.25

Vocabulary

  • Normal distribution
  • Population Percentages
  • Empirical Rule
  • Normal curve
  • Mean
  • Standard deviation

Knowledge

Students know:
From a normal distribution,
  • Techniques to find the mean and standard deviation of data sets using technology.
  • Techniques to use calculators, spreadsheets, and standard normal distribution tables to estimate areas under the normal curve.

Skills

Students are able to:
  • From a normal distribution, accurately find the mean and standard deviation of data sets using technology.
  • Make reasonable estimates of population percentages from a normal distribution.
  • Read and use normal distribution tables and use calculators and spreadsheets to accurately estimate the areas under a normal curve.

Understanding

Students understand that:
Under appropriate conditions,
  • The mean and standard deviation of a data set can be used to fit the data set to a normal distribution.
  • Population percentages can be estimated by areas under the normal curve using calculators, spreadsheets, and standard normal distribution tables.
Mathematics (2019) Grade(s): 09-12 - Algebra II with Statistics

MA19.A2.26

Describe the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.

Unpacked Content

UP:MA19.A2.26

Vocabulary

  • Sample surveys
  • Experiments
  • Observational studies
  • Randomization

Knowledge

Students know:
  • Key components of sample surveys, experiments, and observational studies.
  • Procedures for selecting random samples.

Skills

Students are able to:
  • Use key characteristics of sample surveys, experiments, and observational studies to select the appropriate technique for a particular statistical investigation.

Understanding

Students understand that:
  • Sample surveys, experiments, and observational studies may be used to make inferences made about the population.
  • Randomization is used to reduce bias in statistical procedures.
Link to Resource
https://aptv.pbslearningmedia.org/resource/ket-targetedmath4/central-tendency/

CR Resource Type

Lesson/Unit Plan

Resource Provider

PBS
Accessibility
License

License Type

Custom

Custom License Type (URL)

https://aptv.pbslearningmedia.org/help/terms-of-use/#.YD-bCNhKiUk

Comments or Notes

This lesson should take approximately 1 hour and 15 minutes to complete, if all components are utilized.

Approved Date

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