Embedded Files
In 7th grade, students learn to construct, solve and interpret proportions and two step equations using rational numbers in order to apply and represent these skills in real world situations including statistics, percent, geometry and probability.
Essential Standard Claim 1 Proficiency Scales (Probability covered in Unit 5)
Can be used to inform standard-based grading
Applicable Pre-assessments
If given prior, then you only need to view a portion of the results.
MAP (part of the district assessment plan)
MAP (part of the district assessment plan)
Learning Continuum by Topic: See MAP Report
Learning Continuum by Standard: See MAP Report
MDTP Preparedness for 7th Grade (optional)
MDTP Preparedness for 7th Grade (optional)
DAST: #14, #20, #38 & FRAC: #4, #23, #28
MDTP Preparedness for 8th Grade (optional)
MDTP Preparedness for 8th Grade (optional)
DAPS: #12, #36
Formative and/or Summative Assessments,
Reengagement & Reassessment
Questions 2, 3, 5, 6, 7, 8, 13. Skip probability questions or use them as a pre-assessment for Unit 5.
Consider using this assessment throughout instruction in an unstandardized administation - whole class, small group or select items individually.
Reengagement One Pager See document.
Reengagement Template (One Slide). See slides.
Need to Do a Class Review for your Next Big Summative Assessment? Instead of wasting time and boring students with a comprehensive review, provide those notes and try something different instead. Rather than reviewing first and then doing a practice test, consider giving the practice test first and then reengaging around the results for a more targeted and engaging review.
Cumulative Assessment #1: Site / teacher created. Please submit to the design team, email dmattoon@hemetusd.org
Cumulative Assessment #1: Site / teacher created. Please submit to the design team, email dmattoon@hemetusd.org
To save time in this relatively short unit, consider giving the Stats & Probability FIAB instead of any quizzes, chapter tests or site-created cumulative assessment.
Reengagement One Pager See document.
Reengagement Template (One Slide). See slides.
Need to Do a Class Review for your Next Big Summative Assessment? Instead of wasting time and boring students with a comprehensive review, provide those notes and try something different instead. Rather than reviewing first and then doing a practice test, consider giving the practice test first and then reengaging around the results for a more targeted and engaging review.
Cumulative Assessment #2: Site / teacher created. Please submit to the design team, email dmattoon@hemetusd.org
Cumulative Assessment #2: Site / teacher created. Please submit to the design team, email dmattoon@hemetusd.org
To save time in this relatively short unit, consider giving the Stats & Probability FIAB instead of any quizzes, chapter tests or site-created cumulative assessment.
Guidelines for Creating your Own Assesment in Claim 1
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.
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.
7.SP.1 (embedded with 7.SP.2) 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.1 (embedded with 7.SP.2) 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.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.
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.
There are no SBAC Stimulus Guidelines for this standard in the Target H Item Specifications. See the Stimulus Guidelines for 7.SP.3 (embedded) instead.
7.SP.3 (embedded with 7.SP.4) 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.3 (embedded with 7.SP.4) 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.
Embed your assessments into you custom Clarity Calendar! See tab.
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