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Browse Standards

View all PreK-12 NYS Learning Standards in a dropdown list format.
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  • Standard Area - TECH: Learning Standards for Technology
    (see MST standards under Previous Standard Versions)
            • Standard - 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.
              Emphasis: AEP
            • Standard - 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.
              Emphasis: AP
            • Standard - 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
              Emphasis: AEP
            • Standard - 6.SP.4:
              Display numerical data in plots on a number line, including dot plots, histograms, and box plots.
              Emphasis: AP
            • Emphasis: AP
              • Component - 6.SP.5.a:
                Reporting the number of observations.
              • Component - 6.SP.5.b:
                Describing the nature of the attribute under investigation, including how it was measured and its units of measurement.
              • Component - 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.
              • Component - 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.
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