Data Displays & Analysis
6th Grade


Alabama Course of Study Standards:
22

Write examples and nonexamples of statistical questions, explaining that a statistical question anticipates
variability in the data related to the question 
Arkansas Academic Standards:
6.SP.A.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.
Note: Statistics is also the name for the science of collecting, analyzing and interpreting data. Data are the numbers produced in response to a statistical question and are frequently collected from surveys or other sources (i.e. documents). 
Arizona Academic Standards:
6.SP.A.1

Recognize a statistical question as one that anticipates variability in the data related to the question and accounts for variability 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. 
Common Core State Standards:
Math.6.SP.1 or 6.SP.A.1
Florida  Benchmarks for Excellent Student Thinking:
MAFS.6.SP.1.1

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. 
North Carolina  Standard Course of Study:
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. 
New York State Next Generation Learning Standards:
6.SP.1

 Recognize that a statistical question is one that anticipates variability in the data related to the question and accounts for it in the answers.
e.g., "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.  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.
Note: Students need to understand that data are generated with respect to particular contexts or situations and can be used to answer questions about those contexts or situations.  Understand that the method and sample size used to collect data for a particular question is intended to reduce the difference between a population and a sample taken from the population so valid inferences can be drawn about the population. Generate multiple samples (or simulated samples) of the same size to recognize the variation in estimates or predictions.
Note: Examples of acceptable methods to obtain a representative sample from a population include, but are not limited to, a simple random sample for a given population or a systematic random sample for an unknown population. Examples of unacceptable methods of sampling include, but are not limited to, online polls and convenience sampling because they introduce bias and are not representative of the population.

Ohio's Learning Standards:
6.SP.1

Develop statistical reasoning by using the GAISE model: Formulate Questions: Recognize and formulate a statistical question as one that anticipates variability and can be answered with quantitative data. 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 of the variability in students’ ages. (GAISE Model, step 1)
 Collect Data: Design and use a plan to collect appropriate data to answer a statistical question. (GAISE Model, step 2)
 Analyze Data: Select appropriate graphical methods and numerical measures to analyze data by displaying variability within a group, comparing individual to individual, and comparing individual to group. (GAISE Model, step 3)
 Interpret Results: Draw logical conclusions from the data based on the original question. (GAISE Model, step 4)

Tennessee Academic Standards:
6.SP.A.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. 
Wisconsin Academic Standards:
6.SP.A.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. 
Arkansas Academic Standards:
6.SP.A.2

Determine center, spread, and overall shape from a set of data 
Arizona Academic Standards:
6.SP.A.2

Understand that a set of data collected to answer a statistical question has a distribution whose general characteristics can be described by its center, spread, and overall shape. 
Common Core State Standards:
Math.6.SP.2 or 6.SP.A.2
North Carolina  Standard Course of Study:
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. 
Georgia Standards of Excellence (GSE):
6.NR.2.3

Interpret numerical data to answer a statistical investigative question created. Describe the distribution of a quantitative (numerical) variable collected, including its center, variability, and overall shape. 
New York State Next Generation Learning Standards:
6.SP.2

Understand that a set of quantitative data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape. Notes:  Students need to determine and justify the most appropriate graph to display a given set of data (histogram or dot plot).
 Students extend their knowledge of symmetric shapes, to describe data displayed in dot plots and histograms in terms of symmetry. They identify clusters, peaks and gaps, recognizing common shapes and patterns in these displays of data distributions, and ask why a distribution takes on a particular shape for the context of the variable being considered.

Tennessee Academic Standards:
6.SP.A.2

Understand that a set of data collected to answer a statistical question has a distribution which can be described by its center (mean, median, mode),
spread (range), and overall shape. 
Alabama Course of Study Standards:
23

Calculate, interpret, and compare measures of center (mean, median, mode) and variability (range and interquartile range) in realworld data sets. Determine which measure of center best represents a realworld data set.
 Interpret the measures of center and variability in the context of a problem.

Arkansas Academic Standards:
6.SP.A.3

Recognize that a measure of center for a numerical data set summarizes all of its values with a single number (mean, median, mode), while a measure of variation (interquartile range, mean absolute deviation) describes how its values vary with a single number Example: If the mean height of the students in the class is 48” are there any students in the class taller than 48”? 
Arizona Academic Standards:
6.SP.A.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 uses a single number to describe the spread of the data set. 
Common Core State Standards:
Math.6.SP.3 or 6.SP.A.3
Tennessee Academic Standards:
6.SP.A.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. 
Georgia Standards of Excellence (GSE):
6.NR.2.4

Design simple experiments and collect data. Use data gathered from realistic scenarios and simulations to determine quantitative measures of center (median and/or mean) and variability (interquartile range and range). Use these quantities to draw conclusions about the data, compare different numerical data sets, and make predictions 
North Carolina  Standard Course of Study:
6.SP.3

Understand that both a measure of center and a description of variability should be considered when describing a numerical data set. Determine the measure of center of a data set and understand that it is a single number that summarizes all the values of that data set.
 Understand that a mean is a measure of center that represents a balance point or fair share of a data set and can be influenced by the presence of extreme values within the data set.
 Understand the median as a measure of center that is the numerical middle of an ordered data set.
 Understand that describing the variability of a data set is needed to distinguish between data sets in the same scale, by comparing graphical representations of different data sets in the same scale that have similar measures of center, but different spreads.

New York State Next Generation Learning Standards:
6.SP.3

Recognize that a measure of center for a quantitative 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.Note: Measures of center are mean, median, and mode. The measure of variation is the range. 
Arkansas Academic Standards:
6.SP.B.4

Display numerical data in plots on a number line, including dot plots, histograms, and box plots 
Arizona Academic Standards:
6.SP.B.4

Display and interpret numerical data by creating plots on a number line including histograms, dot plots, and box plots. 
Common Core State Standards:
Math.6.SP.4 or 6.SP.B.4

Display numerical data in plots on a number line, including dot plots, histograms, and box plots. 
Georgia Standards of Excellence (GSE):
6.NR.2.5

Relate the choice of measures of center and variability to the shape of the data distribution and the context in which the data were gathered. 
North Carolina  Standard Course of Study:
6.SP.4

Display numerical data in plots on a number line. Use dot plots, histograms, and box plots to represent data.
 Compare the attributes of different representations of the same data.

New York State Next Generation Learning Standards:
6.SP.4

Display quantitative data in plots on a number line, including dot plots, and histograms. 
Ohio's Learning Standards:
6.SP.4

Display numerical data in plots on a number line, including dot plots (line plots), histograms, and box plots. (GAISE Model, step 3) 
Tennessee Academic Standards:
6.SP.B.4

Display a single set of numerical data using dot plots (line plots), box plots, pie charts and stem plots. 
Arkansas Academic Standards:
6.SP.B.5.A

Reporting the number of observations 
Arizona Academic Standards:
6.SP.B.5a
Common Core State Standards:
6.SP.B.5.A
Kentucky Academic Standards (KAS):
6.SP.5.a
Mississippi College and CareerReadiness Standards:
6.SP.5a

Reporting the number of observations. 
Georgia Standards of Excellence (GSE):
6.NR.2.6

Describe the impact that inserting or deleting a data point has on the mean and the median of a data set. Create data displays using a dot plot or box plot to examine this impact. 
North Carolina  Standard Course of Study:
6.SP.5.a

Describe the collected data by: Reporting the number of observations in dot plots and histograms.
 Communicating the nature of the attribute under investigation, how it was measured, and the units of measurement.

New York State Next Generation Learning Standards:
6.SP.5.a

Report the number of observations. 
Arkansas Academic Standards:
6.SP.B.5.B

Describing the nature of the attribute under investigation, including how it was measured and its units of measurement 
Arizona Academic Standards:
6.SP.B.5b

Describing the nature of the attribute under investigation including how it was measured and its units of measurement. 
Common Core State Standards:
6.SP.B.5.B
Kentucky Academic Standards (KAS):
6.SP.5.b
Mississippi College and CareerReadiness Standards:
6.SP.5b

Describing the nature of the attribute under investigation, including how it was measured and its units of measurement. 
North Carolina  Standard Course of Study:
6.SP.5.b

Analyze center and variability by: Giving quantitative measures of center, describing variability, and any overall pattern, and noting any striking deviations.
 Justifying the appropriate choice of measures of center using the shape of the data distribution.

New York State Next Generation Learning Standards:
6.SP.5.b

Describe the nature of the attribute under investigation, including how it was measured and its units of measurement. 
Alabama Course of Study Standards:
24

Represent numerical data graphically, using dot plots, line plots, histograms, stem and leaf plots, and box plots. 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).
 Use graphical representations of realworld data to describe the context from which they were collected.

Arkansas Academic Standards:
6.SP.B.5.C

 Calculate quantitative measures of center (including but not limited to median and mean) and variability (including but not limited to interquartile range and mean absolute deviation)
 Use the calculations to describe any overall pattern and any striking deviations (outliers) from the overall pattern with reference to the context in which the data were gathered
Note: Instructional focus should be on summarizing and describing data distributions.

Arizona Academic Standards:
6.SP.B.5c
Common Core State Standards:
6.SP.B.5.C
Kentucky Academic Standards (KAS):
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. 
Georgia Standards of Excellence (GSE):
6.NR.2.1

Describe and interpret the center of the distribution by the equal share value (mean). 
Massachusetts Curriculum Frameworks:
6.SP.B.5.c

Giving quantitative measures of center (median, and/or mean) and variability (range and/or interquartile range), 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. 
Mississippi College and CareerReadiness Standards:
6.SP.5c

Giving quantitative measures of center (median and/or mean) and variability (interquartile range), 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. 
New York State Next Generation Learning Standards:
6.SP.5.c

Calculate range and measures of center, as well as describe any overall pattern and any striking deviations from the overall pattern with reference to the context in which the data were gathered. Note: Measures of center are mean, median, and mode. The measure of variation is the range. The role of outliers should be discussed, but no formula is required. 
Ohio's Learning Standards:
6.SP.5.c

Find the quantitative measures of center (median and/or mean) for a numerical data set and recognize that this value summarizes the data set with a single number. Interpret mean as an equal or fair share. Find measures of variability (range and interquartile range) as well as informally describe the shape and the presence of clusters, gaps, peaks, and outliers in a distribution. 
Tennessee Academic Standards:
6.SP.B.5.c

Give quantitative measures of center (median and/or mean) and variability (range) as well as describing any overall pattern with reference to the context in which the data were gathered. 
Wisconsin Academic Standards:
6.SP.B.5.c

Describing any overall pattern and any striking deviations from the overall pattern with reference to the context in which the data were gathered and the quantitative measures of center (median and/or mean) and variability (interquartile range and/or mean absolute deviation) were given. 
Arkansas Academic Standards:
6.SP.B.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. For example, demonstrate in the case where there are outliers in the data median would be a better measure of center than the mean. 
Arizona Academic Standards:
6.SP.B.5d
Common Core State Standards:
6.SP.B.5.D
Kentucky Academic Standards (KAS):
6.SP.5.d
Mississippi College and CareerReadiness Standards:
6.SP.5d

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. 
Georgia Standards of Excellence (GSE):
6.NR.2.2

Summarize categorical and quantitative (numerical) data sets in relation to the context: display the distributions of quantitative (numerical) data in plots on a number line, including dot plots, histograms, and box plots and display the distribution of categorical data using bar graphs. 
New York State Next Generation Learning Standards:
6.SP.5.d

Relate the range and the choice of measures of center to the shape of the data distribution and the context in which the data were gathered. Note: Measures of center are mean, median, and mode. The measure of variation is the range. 
Ohio's Learning Standards:
6.SP.5.d

Choose the measures of center and variability, based on the shape of the data distribution and the context in which the data were gathered. 
Tennessee Academic Standards:
6.SP.B.5.d

Relate the choice of measures of center to the shape of the data distribution and the context in which the data were gathered. 
Pennsylvania Core Standards:
CC.2.4.6.B.1

Demonstrate an understanding of statistical variability by displaying, analyzing, and summarizing distributions. 
Pennsylvania Core Standards:
M06.DS.1.1.1

Display numerical data in plots on a number line, including line plots, histograms, and boxand whisker plots. 
Pennsylvania Core Standards:
M06.DS.1.1.2

Determine quantitative measures of center (e.g., median, mean, mode) and variability (e.g., range, interquartile range, mean absolute deviation). 
Pennsylvania Core Standards:
M06.DS.1.1.3

Describe any overall pattern and any deviations from the overall pattern with reference to the context in which the data were gathered 
Pennsylvania Core Standards:
M06.DS.1.1.4

Relate the choice of measures of center and variability to the shape of the data distribution and the context in which the data were gathered. 
Georgia Standards of Excellence (GSE):
6.NR.2.1

Describe and interpret the
center of the distribution by
the equal share value
(mean). 
Georgia Standards of Excellence (GSE):
6.NR.2.2

Summarize categorical and
quantitative (numerical) data
sets in relation to the
context: display the
distributions of quantitative
(numerical) data in plots on a
number line, including dot
plots, histograms, and box
plots and display the
distribution of categorical
data using bar graphs. 
Georgia Standards of Excellence (GSE):
6.NR.2.3

Interpret numerical data to
answer a statistical
investigative question
created. Describe the
distribution of a quantitative
(numerical) variable
collected, including its
center, variability, and
overall shape. 
Georgia Standards of Excellence (GSE):
6.NR.2.4

Design simple experiments
and collect data. Use data
gathered from realistic
scenarios and simulations to
determine quantitative
measures of center (median
and/or mean) and variability
(interquartile range and
range). Use these quantities
to draw conclusions about
the data, compare different
numerical data sets, and
make predictions. 
Georgia Standards of Excellence (GSE):
6.NR.2.5

Relate the choice of
measures of center and
variability to the shape of the
data distribution and the
context in which the data
were gathered. 
Georgia Standards of Excellence (GSE):
6.NR.2.6

Describe the impact that
inserting or deleting a data
point has on the mean and
the median of a data set.
Create data displays using a dot plot or box plot to
examine this impact. 
