10 Math.7.SP.1 7.SP.A.1 7.PAR.4.10 7.SP.1 7.SP.1 7.SP.1 Math.7.SP.2 7.SP.A.2 7.PAR.4.12 7.SP.2 7.SP.2 7.SP.A.2 11 Math.7.SP.3 7.SP.B.3 7.SP.B.3 7.SP.B.3 7.SP.3 7.SP.3 7.SP.3 7.SP.3 7.SP.B.3 12 Math.7.SP.4 7.SP.B.4 7.PR.6.6 7.SP.4 7.SP.4 7.SP.4 7.SP.B.4 7.SP.B.4 CC.2.4.7.B.1 M07.D-S.1.1.1 M07.D-S.1.1.2 CC.2.4.7.B.2 M07.D-S.2.1.1 7.PAR.4.10 7.PAR.4.11 7.PAR.4.12 7.SP.3 7.SP.4 7.SP.5 7.SP.6

Statistics 7th Grade

Alabama Course of Study Standards: 10
Examine a sample of a population to generalize information about the population. Differentiate between a sample and a population. 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. Determine whether conclusions and generalizations can be made about a population based on a sample. 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. Informally explain situations in which statistical bias may exist.
Common Core State Standards: Math.7.SP.1 or 7.SP.A.1
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.
Georgia Standards of Excellence (GSE): 7.PAR.4.10
Predict characteristics of a population by examining the characteristics of a representative sample. Recognize the potential limitations and scope of the sample to the population.
North Carolina - Standard Course of Study: 7.SP.1
Understand that statistics can be used to gain information about a population by: Recognizing that generalizations about a population from a sample are valid only if the sample is representative of that population. Using random sampling to produce representative samples to support valid inferences.
New York State Next Generation Learning Standards: 7.SP.1
Construct and interpret box-plots, find the interquartile range, and determine if a data point is an outlier. Note: Students in grade 7 are not expected to construct box-plots that include outliers in the data, but students are expected to interpret box-plots that may contain outliers.
Ohio's Learning Standards: 7.SP.1
Understand that statistics can be used to gain information about a population by examining a sample of the population. Differentiate between a sample and a population. Understand that conclusions and generalizations about a population are valid only if the sample is representative of that population. Develop an informal understanding of bias.
Common Core State Standards: Math.7.SP.2 or 7.SP.A.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.
Georgia Standards of Excellence (GSE): 7.PAR.4.12
Use data from repeated random samples to evaluate how much a sample mean is expected to vary from a population mean. Simulate multiple samples of the same size.
North Carolina - Standard Course of Study: 7.SP.2
Generate multiple random samples (or simulated samples) of the same size to gauge the variation in estimates or predictions, and use this data to draw inferences about a population with an unknown characteristic of interest.
Ohio's Learning Standards: 7.SP.2
Broaden 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 do the heights of seventh graders compare to the heights of eighth graders?”(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 and make generalizations from the data based on the original question. (GAISE Model, step 4)
Wisconsin Academic Standards: 7.SP.A.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.
Alabama Course of Study Standards: 11
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.
Common Core State Standards: Math.7.SP.3 or 7.SP.B.3
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.
Louisiana Academic Standards: 7.SP.B.3
Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities using 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.
Massachusetts Curriculum Frameworks: 7.SP.B.3
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 and both distributions have similar variability (mean absolute deviation) of about 5 cm. The difference between the mean heights of the two teams (10 cm) is about twice the variability (5 cm) on either team. On a dot plot, the separation between the two distributions of heights is noticeable.
Mississippi College- and Career-Readiness Standards: 7.SP.3
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 on either team; on a dot plot, the separation between the two distributions of heights is noticeable.
North Carolina - Standard Course of Study: 7.SP.3
Recognize the role of variability when comparing two populations. Calculate the measure of variability of a data set and understand that it describes how the values of the data set vary with a single number. Understand the mean absolute deviation of a data set is a measure of variability that describes the average distance that points within a data set are from the mean of the data set. Understand that the range describes the spread of the entire data set. Understand that the interquartile range describes the spread of the middle 50% of the data. Informally assess the difference between two data sets by examining the overlap and separation between the graphical representations of two data sets.
New York State Next Generation Learning Standards: 7.SP.3
Informally assess the degree of visual overlap of two quantitative data distributions.
Ohio's Learning Standards: 7.SP.3
Describe and analyze distributions. Summarize quantitative data sets in relation to their context by using mean absolute deviation (MAD), interpreting mean as a balance point. . Informally assess the degree of visual overlap of two numerical data distributions with roughly equal 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 (line plot), the separation between the two distributions of heights is noticeable.
Wisconsin Academic Standards: 7.SP.B.3
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.
Alabama Course of Study Standards: 12
Make informal comparative inferences about two populations using measures of center and variability and/or mean absolute deviation in context.
Common Core State Standards: Math.7.SP.4 or 7.SP.B.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.
Georgia Standards of Excellence (GSE): 7.PR.6.6
Use appropriate graphical displays and numerical summaries from data distributions with categorical or quantitative (numerical) variables as probability models to draw informal inferences about two samples or populations.
Mississippi College- and Career-Readiness Standards: 7.SP.4
Use measures of center and measures of variability (i.e. inter-quartile range) 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.
North Carolina - Standard Course of Study: 7.SP.4
Use measures of center and measures of variability for numerical data from random samples to draw comparative inferences about two populations.
New York State Next Generation Learning Standards: 7.SP.4
Use measures of center and measures of variability for quantitative data from random samples or populations to draw informal comparative inferences about the populations. Note: Measures of center are mean, median, and mode. The measures of variation include range and the interquartile range.
Tennessee Academic Standards: 7.SP.B.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 7^th science book are generally longer than the words in a chapter of a 4^th science book.
Wisconsin Academic Standards: 7.SP.B.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.
Pennsylvania Core Standards: CC.2.4.7.B.1
Draw inferences about populations based on random sampling concepts.
Pennsylvania Core Standards: M07.D-S.1.1.1
Determine whether a sample is a random sample given a real-world situation.
Pennsylvania Core Standards: M07.D-S.1.1.2
Use data from a random sample to draw inferences about a population with an unknown characteristic of interest
Pennsylvania Core Standards: CC.2.4.7.B.2
Draw informal comparative inferences about two populations.
Pennsylvania Core Standards: M07.D-S.2.1.1
Compare two numerical data distributions using measures of center and variability.
Georgia Standards of Excellence (GSE): 7.PAR.4.10
Predict characteristics of a population by examining the characteristics of a representative sample. Recognize the potential limitations and scope of the sample to the population.
Georgia Standards of Excellence (GSE): 7.PAR.4.11
Analyze sampling methods and conclude that random sampling produces and supports valid inferences.
Georgia Standards of Excellence (GSE): 7.PAR.4.12
Use data from repeated random samples to evaluate how much a sample mean is expected to vary from a population mean. Simulate multiple samples of the same size.
Arkansas Academic Standards: 7.SP.3
Graph two numerical data sets and compare their variability. Variability includes: range, interquartile range, or mean absolute deviation
Arkansas Academic Standards: 7.SP.4
Select an appropriate measure(s) of center or variability and draw valid comparative inferences for two data sets.
Arkansas Academic Standards: 7.SP.5
Distinguish between a random and non-random sample.
Arkansas Academic Standards: 7.SP.6
Use a random sampling of a population to draw valid inferences and generalizations of populations.

Statistics

Alabama Course of Study Standards: 10

Common Core State Standards: Math.7.SP.1 or 7.SP.A.1

Georgia Standards of Excellence (GSE): 7.PAR.4.10

Predict characteristics of a population by examining the characteristics of a representative sample. Recognize the potential limitations and scope of the sample to the population.

North Carolina - Standard Course of Study: 7.SP.1

Understand that statistics can be used to gain information about a population by:Recognizing that generalizations about a population from a sample are valid only if the sample is representative of that population.Using random sampling to produce representative samples to support valid inferences.

New York State Next Generation Learning Standards: 7.SP.1

Construct and interpret box-plots, find the interquartile range, and determine if a data point is an outlier.Note: Students in grade 7 are not expected to construct box-plots that include outliers in the data, but students are expected to interpret box-plots that may contain outliers.

Ohio's Learning Standards: 7.SP.1

Common Core State Standards: Math.7.SP.2 or 7.SP.A.2

Georgia Standards of Excellence (GSE): 7.PAR.4.12

Use data from repeated random samples to evaluate how much a sample mean is expected to vary from a population mean. Simulate multiple samples of the same size.

North Carolina - Standard Course of Study: 7.SP.2

Generate multiple random samples (or simulated samples) of the same size to gauge the variation in estimates or predictions, and use this data to draw inferences about a population with an unknown characteristic of interest.

Ohio's Learning Standards: 7.SP.2

Wisconsin Academic Standards: 7.SP.A.2

Alabama Course of Study Standards: 11

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.

Common Core State Standards: Math.7.SP.3 or 7.SP.B.3

Louisiana Academic Standards: 7.SP.B.3

Massachusetts Curriculum Frameworks: 7.SP.B.3

Mississippi College- and Career-Readiness Standards: 7.SP.3

North Carolina - Standard Course of Study: 7.SP.3

New York State Next Generation Learning Standards: 7.SP.3

Informally assess the degree of visual overlap of two quantitative data distributions.

Ohio's Learning Standards: 7.SP.3

Wisconsin Academic Standards: 7.SP.B.3

Alabama Course of Study Standards: 12

Make informal comparative inferences about two populations using measures of center and variability and/or mean absolute deviation in context.

Common Core State Standards: Math.7.SP.4 or 7.SP.B.4

Georgia Standards of Excellence (GSE): 7.PR.6.6

Use appropriate graphical displays and numerical summaries from data distributions with categorical or quantitative (numerical) variables as probability models to draw informal inferences about two samples or populations.

Mississippi College- and Career-Readiness Standards: 7.SP.4

North Carolina - Standard Course of Study: 7.SP.4

Use measures of center and measures of variability for numerical data from random samples to draw comparative inferences about two populations.

New York State Next Generation Learning Standards: 7.SP.4

Use measures of center and measures of variability for quantitative data from random samples or populations to draw informal comparative inferences about the populations.Note: Measures of center are mean, median, and mode. The measures of variation include range and the interquartile range.

Tennessee Academic Standards: 7.SP.B.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 7th science book are generally longer than the words in a chapter of a 4th science book.

Wisconsin Academic Standards: 7.SP.B.4

Pennsylvania Core Standards: CC.2.4.7.B.1

Draw inferences about populations based on random sampling concepts.

Pennsylvania Core Standards: M07.D-S.1.1.1

Determine whether a sample is a random sample given a real-world situation.

Pennsylvania Core Standards: M07.D-S.1.1.2

Use data from a random sample to draw inferences about a population with an unknown characteristic of interest

Pennsylvania Core Standards: CC.2.4.7.B.2

Draw informal comparative inferences about two populations.

Pennsylvania Core Standards: M07.D-S.2.1.1

Compare two numerical data distributions using measures of center and variability.

Georgia Standards of Excellence (GSE): 7.PAR.4.10

Predict characteristics of a population by examining the characteristics of a representative sample. Recognize the potential limitations and scope of the sample to the population.

Georgia Standards of Excellence (GSE): 7.PAR.4.11

Analyze sampling methods and conclude that random sampling produces and supports valid inferences.

Georgia Standards of Excellence (GSE): 7.PAR.4.12

Use data from repeated random samples to evaluate how much a sample mean is expected to vary from a population mean. Simulate multiple samples of the same size.

Arkansas Academic Standards: 7.SP.3

Graph two numerical data sets and compare their variability.Variability includes: range, interquartile range, or mean absolute deviation

Arkansas Academic Standards: 7.SP.4

Select an appropriate measure(s) of center or variability and draw valid comparative inferences for two data sets.

Arkansas Academic Standards: 7.SP.5

Distinguish between a random and non-random sample.

Arkansas Academic Standards: 7.SP.6

Use a random sampling of a population to draw valid inferences and generalizations of populations.

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Understand that statistics can be used to gain information about a population by:
Recognizing that generalizations about a population from a sample are valid only if the sample is representative of that population.
Using random sampling to produce representative samples to support valid inferences.

Construct and interpret box-plots, find the interquartile range, and determine if a data point is an outlier.
Note: Students in grade 7 are not expected to construct box-plots that include outliers in the data, but students are expected to interpret box-plots that may contain outliers.

Use measures of center and measures of variability for quantitative data from random samples or populations to draw informal comparative inferences about the populations.
Note: Measures of center are mean, median, and mode. The measures of variation include range and the interquartile range.

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 7^th science book are generally longer than the words in a chapter of a 4^th science book.

Graph two numerical data sets and compare their variability.
Variability includes: range, interquartile range, or mean absolute deviation