Common Core Algebra - Statistics Unit: Describing Data POSTERS

30 Posters! Each 8.5" x 11" in size. Posters are aligned with Common Core's Algebra - Statistics: Describing Data Unit.

Posters Included:

Mean

Median

Mode

Range

Interquartile Range

Outlier

Mean Absolute Deviation

Measures of Center

Measures of Spread

Dot Plot

Histogram

Box Plot

Normal/ Bell Shaped Distribution

Skewed Right/Positive Skew

Skewed Left/ Negative Skew

Uniform

2 Way Frequency Table

Joint Frequency

Marginal Frequency

2 Way Relative Frequency Table

Conditional Relative Frequency

Scatter Plot

Correlation

Correlation Coefficient, r

Causation

Correlation ≠ Causation

Line of Best Fit/ Trend Line/ Regression Line

How to Create a Line of Best Fit

Slope/ Rate of Change

Y-intercept

Common Core Standards:

CCSS.HSS.ID.A.1 Represent data with plots on the real number line (dot plots, histograms, and box plots).

CCSS.HSS.ID.A.2 Use statistics appropriate to the shape of the data distribution to compare center and spread of two or more different data sets.

CCSS.HSS.ID.A.3 Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

CCSS.HSS.ID.B.5 Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.

CCSS.HSS.ID.B.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

CCSS.HSS.ID.B.6c Using given or collected bivariate data, fit a linear function for a scatter plot that suggests a linear association.

CCSS.HSS.ID.C.7 Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

CCSS.HSS.ID.C.8 Compute (using technology) and interpret the correlation coefficient “r” of a linear fit. (For instance, by looking at a scatterplot, students should be able to tell if the correlation coefficient is positive or negative and give a reasonable estimate of the “r” value.) After calculating the line of best fit using technology, students should be able to describe how strong the goodness of fit of the regression is, using “r”.

CCSS.HSS.ID.C.9 Distinguish between correlation and causation.

See similar resources:

Statistics: Representing and Interpreting Data(Box Plots, Histograms, Dot Plots) CARD SORT

Statistics: 2 Way Frequency Tables BINGO GAME

Statistics:Measures of Center and Spread TASK CARDS

Statistics: Scatter Plots and Lines of Best Fit FOLDABLE

Statistics: Math Article (Case Studies of Bad Graphs found in the Media)

Statistics Project: U.S. Home Energy & Tax Themed Analysis of Real-World Data

Statistics: Vocabulary Activities

Statistics: Line of Best Fit MYSTERY ACTIVITY (FREE!)

Statistics: Mystery Picture

This topic is also covered in:

Algebra State Exam Prep: Study Guide w/ Notes and 2 Practice Tests

Algebra Warm-ups/ Bellringers/ Exit Tickets- COMMON CORE ALIGNED

Algebra Curriculum Vocabulary Bundle: Matching Card Sets & Vocabulary Puzzles

Common Core Algebra 1 Full Curriculum POSTERS

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