Statistics FlexBook® for Middle School

Statistics FlexBook® for High School

For Middle School

For High School

Levels are CK-12's student achievement levels.

Basic
Students matched to this level have a partial mastery of prerequisite knowledge and skills fundamental for proficient work.

At Grade (Proficient)
Students matched to this level have demonstrated competency over challenging subject matter, including subject matter knowledge, application of such knowledge to real-world situations, and analytical skills appropriate to subject matter.

Advanced
Students matched to this level are ready for material that requires superior performance and mastery.

Sorry, there are no FlexBook® Textbooks for this selection.

- Data Summary and Presentation
- Summary Statistics, Summarizing Univariate Distributions
- Measures of Central Tendency and Dispersion
- Mean
- Ungrouped Data to Find the Mean
- Grouped Data to Find the Mean
- Median
- Median of Large Sets of Data
- Mode
- Measures of Spread/Dispersion
- Range of Spread/Dispersion
- Quartiles
- Five Number Summary
- Types of Data Representation
- Line Graphs
- Broken-Line Graphs
- Line Plots from Frequency Tables
- Line Graphs to Display Data Over Time
- Multiple Line Graphs
- Stem-and-Leaf Plots
- Stem-and-Leaf Plots and Histograms
- Stem and Leaf Plots, Range of a Data Set
- Stem and Leaf Plots, Mean, Median, and Mode
- Pie Charts
- Circle Graphs to Make Bar Graphs
- Interpretation of Circle Graphs
- Circle Graphs to Display Data
- Box-and-Whisker Plots
- Applications of Box-and-Whisker Plots
- Effects On Box-and-Whisker Plots
- Frequency Tables to Organize and Display Data
- Bar Graphs, Frequency Tables, and Histograms
- Frequency Tables and Histograms
- Histograms
- Applications of Histograms
- Frequency Polygons
- Data Display Choices
- Scatter Plots
- Linear Regression Equations
- Scatter Plots and Linear Correlation
- Scatter Plots on the Graphing Calculator
- Displaying by Type of Data
- Displaying Categorical Variables
- Displaying Univariate Data
- Displaying Bivariate Data
- Interpreting Graphical Displays
- Identification of Misleading Statistics
- Double Line Graphs
- Comparison of Dot, Two-Sided Stem, and Parallel Box Plots
- Two-Sided Stem-and-Leaf Plots
- Double Box-and-Whisker Plots
- Bar Graphs
- Double Bar Graphs
- Multiple Bar Graphs

- Interpreting Probability
- Relative Frequency Interpretation
- Simulation of Random Behavior and Probability Distributions
- Theoretical and Experimental Spinners
- Theoretical and Experimental Coin Tosses
- Statistics of a Random Variable
- Variance of a Data Set
- Standard Deviation of a Data Set
- Applications of Variance and Standard Deviation
- Coefficient of Variation
- Combining Independent Random Variables
- Independence versus Dependence
- Independent Events and Sample Spaces
- Dependent Events and Sample Spaces
- Sums and Differences of Random Variables
- Normal Distribution
- Normal Distribution Properties
- Normal Distributions
- Standard Deviation of a Normal Distribution
- Density Curve of the Normal Distribution
- Using Tables of the Normal Distribution
- Applications of Normal Distributions
- Binomial Distributions
- Geometric Distributions
- Sampling Distributions
- Sampling Distribution of a Sample Mean
- Central Limit Theorem
- T-Distribution
- Student's t-Distribution
- F-Distribution

- Confidence Intervals
- Null and Alternative Hypotheses
- p-Values
- One- and Two-Sided Tests of Significance
- Significance Test for a Proportion
- Significance Test for a Mean
- Significance Test for a Difference of Two Means
- Chi-Square Test
- Test of Independence
- Tests of Single Variance
- Contingency Tables
- Testing a Hypothesis for Dependent and Independent Samples
- Anova Tests
- One-Way ANOVA Tests
- Two-Way ANOVA Tests
- Regression and Correlation
- Least-Squares Regression
- Inferences about Regression
- Multiple Regression
- Modeling with Regression
- Non-Parametric Statistics
- Rank Sum Test and Rank Correlation
- Kruskal-Wallis Test and Runs Test

Back to the top of the page ↑

+