From a Dataset, Draw a Histogram

From a Dataset, Draw a Dotplot

From a Dataset, Draw Stemplot

From a Dataset, Draw a Frequency Polygon

From a Dataset, Draw an Ogive (Cumulative Frequency Distribution)

Recognizing the Shape of a Histogram

Recognizing the Shape of a Distribution with Clusters

Recognizing the Shape of a Distribution with Gaps

Recognizing the Shape of a Dotplot

Recognizing the Shape of a Stemplot (Stem-and-Leaf)

Recognizing the Shape from a Single Data Set

Recognizing the Shape from a Frequency Table

Recognizing the Shape of a Distribution from Context

Constructing a Histogram by Hand

Finding Mean from a DataSet

Finding Median from a DataSet

Finding Median or Mean from Grouped Data

Finding Median or Mean from a Histogram, Dotplot, or Boxplot

The Resistant Median and Not So Resistant Mean: Outliers and Skewness

Weighted Averages

The Lost Measure of Center: Midrange

Transformation Rules for Center

Which to Choose: Mean or Median?

Strange Ratio: Mean/Median and Shape

Standard Deviation by Definition

Transformation Rules for Spread

Calculating Standard Deviation or IQR from Grouped Data

Finding IQR from a Boxplot

Finding IQR from a Summary Table

The Mechanics and Symbols of Deviation

Finding IQR from a Histogram, Stemplot, or Dotplot

Sx to Max or Min to Inform About Shape

Finding the Count or Likelihood of Values within a Center

Finding a Measure of Spread from a Data Set

Summary Tables and Histograms to Determine Outliers

Find the 5-Number Summary from a Data Set

Outliers from a Summary Table

2 Standard Deviations Away

Percentage of Data Within the 5-Number Summary

Distance Between Quartiles and Shape: Symmetric vs. Skewed

Creating a Boxplot from a Data Set

Width of a Quartile, from a Boxplot

Identify the 5-Number Summary from a Boxplot

Finding Percentiles or Percentages from a Boxplot

Outliers from a Cumulative Table or Graph

Finding Q1 from a Cumulative Table or Graph

Finding M from a Cumulative Table or Graph

Finding Q3 from a Cumulative Table or Graph

Finding IQR from a Cumulative Table or Graph

Interpreting Percentiles

Locating Top or Bottom Percentages of a Cumulative Distribution

Construct a Cumulative Table or Graph

From a Cumulative Graph or Table, Find the Domain of Least or Greatest Change

Finding Percentile Rank from a Dotplot or Stemplot

From a Histogram, Compare Median and Mean due to Shape

Histogram Bins-Pitfalls without the Data

(Max-M)/(M-Min) Ratio for Shape

Transforming a Boxplot

Creating a Boxplot with Data and the 5-Number Summary Split

Finding Proportion Above or Below a Certain Value

Steps in Finding an Outlier

Describing a Distribution

TimeSeries-Shapes of Frequencies

TimeSeries-Unusual Characteristics

TimesSeries-Center of Frequencies

TimeSeries-Volatility

Moving Average for Trend

TimeSeries-Calculate Moving Average

TimeSeries-Frequency Polygon vs. Moving Average

Graphing Mistakes

Pros and Cons of Graphical Displays

Boxplots: Comparative and Groups

Histograms: Back-to-Back, Side-by-Side, Comparative

Frequency Polygons

Comparative Dotplots

Back-to-Back Stemplots

Compare Center Within 1 Group of Boxplots

Compare Spread Within 1 Group of Boxplots

Compare Position Within 1 Group of Boxplots

Compare Multiple Groups of Boxplots

Boxplots-Justify by Center

Boxplots-Justify by Spread

Boxplots-Justify by Outliers or Extreme Values

Compare Boxplots After Transforming One Distribution

Comparing 5-Number Summaries

Compare Dotplots

Dotplots-Justify by Center

Dotplots-Justify by Spread

Compare and Contrast Histograms

Compare and Contrast Histograms and Boxplots

Comparing Back-to-Back Stemplots

Comparing Ogives

Compare 2 Sets of Data

Interpreting Population Pyramids

Comparing Timeplots

Characteristics of Probability Density Functions

Analyze the Illustration of a Density Function

Given or Create a Density Curve, Then Estimate the Standard Deviation

Identifying Contextual Situation that are Approx. Normal

Identify the Parameters of a Normal or Standard Normal Model

Selecting Appx. Normal Frequency Tables or Displays

Interpreting Standardized Values and Their Properties

Empirical Rule and Interval of Data

Empirical Rule to Find Area

Chebyshev's Rule-The Empirical Substitute When We Know NOTHING!

Comparing z-scores or Percentiles for Low Outcomes

Compare z-scores or Percentiles for High Outcomes

Add z-scores to Show Better Overall Performance

Use z-scores or Standard Units to Show if a Value is Unusual or Not

From x, Mean, and Standard Deviation, Find Area to the Left

From x, Mean, and Standard Deviation, Find Area to the Right

From x, Mean, and Standard Deviation, Find Area Between Two x-values

Find Union of 2 Tails

Given z, Use Standard Normal Model to Find Area Under the Curve

Select or use a Correctly Drawn, Labeled, & Shaded Normal Model

From Percentiles, Find z

From z-score, Mean and Standard Deviation, Find x

From Percentile, Mean and Standard Deviation, Find x

From a z-score and Summary Table, Find x

From Percentile, Standard Deviation and x, Find Mean

Given Percentile, Mean, and x, Find Standard Deviation

Comparing the 4- x-axis Scales of the Normal Model

Q1 & Q3 on the Normal Model

System of z-score Equations

Creating and Interpreting Normal Probability Plots