Unit 4: Describing Data After 10 long weeks, we have finally finished Unit 3: Linear & Exponential Functions. Now on to Unit 4 which will last 5 weeks.

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Presentation transcript:

Unit 4: Describing Data After 10 long weeks, we have finally finished Unit 3: Linear & Exponential Functions. Now on to Unit 4 which will last 5 weeks. This unit is all about statistics, so let’s begin by getting to know some of the vocabulary of statistics…

Vocabulary: Box-and-Whisker Plot (Box Plot) Center Dot plot First Quartile Histogram Interquartile Range Mean Absolute Deviation Outlier Second Quartile (Q2) Shape Symmetry Number of Peaks Direction of Skew Uniformity Spread Third quartile Trend Association Bivariate data Categorical variables Causation Conditional Relative Frequencies Correlation Coefficient Joint Frequencies Line of best fit Marginal Frequencies Quantitative Variables Residuals Scatter plot Two-frequency table

Learning Target: Students can identify the best way to represent, compare, and interpret sets of data. Standard: MCC9-12.S.ID.1-3, 5-9, SP.5

Box Plot A plot showing the minimum, maximum, first quartile, median, and third quartile of a data set; the middle 50% of the data is indicated by a box. Example:

Box Plot: Pros and Cons Advantages: Shows 5-point summary and outliers Easily compares two or more data sets Handles extremely large data sets easily Disadvantages: Not as visually appealing as other graphs Exact values not retained

Dot Plot A frequency plot that shows the number of times a response occurred in a data set, where each data value is represented by a dot. Example:

Dot Plot: Pros and Cons Advantages: Simple to make Shows each individual data point Disadvantages: Can be time consuming with lots of data points to make Have to count to get exact total. Fractions of units are hard to display.

Histogram A frequency plot that shows the number of times a response or range of responses occurred in a data set. Example:

Histogram: Pros and Cons Advantages: Visually strong Good for determining the shape of the data Disadvantages: Cannot read exact values because data is grouped into categories More difficult to compare two data sets

Histogram vs. Bar Graph Histograms are a great way to show results of continuous data, such as: weight height how much time etc. But if your data is in categories (such as Country or Favorite Movie), then you should use a Bar Graph