# Recognize strong trends or other patterns in a time

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Recognize strong trends or other patterns in a time plot D. Measuring Center 1. Find the mean, x-bar, of a set of observations 2. Find the median M of a set of observations 3. Understand that the median is more resistant (less affected by extreme observations) than the mean. Recognize that skewness in a distribution moves the mean away from the median toward the long fall. E. Measuring Spread 1. Find the quartiles Q 1 and Q 3 for a set of data 2. Give the five-number summary and draw a boxplot, assess center, spread, symmetry, and skewness from a boxplot. Determine outliers 3. Using a calculator or software, find the standard deviation, s, for a set of observations 4. Know the basic properties of s: s ≥ 0 always; s = 0 only when all observations are identical; s increases as the spread increases; s has the same units as the original measurements; s is increased by outliers or skewness F. Changing Units of Measurement (Linear Transformation) 1. Determine the effect of a linear transformation on measures of center and spread 2. Describe a change in units of measurement in terms of a linear transformation of the form x new = a + bx G. Comparing Distributions 1. Use side-by-side bar graphs to compare distributions of categorical data 2. Make back-to-back stemplots and side-by-side Boxplots to compare distributions of quantitative variables 3. Write narrative comparisons of the shape, center, spread, and outliers for two or more quantitative distributions

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Chapter 1: Exploring Data Section 1.1: Displaying Distributions with Graphs Knowledge Objectives: Students will: Explain what is meant by exploratory data analysis . Explain what is meant by the distribution of a variable . Differentiate between categorical variables and quantitative variables . Explain what is meant by the mode of a distribution . Explain what is meant by an outlier in a stemplot or histogram. Construction Objectives: Students will be able to: Construct bar graphs and pie charts for a set of categorical data. Construct a stemplot for a set of quantitative data. Construct a back-to-back stemplot to compare two related distributions. Construct a stemplot using split stems . Construct a histogram for a set of quantitative data, and discuss how changing the class width can change the impression of the data given by the histogram Describe the overall pattern of a distribution by its shape, center, and spread . Recognize and identify symmetric and skewed distributions. Construct and interpret an ogive (relative cumulative frequency graph) form a relative frequency table. Construct a time plot for a set of data collected over time. Vocabulary: Back-to-back stemplot – two distributions plotted with a common stem Bar graph – displays the distribution of a categorical variable Bimodal – a distribution whose shape has two peaks (modes) Histogram – breaks range of values into classes and displays their frequencies Frequency – counts of data in a class Frequency table – table of frequencies Modes – major peaks in a distribution
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