Segments in this Video

Methods of Displaying Data... (01:28)

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Graphs and other displays help one to understand data. These include: circle graphs, line graphs, two-way table, scatter plot, bar graphs, and histograms.

Tables and Bar Graphs— Drums (02:48)

A variety of drums are used around the world in various musical genres; the type of drum is an example of an attribute. In this example, graphs and tables can illustrate attribute characteristics, values of variables, and relationships among them. See examples.

Histograms and Line Graphs— Pianos (02:39)

Higher quality craftsmanship includes higher prices. In this example, a histogram illustrates piano sales in different price ranges. A line graph illustrates the sale trends of a specific model over time.

Scatter Plots— MP3s and Albums (03:48)

Some analysts predict a decline of in store album sales with the increase of music purchasing online. A relational pattern occurs when one variable influences another; see a scatter plot.

Central Tendency and Variability (01:48)

Coaches can analyze a player's performance using a variety central tendency measures; learn to calculate earned run average. Three common measures of central tendency are mean, median, and mode.

Mean, Mode, and Median— Babe Ruth (03:45)

Ruth played baseball from 1914-1935. In this example, consider Ruth's yearly number of home runs in his last 10 year of play to determine the mean, median, and mode; plot data on a line plot.

Normal Curve— Height (02:06)

Diversity contributes to the distribution of height among the U.S. population. In this example, consider the distribution of heights in adult males.

Standard Deviation— Bicycle Training (03:36)

In this example, describe and track Lance Armstrong's performance by analyzing data for patterns and relationships in his practice times. Learn the standard deviation formula.

Understanding Correlation (02:12)

Studies show an increase in shark attacks. Is this correlated to the number of beach goers? Correlation does not imply causation but causation does result in correlation.

Correlations and Scatter Plots— Weather (04:19)

Beaches are a popular vacation destination. In this example, use a scatter plot to consider the correlation between weather and the number of beach goers and calculate the correlation coefficient.

Correlation Coefficients— Beach Attendance (02:04)

In this example, a scatter plot shows a correlation between temperature and beach attendance.

Lurking Variables and Causation— Property Value and Construction (02:27)

In this example, consider the price increase of oceanfront properties in relation to the construction rate of new homes. Lurking variables are variables not taken into account during an experiment or observation.

Line-Fitting Methods (02:03)

Samantha Smith collects samples inside a cave system to study the role of bacteria in cave formation. A scatter plot shows the relationship between two types of intestinal bacteria in a lake. Scientists use curve fitting to describe relationships between variables.

Scatter Plots and Lines— Coral Reefs and Warming (02:39)

Aquanauts study coral colonies. In this example, consider the overall rate of change in the average global temperature using curve fitting, a median-fit line, and a least-squares regression line.

Median-Fit Lines— Sea Ice (03:18)

Scientists use climate model experiments to understand the changes in Arctic sea ice. In this example, calculate the median-fit line to understand the rate of reduction.

Least Squares Linear Regression— Sea Turtles (02:25)

All sea turtle species are threatened or endangered. In this example, consider the association of juvenile leatherback turtle size and latitude.

Credits: Discovering Math: Advanced—Statistics and Data Analysis: Part 1 (00:49)

Credits: Discovering Math: Advanced—Statistics and Data Analysis: Part 1

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Discovering Math: Advanced—Statistics and Data Analysis: Part 1

Part of the Series : Discovering Math: Advanced
3-Year Streaming Price: $169.95

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Description

In this Discovering Math video, viewers will consider methods of displaying data, measures of central tendency, measures of variability, correlation, and line-fitting methods. Topics include: tables, bar graphs, histograms, scatter plots, line graphs, mean-mode-median, standard deviation, curve fitting line, median-fit line, and least-squares regression line. 

Length: 46 minutes

Item#: BVL117914

Copyright date: ©2007

Closed Captioned

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