SOCR Events May2008 - Revision history

IvoDinov: added title

2008-04-25T15:57:28Z

added title

2008-04-03T20:00:01Z

2008-02-14T22:09:04Z

2008-02-13T01:24:39Z

2008-02-12T22:13:16Z

2008-02-08T19:36:56Z

‎Analyze bivariate data using linear regression methods

2008-02-08T19:36:39Z

‎Compute probabilities for discrete distributions and use sampling distributions to calculate approximate probabilities

2008-02-08T19:36:21Z

‎Use percentiles and measures of variability to analyze data

2008-02-08T19:36:03Z

‎Apply basic concepts of probability

2008-02-08T19:35:47Z

‎Summarize, display, and analyze bivariate data

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-== [[SOCR_Events | SOCR Events]] - [[SOCR]] ASA MWM Webinar==
+== [[SOCR_Events | SOCR Events]] - [[SOCR]] ASA MWM Webinar - Interactive Web-based Probability and Statistics using SOCR==
 == Logistics==
 * '''Date''': Monday, May 05, 2008, 2:00-2:30 PM ([http://wwp.greenwichmeantime.com/time-zone/usa/pacific-time/ Pacific Time])
 * '''Presenter''': [http://www.stat.ucla.edu/~dinov/ Ivo Dinov], [http://www.SOCR.ucla.edu Statistics Online Computational Resource (SOCR)]

← Older revision		Revision as of 20:00, 3 April 2008
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	Use of the Fundamental Counting Principle, complement, theoretical probability, experiment, data, percentile, histogram, box-and-whisker plot, spread		Use of the Fundamental Counting Principle, complement, theoretical probability, experiment, data, percentile, histogram, box-and-whisker plot, spread
		+
		+	* [[AP_Statistics_Curriculum_2007_Prob_Basics#Elementary_Probability \| Elementary Probability Example]]: Each of the three boxes below contains two types of balls (Red and Green). Box 1 has 4 Red and 3 Green balls, box 2 has 3 Red and 2 Green balls, and box 3 has 2 Red and 1 Green balls. All balls are identical except for their labels. Which of the three boxes are you most likely to draw a Red ball from? In other words, if a randomly drawn ball is known to be Red, which box is the one that we most likely drew the ball out of?

	* Solve counting problems using the Fundamental Counting Principle		* Solve counting problems using the Fundamental Counting Principle

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 * '''Date''': Monday, May 05, 2008, 2:00-2:30 PM ([http://wwp.greenwichmeantime.com/time-zone/usa/pacific-time/ Pacific Time])
 * '''Presenter''': [http://www.stat.ucla.edu/~dinov/ Ivo Dinov], [http://www.SOCR.ucla.edu Statistics Online Computational Resource (SOCR)]
-* '''Venue''': TBD
+* '''Venue''': This webinar is presented as part of the follow-up activities for the [http://www.amstat.org/education/mwm American Statistical Association's Meeting Within a Meeting workshop] for math and science teachers.  If you are not a Meeting Within a Meeting participant and are interested in viewing the live webinar, please contact [http://www.amstat.org/about/index.cfm?fuseaction=contacts Rebecca Nichols] (Rebecca@amstat.org).
 * '''Sponsors''': [http://www.amstat.org ASA], [http://www.amstat.org/education/gaise/ GAISE], [http://www.amstat.org/education/mwm MWM], [[SOCR]]
 * '''Audience''': This Webinar is intended for middle school teachers in various science and quantitative disciplines.

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 == Logistics==
-* '''Date''': May 2008
+* '''Date''': Monday, May 05, 2008, 2:00-2:30 PM ([http://wwp.greenwichmeantime.com/time-zone/usa/pacific-time/ Pacific Time])
 * '''Presenter''': [http://www.stat.ucla.edu/~dinov/ Ivo Dinov], [http://www.SOCR.ucla.edu Statistics Online Computational Resource (SOCR)]
 * '''Venue''': TBD

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 ==References==
 * [http://www.schools.utah.gov/curr/core/corepdf/Mth7-12.pdf Utah Secondary Core Curriculum Standards for Statistics]
 * [[EBook | Interactive Statistics Education EBook]]
 * SOCR Home page: http://www.socr.ucla.edu
 {{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_Events_May2008}}

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 *Calculate probabilities in real problems using sampling distributions.
-===Analyze bivariate data using linear regression methods===
+===[[SOCR_Events_May2008_C9_S1 |Analyze bivariate data using linear regression methods]]===
 *Fit regression lines to pairs of numeric variables and calculate the means and standard deviations of the two variables and the correlation coefficient, using technology.

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 * Use histograms to obtain percentiles
-===Compute probabilities for discrete distributions and use sampling distributions to calculate approximate probabilities===
+===[[SOCR_Events_May2008_C8_S1 |Compute probabilities for discrete distributions and use sampling distributions to calculate approximate probabilities]]===
 * Obtain sample spaces and probability distributions for simple discrete random variables.

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 * Define simple discrete random variables
-===Use percentiles and measures of variability to analyze data===
+===[[SOCR_Events_May2008_C7_S1 |Use percentiles and measures of variability to analyze data]]===
 * Compute different measures of spread, including the range, standard deviation, and interquartile range

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 * Predict y-values for given x-values when appropriate using a line fitted to bivariate numerical data
-===Apply basic concepts of probability===
+===[[SOCR_Events_May2008_C6_S1 |Apply basic concepts of probability]]===
 Use of permutation, combination, conditional probability, discrete random variable, standard
 deviation, interquartile range, percentile.

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 * Use graphical representations and numerical summaries to answer questions and interpret data
-===Summarize, display, and analyze bivariate data===
+===[[SOCR_Events_May2008_C5_S1 | Summarize, display, and analyze bivariate data]]===
 Use of scatter plot, positive correlation, negative correlation, no correlation, line of best fit, bivariate data.