SOCR Events May2008
- 1 SOCR Events - SOCR ASA MWM Webinar - Interactive Web-based Probability and Statistics using SOCR
- 2 Logistics
- 3 Objectives
- 3.1 Use basic concepts of probability to determine the likelihood of an event and compare the results of various experiments
- 3.2 Display and compare data to make predictions and formulate conclusions
- 3.3 Calculate probabilities of events and compare theoretical and experimental probability
- 3.4 Formulate questions and answer the questions by organizing and analyzing data
- 3.5 Summarize, display, and analyze bivariate data
- 3.6 Apply basic concepts of probability
- 3.7 Use percentiles and measures of variability to analyze data
- 3.8 Compute probabilities for discrete distributions and use sampling distributions to calculate approximate probabilities
- 3.9 Analyze bivariate data using linear regression methods
- 4 References
SOCR Events - SOCR ASA MWM Webinar - Interactive Web-based Probability and Statistics using SOCR
- Title: Interactive Web-based Probability and Statistics using SOCR
- Date: Monday, May 05, 2008, 2:00-2:30 PM (Pacific Time)
- Presenter: Ivo Dinov, Statistics Online Computational Resource (SOCR)
- Venue: This webinar is presented as part of the follow-up activities for the 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 Rebecca Nichols (Rebecca@amstat.org).
- Webinar Archive: The complete record of this webinar will be posted online in May 2008.
- Sponsors: ASA, GAISE, MWM, SOCR
- Audience: This Webinar is intended for middle school teachers in various science and quantitative disciplines.
- Overarching Goals: To present an integrated approach for IT technology blended instruction using free Internet-based resources (web-applets, instructional materials and learning activities)
Use basic concepts of probability to determine the likelihood of an event and compare the results of various experiments
- Write the results of a probability experiment as a fraction, ratio, or decimal, between zero and one, or as a percent between zero and one hundred, inclusive
- Compare experimental results with theoretical probability
- Compare individual, small group, and large group results of a probability experiment
- Display data using tables, scatter plots, and circle graphs
- Compare two similar sets of data on the same graph
- Compare two different kinds of graphs representing the same set of data
- Propose and justify inferences and predictions based on data
Use of the Fundamental Counting Principle, complement, theoretical probability, experiment, data, percentile, histogram, box-and-whisker plot, spread
- 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
- Calculate the probability of an event or sequence of events with and without replacement using models
- Recognize that the sum of the probability of an event and the probability of its complement is equal to one
- Make approximate predictions using theoretical probability and proportions
- Collect and interpret data to show that as the number of trials increases, experimental probability approaches the theoretical probability
- Formulate questions that can be answered through data collection and analysis
- Determine the 25th and 75th percentiles (first and third quartiles) to obtain information about the spread of data
- Graphically summarize data of a single variable using histograms and box-and-whisker plots
- Compute the mean and median of a numerical characteristic and relate these values to the histogram of the data
- Use graphical representations and numerical summaries to answer questions and interpret data
Use of scatter plot, positive correlation, negative correlation, no correlation, line of best fit, bivariate data.
- Collect, record, organize, and display a set of data with at least two variables
- Determine whether the relationship between two variables is approximately linear or nonlinear by examination of a scatter plot
- Characterize the relationship between two linear related variables as having positive, negative, or approximately zero correlation
- Estimate, interpret, and use lines fit to bivariate data
- Estimate the equation of a line of best fit to make and test conjectures
- Interpret the slope and y-intercept of a line through data
- Predict y-values for given x-values when appropriate using a line fitted to bivariate numerical data
Use of permutation, combination, conditional probability, discrete random variable, standard deviation, interquartile range, percentile.
- Distinguish between permutations and combinations and identify situations in which each is appropriate
- Calculate probabilities using permutations and combinations to count events
- Compute conditional and unconditional probabilities in various ways, including by definitions, the general multiplication rule, and probability trees
- Define simple discrete random variables
- Compute different measures of spread, including the range, standard deviation, and interquartile range
- Compare the effectiveness of different measures of spread, including the range, standard deviation, and interquartile range in specific situations
- Use percentiles to summarize the distribution of a numerical variable
- Use histograms to obtain percentiles
Compute probabilities for discrete distributions and use sampling distributions to calculate approximate probabilities
- Obtain sample spaces and probability distributions for simple discrete random variables.
- Compute binomial probabilities using Pascal’s Triangle and the Binomial Theorem.
- Compute means and variances of discrete random variables.
- Compute probabilities using areas under the Normal Curve.
- Calculate parameters of sampling distributions for the sample average, sum, and proportion.
- Calculate probabilities in real problems using sampling distributions.
- 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.
- Compute predictions of y-values for given x-values using a regression equation, and recognize the limitations of such predictions.
- Compute and use the standard error for regression.
- Utah Secondary Core Curriculum Standards for Statistics
- (GAISE) Report: A Pre-K -12 Curriculum Framework
- Interactive Statistics Education EBook
- SOCR Home page: http://www.socr.ucla.edu
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