Difference between revisions of "SOCR Events LAUSD Mar2013"

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== [[SOCR_Events | SOCR Events]]: 2013 [http://www.socr.ucla.edu SOCR] AP Statistics Continuing Education Workshop ==
+
== [[SOCR_News | SOCR News & Events]]: 2013 [http://www.socr.ucla.edu SOCR] blended mathematics and statistics education resources: the California Common Core State Standards ==
−
[[Image:SOCR_Icon_ConceptsMethods.png|150px|thumbnail|right| 2010 SOCR AP Stats Workshop]]
+
[[Image:SOCR_Icon_ConceptsMethods.png|150px|thumbnail|right| 2013 SOCR LAUSD Common Core Standards Workshop]]
  
−
== Workshop Summary and Goals ==
+
==Overview==
−
The 2010 SOCR Advanced Placement (AP) training, continuing education and development workshop will extend the efforts of the [[SOCR_Events_Aug2007 | 2007 SOCR/CAUSEway workshop]] and the [[SOCR_Events_Aug2009 | 2009 SOCR Continuing Education workshop]]. The aims of this workshop are to demonstrate the functionality, utilization and assessment of the current SOCR resources in the AP statistics curricula. The [[SOCR]] Motto ''It's Online, Therefore it Exists!'' clearly indicates that all of these tools, activities and materials are freely available over the Internet to the entire community. This workshop will be of most value to AP teachers and college instructors of probability and statistics classes who have interests in exploring novel technology-enhanced approaches for statistics education. The workshop will provide an interactive forum for exchange of ideas and recommendations for strategies to integrate computers, modern pedagogical techniques, the Internet and new student assessment techniques.
+
The [http://socr.ucla.edu/ Statistics Online Computational Resource (SOCR)] designs, validates and freely disseminates knowledge. Specifically, SOCR provides portable online aids for probability, statistics and mathematics education, technology based instruction and statistical computing. SOCR tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials.
 +
 
 +
The [http://www.cde.ca.gov/re/cc/ California Common Core State Standards, CCSS] describe the K-12 knowledge of California pupils by subject and grade. In California, the State Board of Education decides on the standards for all students, from kindergarten through high school.
 +
 
 +
The [http://www.lausd.net/math/InstructionalGuides/Mathematics%20Instructional%20Guide%202009%20-%202010.pdf LAUSD Mathematics Instructional Guide (MIG)] promotes a balanced and designed mathematics curriculum for students as part of a coherent educational system. The Los Angeles Unified School District's (LAUSD) vision is to provide its students with:
 +
* A designed curriculum based on the Mathematics Content Standards for California Public Schools and the Mathematics Framework for California Public Schools.
 +
* A balanced curriculum that teaches computational and procedural skills; conceptual understanding of mathematics; and problem solving.
  
 
== Presenters ==
 
== Presenters ==
−
* [http://directory.stat.ucla.edu/info.php?directory=3 Nicolas Christou], [http://www.ucla.edu UCLA] [http://www.stat.ucla.edu Statistics]
+
* [http://directory.stat.ucla.edu/nicolas-christou Nicolas Christou], [http://www.ucla.edu UCLA] [http://www.stat.ucla.edu Statistics]
−
* [http://directory.stat.ucla.edu/info.php?directory=146 Ivo Dinov], [http://www.ucla.edu UCLA] [http://www.stat.ucla.edu Statistics] and [http://www.ccb.ucla.edu Center for Computational Biology]
+
* [http://www.stat.ucla.edu/~dinov/ Ivo Dinov], [http://www.ucla.edu UCLA] [http://www.stat.ucla.edu Statistics] and [http://www.ccb.ucla.edu Center for Computational Biology]
  
−
== Attendees ==
+
==Advantages of the SOCR IT-Enhanced Blended Instruction Resources==
−
[[SOCR_Events_Aug2010_Attendees | Workshop Attendees List]]
 
  
−
== Logistics==
+
The SOCR technology-enhanced blended instruction model to K-12 science-education has the following '''advantages''':
−
===Date, Place and Time===
 
−
We anticipate being able to host 10-15 workshop participants for this 1-day intensive training event. There will be no registration fee, no travel funds or accommodation reimbursements, however free refreshments will be provided during the workshop. All interested participants must submit an application and be approved to attend the workshop in advance (see below).
 
−
* '''Date''': [http://calendar.ucla.edu/event_detail.php?eid=22483 Fri, August 13, 2010]
 
−
* '''Times''': AM & PM Sessions (9AM - 12PM & 1PM - 4:30 PM)
 
−
* '''On-site Registration''': starts at 8:00 AM, 08/13/10
 
−
* '''Venue/Place''': [http://www.stat.ucla.edu/computing/labs/ Boelter Hall 9413 Computer Lab (workshop venue)]
 
−
* '''Maps''': [http://www.socr.ucla.edu/SOCR_UserGoogleMap.html SOCR Interactive Google Map], [http://www.ucla.edu/map UCLA Maps]
 
  
−
===Application===
+
* ''Multi-lingual support'': All materials are auto-translated into 24 different languages;
−
Please register/submit your application to participate in the 2010 SOCR AP Workshop via email to [[Image:SOCR_Email.png|150px]]. Please include your CV/Biosketch and a short description of your background, AP statistics interests and teaching role (including courses you expect to teach in the next few years). We will make any effort to invite as many people as we can physically accommodate, however, we can not guarantee that we have the resources to invite all applicants, or to respond to all applicants that may not be selected (we expect a large number of applicants). Women, minorities and persons with disabilities are encouraged to apply. All applications received before July 15, 2010 will receive full consideration.
+
* ''CCSS support'': The SOCR learning materials, tools and activities are community-built and cover most of the mathematics and statistics components of the CCSS standard;
 +
* ''Open-access'': All SOCR resources are always freely and openly accessible to all (students, teachers and the community) and can be customized for specific curricular needs (e.g., [http://www.k12hsn.org/calaxy/wikis.php/calaxy/Probability_and_Statistics_EBook K12HSN Calaxy network]);
 +
*  ''Blended Instructional Model'': the SOCR learning resources blend information technology, open-datasets, scientific techniques and modern pedagogical concepts.  
  
−
== Program ==
+
===California Common Core State Standards (CCSS)===
−
<center>
+
* General [http://www.cde.ca.gov/re/cc/ California Common Core State Standards]
−
[[Image:SOCR_2009Workshop_Handbook_FrontCover.png|150px|thumbnail|right| [http://www.socr.ucla.edu/docs/SOCR_2009_Workshop/Handbook/SOCR_Workshop_Booklet_Aug2009.pdf Workshop Handbook] ]]
+
** [http://www.scoe.net/castandards/agenda/2010/math_ccs_recommendations.pdf Mathematics CCSS Standards]
 +
*** [http://www.corestandards.org/Math/Content/SP Probability and Statistics (Grades 6-8)]
 +
**** Summarize and describe distributions: Relating the choice of measures of center and variability to the shape of the data distribution and the context in which the data were gathered (e.g., Coin-Sample Experiment ([http://socr.ucla.edu/htmls/exp/Coin_Sample_Experiment.html Java] and [http://www.distributome.org/V3/exp/BinomialExperiment.html JavaScript]).
 +
**** Use random sampling to draw inferences about a population (e.g., [http://www.distributome.org/V3/exp/DiscreteUniformExperiment.html Discrete Uniform Simulation]).
 +
**** Draw informal comparative inferences about two populations (e.g., [http://www.distributome.org/V3/exp/BinomialExperiment.html Binomial Coin with varying p=P(Head)]).
 +
**** Investigate chance processes and develop, use, and evaluate probability models.
 +
**** Investigate patterns of association in bivariate data (e.g., [http://www.socr.ucla.edu/htmls/game/Bivariate_Game.html Interactive Scatter plot]).
 +
*** [http://www.corestandards.org/Math/Content/HSS/introduction Probability and Statistics (Grades 9-12)]
 +
**** Interpreting Categorical & Quantitative Data (e.g., [[AP_Statistics_Curriculum_2007_Contingency_Fit|Mendel's Pea Experiment]])
 +
**** Making Inferences & Justifying Conclusions (e.g., [[AP_Statistics_Curriculum_2007_Hypothesis_Proportion#Genders_of_Siblings_Example| Gender of Siblings Example]])
 +
**** Conditional Probability & the Rules of Probability (e.g., [[AP_Statistics_Curriculum_2007_Prob_Rules#Contingency_table|Type and location of cancer example]])
 +
**** Using Probability to Make Decisions (e.g., [[AP_Statistics_Curriculum_2007_Prob_Rules#Monty_Hall_Problem|Monte Hall Problem/Demo]])
  
−
[[Image:BusinessCard_CD_Label_SOCR_2010.png|150px|thumbnail|right| [http://www.socr.ucla.edu/jars/SOCR/SOCR_CD.zip SOCR Mini-CD] ]]
+
===SOCR Professional Development Activities===
−
{| class="wikitable"
+
SOCR faculty, students and fellows regularly conduct onsite and remote continuing education training sessions and participate in local and National educational workshops. The future, current and past training activities are listed on the [[SOCR_News| SOCR News website]].
−
|-
 
−
! Time || Presenter || Topic
 
−
|-
 
−
| 8:00-9:00AM || colspan=2 align="center"| Registration and Breakfast
 
−
|-
 
−
| 9:00-9:10AM || [http://directory.stat.ucla.edu/info.php?directory=146 Ivo Dinov], SOCR Director || Welcome
 
−
|-
 
−
| 9:10-9:20AM || Everyone|| [[SOCR_Events_Aug2010_Attendees | Participants Introductions]]
 
−
|-
 
−
| 9:20-9:30AM || [http://directory.stat.ucla.edu/info.php?directory=146 Ivo Dinov] || [[SOCR_Events_SOCR_Workshop2010_GuestAccounts | Guest Accounts]]
 
−
|-
 
−
| 9:20-9:30AM || [http://directory.stat.ucla.edu/info.php?directory=146 Ivo Dinov] || [http://socr.ucla.edu/APStats/ AP Statistics Curriculum]
 
−
|-
 
−
| rowspan=3|9:40-10:00AM || rowspan=3|[http://directory.stat.ucla.edu/info.php?directory=3 Nicolas Christou], SOCR Co-Director || [[SOCR_Data | SOCR Open Motivational Datasets]]
 
−
|-
 
−
| [[SOCR_Data |Research-derived data]] and a [[SOCR_EduMaterials_AnalysisActivities_TwoPairedT |Paired t-test example]]
 
−
|-
 
−
| [http://wiki.stat.ucla.edu/niser/index.php/NISER_EduMaterials_GeneralActivities Multidisciplinary data understanding]
 
−
|-
 
−
| 10:00-10:30AM || [http://directory.stat.ucla.edu/info.php?directory=3 Nicolas Christou] || [http://socr.ucla.edu/htmls/SOCR_Distributions.html SOCR Distributions] & [[SOCR_EduMaterials_DistributionsActivities | Distribution Activities]]
 
−
|-
 
−
| 10:30-11:00AM || [http://directory.stat.ucla.edu/info.php?directory=146 Ivo Dinov] || [http://socr.ucla.edu/htmls/SOCR_Experiments.html SOCR Experiments] & [http://socr.ucla.edu/htmls/SOCR_Games.html SOCR Games]
 
−
|-
 
−
| 11:00-11:30AM || [http://directory.stat.ucla.edu/info.php?directory=146 Ivo Dinov] || [http://socr.ucla.edu/htmls/SOCR_Analyses.html SOCR Analyses], [http://socr.ucla.edu/htmls/SOCR_Modeler.html SOCR Modeler] & [http://socr.ucla.edu/htmls/SOCR_Charts.html SOCR Charts]
 
−
|-
 
−
| 11:30AM-12:00PM || Everyone || Interactive Group Discussion: What works, what doesn't, how to extend the collection and enhance the experiences of others?
 
−
|-
 
−
| 12:00-1:00PM || colspan=2 align="center"| Lunch Break (lunch provided by organizers) and informal discussions
 
−
|-
 
−
| 1:00-1:45PM || [http://directory.stat.ucla.edu/info.php?directory=146 Ivo Dinov] || [[SOCR_EduMaterials_Activities_GeneralCentralLimitTheorem | Central Limit Theorem (CLT)]]
 
−
|-
 
−
| 1:45-2:30PM || [http://directory.stat.ucla.edu/info.php?directory=146 Ivo Dinov] || [[SOCR_MotionCharts_CAOzoneData | California Ozone Pollution Activity]]
 
−
|-
 
−
| 2:30-3:15PM || [http://directory.stat.ucla.edu/info.php?directory=3 Nicolas Christou] || [[SOCR_EduMaterials_Activities_General_CI_Experiment | Confidence Intervals Activity]]
 
−
|-
 
−
| 3:15-4:00PM || [http://directory.stat.ucla.edu/info.php?directory=3 Nicolas Christou] || [http://socr.ucla.edu/htmls/app SOCR Application Activities]
 
−
|-
 
−
| 4:00-4:10PM || [[SOCR_Events_Aug2010_Attendees | Attendees]] || [[SOCR_Events_Aug2010#Workshop_Evaluation| Workshop Evaluation (Web Survey)]]
 
−
|-
 
−
| 4:10-4:30PM || Everyone || Interactive Group Discussion: What works, what doesn't, how to extend the collection and enhance the experiences of others?
 
−
|}
 
−
</center>
 
  
−
==Workshop Evaluation==
+
===SOCR Demonstrations===
−
Please complete [http://www.esurveyspro.com/Survey.aspx?id=061edb53-bc89-49e3-8662-d87389426fa7 this brief (1-page) survey] and provide your ''anonymous'' comments, ideas and critiques regarding the workshop organization and the presented SOCR materials. The organizers appreciate your time end effort to complete [http://www.esurveyspro.com/Survey.aspx?id=061edb53-bc89-49e3-8662-d87389426fa7 this survey] and help us improve our education and training efforts.
+
* [http://www.socr.ucla.edu/ Java Applets (analyses, distributions, games, experiments, charts/plots, data-modeler)]
−
 
+
* [http://socr.ucla.edu/htmls/HTML5/ HTML5/JavaScript webapps (mobile devices)]
−
== Sponsorship ==
+
* [[SOCR_EduMaterials |Interactive Learning Activities]]
−
{| style="margin: 1em auto 1em auto" border="3"
+
* [[SOCR_Data|Datasets]]
−
|-
 
−
| [[Image:SOCR Logo Static.GIF|link=socr|80px|]] || [[Image:UCLA Statistics Logo.gif|link=http://www.socr.ucla.edu|80px|]] || [[Image:UCLA Logo.gif|link=http://www.socr.ucla.edu|80px|]] || [[Image:NSF_Logo.jpg|link=http://www.nsf.gov|80px|]]
 
−
|-
 
−
|  [http://www.socr.ucla.edu SOCR]  ||  [http://www.stat.ucla.edu/ UCLA Statistics]  ||  [http://www.oid.ucla.edu/ UCLA OID] || [http://www.nsf.gov NSF]
 
−
|}
 
  
 
==Additional Resources==
 
==Additional Resources==
 +
===Exemplary SOCR Resources===
 
* The complete SOCR Teaching Statistics with Technology EBook is freely available in PDF format from the following digital libraries:
 
* The complete SOCR Teaching Statistics with Technology EBook is freely available in PDF format from the following digital libraries:
 
** Handbook: [http://www.socr.ucla.edu/docs/SOCR_2009_Workshop/Handbook/SOCR_Workshop_Booklet_Aug2009.pdf (10MB, low-res) PDF] and [http://www.socr.ucla.edu/docs/SOCR_2009_Workshop/Handbook/SOCR_Workshop_Booklet_Aug2009_mid.pdf (320MB, high-res) PDF]
 
** Handbook: [http://www.socr.ucla.edu/docs/SOCR_2009_Workshop/Handbook/SOCR_Workshop_Booklet_Aug2009.pdf (10MB, low-res) PDF] and [http://www.socr.ucla.edu/docs/SOCR_2009_Workshop/Handbook/SOCR_Workshop_Booklet_Aug2009_mid.pdf (320MB, high-res) PDF]
Line 92: Line 57:
 
** ISBN 978-0-615-30464-9
 
** ISBN 978-0-615-30464-9
 
** [http://lcweb.loc.gov Library of Congress Control Number:  2009907564]
 
** [http://lcweb.loc.gov Library of Congress Control Number:  2009907564]
 +
* [http://www.socr.ucla.edu/APStats/ SOCR AP Statistics Resources]
 
* [[EBook | SOCR Online Probability and Statistics EBook]]
 
* [[EBook | SOCR Online Probability and Statistics EBook]]
−
* [[SOCR_Events_Aug2010_Postings]]
+
 
−
* [http://wiki.stat.ucla.edu/socr/uploads/3/3c/SOCR_2010_WorkshopFlier.pdf Workshop Flier (PDF)] (0.5MB)
+
===Probability and Statistics CCSS===
−
* [http://picasaweb.google.com/jenny.jcui/Socr2010?authkey=Gv1sRgCLHcy4OU1vuOcA&feat=directlink photos]
+
* ''Grades 8-12'': Mathematics Content Standards: This discipline is an introduction to the study of probability, interpretation of data, and fundamental statistical problem solving. Mastery of this academic content will provide students with a solid foundation in probability and facility in processing statistical information.
 +
: 1.0 Students know the definition of the notion of independent events and can use the rules for addition, multiplication, and complementation to solve for probabilities of particular events in finite sample spaces.  
 +
: 2.0 Students know the definition of conditional probability and use it to solve for probabilities in finite sample spaces.  
 +
: 3.0 Students demonstrate an understanding of the notion of discrete random variables by using them to solve for the probabilities of outcomes, such as the probability of the occurrence of five heads in 14 coin tosses.
 +
: 4.0 Students are familiar with the standard distributions (normal, binomial, and exponential) and can use them to solve for events in problems in which the distribution belongs to those families.
 +
: 5.0 Students determine the mean and the standard deviation of a normally distributed random variable.
 +
: 6.0 Students know the definitions of the mean, median, and mode of a distribution of data and can compute each in particular situations.
 +
: 7.0 Students compute the variance and the standard deviation of a distribution of data.
 +
: 8.0 Students organize and describe distributions of data by using a number of different methods, including frequency tables, histograms, standard line and bar graphs, stem-and-leaf displays, scatterplots, and box-and-whisker plots.
 +
 +
====Advanced Placement (AP) Probability and Statistics====
 +
* ''Grades 8-12'': Mathematics Content Standards: This discipline is a technical and in-depth extension of probability and statistics. In particular, mastery of academic content for advanced placement gives students the background to succeed in the Advanced Placement examination in the subject.
 +
: 1.0 Students solve probability problems with finite sample spaces by using the rules for addition, multiplication, and complementation for probability distributions and understand the simplifications that arise with independent events.
 +
: 2.0 Students know the definition of conditional probability and use it to solve for probabilities in finite sample spaces.
 +
: 3.0 Students demonstrate an understanding of the notion of discrete random variables by using this concept to solve for the probabilities of outcomes, such as the probability of the occurrence of five or fewer heads in 14 coin tosses.
 +
: 4.0 Students understand the notion of a continuous random variable and can interpret the probability of an outcome as the area of a region under the graph of the probability density function associated with the random variable.
 +
: 5.0 Students know the definition of the mean of a discrete random variable and can determine the mean for a particular discrete random variable.
 +
: 6.0 Students know the definition of the variance of a discrete random variable and can determine the variance for a particular discrete random variable.
 +
: 7.0 Students demonstrate an understanding of the standard distributions (normal, binomial, and exponential) and can use the distributions to solve for events in problems in which the distribution belongs to those families.
 +
: 8.0 Students determine the mean and the standard deviation of a normally distributed random variable.
 +
: 9.0 Students know the central limit theorem and can use it to obtain approximations for probabilities in problems of finite sample spaces in which the probabilities are distributed binomially.
 +
: 10.0 Students know the definitions of the mean, median, and mode of distribution of data and can compute each of them in particular situations.
 +
: 11.0 Students compute the variance and the standard deviation of a distribution of data.
 +
: 12.0 Students find the line of best fit to a given distribution of data by using least squares regression.
 +
: 13.0 Students know what the correlation coefficient of two variables means and are familiar with the coefficient's properties.
 +
: 14.0 Students organize and describe distributions of data by using a number of different methods, including frequency tables, histograms, standard line graphs and bar graphs, stem-and-leaf displays, scatterplots, and box-and-whisker plots.
 +
: 15.0 Students are familiar with the notions of a statistic of a distribution of values, of the sampling distribution of a statistic, and of the variability of a statistic.
 +
: 16.0 Students know basic facts concerning the relation between the mean and the standard deviation of a sampling distribution and the mean and the standard deviation of the population distribution.
 +
: 17.0 Students determine confidence intervals for a simple random sample from a normal distribution of data and determine the sample size required for a desired margin of error.
 +
: 18.0 Students determine the P- value for a statistic for a simple random sample from a normal distribution.  
 +
: 19.0 Students are familiar with the chi- square distribution and chi- square test and understand their uses.
 +
 
  
 
<hr>
 
<hr>
 
{{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_Events_LAUSD_Mar2013}}
 
{{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_Events_LAUSD_Mar2013}}

Latest revision as of 16:52, 18 March 2013

SOCR News & Events: 2013 SOCR blended mathematics and statistics education resources: the California Common Core State Standards

2013 SOCR LAUSD Common Core Standards Workshop

Overview

The Statistics Online Computational Resource (SOCR) designs, validates and freely disseminates knowledge. Specifically, SOCR provides portable online aids for probability, statistics and mathematics education, technology based instruction and statistical computing. SOCR tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials.

The California Common Core State Standards, CCSS describe the K-12 knowledge of California pupils by subject and grade. In California, the State Board of Education decides on the standards for all students, from kindergarten through high school.

The LAUSD Mathematics Instructional Guide (MIG) promotes a balanced and designed mathematics curriculum for students as part of a coherent educational system. The Los Angeles Unified School District's (LAUSD) vision is to provide its students with:

  • A designed curriculum based on the Mathematics Content Standards for California Public Schools and the Mathematics Framework for California Public Schools.
  • A balanced curriculum that teaches computational and procedural skills; conceptual understanding of mathematics; and problem solving.

Presenters

Advantages of the SOCR IT-Enhanced Blended Instruction Resources

The SOCR technology-enhanced blended instruction model to K-12 science-education has the following advantages:

  • Multi-lingual support: All materials are auto-translated into 24 different languages;
  • CCSS support: The SOCR learning materials, tools and activities are community-built and cover most of the mathematics and statistics components of the CCSS standard;
  • Open-access: All SOCR resources are always freely and openly accessible to all (students, teachers and the community) and can be customized for specific curricular needs (e.g., K12HSN Calaxy network);
  • Blended Instructional Model: the SOCR learning resources blend information technology, open-datasets, scientific techniques and modern pedagogical concepts.

California Common Core State Standards (CCSS)

SOCR Professional Development Activities

SOCR faculty, students and fellows regularly conduct onsite and remote continuing education training sessions and participate in local and National educational workshops. The future, current and past training activities are listed on the SOCR News website.

SOCR Demonstrations

Additional Resources

Exemplary SOCR Resources

Probability and Statistics CCSS

  • Grades 8-12: Mathematics Content Standards: This discipline is an introduction to the study of probability, interpretation of data, and fundamental statistical problem solving. Mastery of this academic content will provide students with a solid foundation in probability and facility in processing statistical information.
1.0 Students know the definition of the notion of independent events and can use the rules for addition, multiplication, and complementation to solve for probabilities of particular events in finite sample spaces.
2.0 Students know the definition of conditional probability and use it to solve for probabilities in finite sample spaces.
3.0 Students demonstrate an understanding of the notion of discrete random variables by using them to solve for the probabilities of outcomes, such as the probability of the occurrence of five heads in 14 coin tosses.
4.0 Students are familiar with the standard distributions (normal, binomial, and exponential) and can use them to solve for events in problems in which the distribution belongs to those families.
5.0 Students determine the mean and the standard deviation of a normally distributed random variable.
6.0 Students know the definitions of the mean, median, and mode of a distribution of data and can compute each in particular situations.
7.0 Students compute the variance and the standard deviation of a distribution of data.
8.0 Students organize and describe distributions of data by using a number of different methods, including frequency tables, histograms, standard line and bar graphs, stem-and-leaf displays, scatterplots, and box-and-whisker plots.

Advanced Placement (AP) Probability and Statistics

  • Grades 8-12: Mathematics Content Standards: This discipline is a technical and in-depth extension of probability and statistics. In particular, mastery of academic content for advanced placement gives students the background to succeed in the Advanced Placement examination in the subject.
1.0 Students solve probability problems with finite sample spaces by using the rules for addition, multiplication, and complementation for probability distributions and understand the simplifications that arise with independent events.
2.0 Students know the definition of conditional probability and use it to solve for probabilities in finite sample spaces.
3.0 Students demonstrate an understanding of the notion of discrete random variables by using this concept to solve for the probabilities of outcomes, such as the probability of the occurrence of five or fewer heads in 14 coin tosses.
4.0 Students understand the notion of a continuous random variable and can interpret the probability of an outcome as the area of a region under the graph of the probability density function associated with the random variable.
5.0 Students know the definition of the mean of a discrete random variable and can determine the mean for a particular discrete random variable.
6.0 Students know the definition of the variance of a discrete random variable and can determine the variance for a particular discrete random variable.
7.0 Students demonstrate an understanding of the standard distributions (normal, binomial, and exponential) and can use the distributions to solve for events in problems in which the distribution belongs to those families.
8.0 Students determine the mean and the standard deviation of a normally distributed random variable.
9.0 Students know the central limit theorem and can use it to obtain approximations for probabilities in problems of finite sample spaces in which the probabilities are distributed binomially.
10.0 Students know the definitions of the mean, median, and mode of distribution of data and can compute each of them in particular situations.
11.0 Students compute the variance and the standard deviation of a distribution of data.
12.0 Students find the line of best fit to a given distribution of data by using least squares regression.
13.0 Students know what the correlation coefficient of two variables means and are familiar with the coefficient's properties.
14.0 Students organize and describe distributions of data by using a number of different methods, including frequency tables, histograms, standard line graphs and bar graphs, stem-and-leaf displays, scatterplots, and box-and-whisker plots.
15.0 Students are familiar with the notions of a statistic of a distribution of values, of the sampling distribution of a statistic, and of the variability of a statistic.
16.0 Students know basic facts concerning the relation between the mean and the standard deviation of a sampling distribution and the mean and the standard deviation of the population distribution.
17.0 Students determine confidence intervals for a simple random sample from a normal distribution of data and determine the sample size required for a desired margin of error.
18.0 Students determine the P- value for a statistic for a simple random sample from a normal distribution.
19.0 Students are familiar with the chi- square distribution and chi- square test and understand their uses.


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