• Statistics and Probability

Instructor:            Tim Frame

Voice mail: 763.506.6261

Email: tim.frame@ahschools.us

Student progress: This is a required course, meaning successful completion is required for graduation.  Students and parents may access progress reports at any time via AH Connect.

Class Tools:

• Scientific calculator or graphing calculator
• folder and pencil

Homework:   Students will be assigned daily homework.  A satisfactory assignment is one that shows an effort to do all of the assigned problems and demonstrates an understanding of the procedures used.  Homework will be collected on a daily basis.  Points will be deducted for late work and all late work must be turned in before the unit test.

Assessments:

There will be at least one quiz per chapter.  You may use your note packet on quizzes.  We will have a test at the end of each unit as well as a final test at the end of the trimester.  In order for a test re-take to be an option you need to meet the following requirements:

• all homework for the unit is completed by the original test date
• the remediation (extra practice) packet is completed
• re-test is completed (either Tuesday during advisement or Wednesday morning during tornado time) within one week of the original test date

Absences:   It is important to keep absences to a minimum.  Due to the activities that are done in class and the fact that you will not have a book, absences can be a major obstacle to success in this class.  All class notes can be found on my website.

Keys for success:

• See me before or after school in the Math Resource Center for extra help.
• Work on homework with other students from class.
• Attend class every day.

A        90% and above

B        80% - 89%

C        70% - 79%

D        60% - 69%

F         0%   - 59%

Weighting Scale:

70 %   Tests

10 %   Quizzes

20 %  Final Exam

 PRIORITY High, Medium, Low Learning Targets Approximate # of Days Resources Standards 2007 Benchmarks Chapter 1 6-8 days total high I can list the outcomes in a sample space for an event by making a list, creating a tree diagram, or by creating a table or grid. 1.1 9.4.3.1 high I can find the number of outcomes for an event using the Fundamental Counting Principle. 1.2 9.4.3.1 high I can find the number of outcomes for an event using permutations. 1.3 9.4.3.1 high I can find the number of outcomes for an event using combinations. 1.4 9.4.3.1 high I can select and apply an appropriate counting method to determine the number of outcomes for an event. 1.1, 1.2, 1.3, 1.4, 1.5 9.4.3.1 low I can select and apply more than one counting method in a multi-step situation to determine the number of outcomes for an event. 1.5 9.4.3.1 Chapter 2 8-10 days total high I can use counting methods to calculate and write a probability for a simple event. 2.1 9.4.3.1 low I can use the concept of the Law of Large Numbers and probabilities to make informed decisions. 2.1 9.4.3.3, 9.4.3.8 high I can calculate probabilities for compound events with or without replacement. 2.2 9.4.3.5 medium I can identify and apply the concepts of mutually exclusive and independence when calculating probabilities for two or more events. 2.2, 2.3 9.4.3.5 medium I can create and use Venn Diagrams to calculate probabilities involving the intersection ("AND"), union ("OR"), or complements ("NOT") of events. 2.1, 2.3 9.4.3.6 medium I can create and use Tree Diagrams to calculate probabilities involving the intersection ("AND"), union ("OR"), or complements ("NOT") of events. 2.4 9.4.3.1 medium I can create and use a 2-way table to calculate probabilities involving the intersection ("AND"), union ("OR"), complements ("NOT"), or conditional probabilities ("GIVEN") of events. 2.5 9.4.3.9 low I can use probability formulas to calculate probabilities involving the intersection ("AND"), union ("OR"), complements ("NOT"), or conditional probabilities ("GIVEN") of events. 2.2, 2.3, 2.4, 2.5 9.4.3.7 high I can select and apply an appropriate method to calculate the probability for an event or series of events. 2.1, 2.2, 2.3, 2.4, 2.5 9.4.3.5, 9.4.3.6, 9.4.3.7 Chapter 3 5-7 days total high I can construct a probability model. 3.1, 3.2, 3.3 9.4.3.1 high I can calculate the expected value of a variable. 3.1, 3.2, 3.3 9.4.3.2 medium I can use expected value to determine if a game is fair 3.2, 3.3 9.4.3.8 medium I can assign digits to a probability model for a simulation. 3.3 9.4.3.4 medium I can carry out a simulation using a random digit table and properly assigned digits based on a probability model. 3.3 9.4.3.2, 9.4.3.4 low I can interpret the results from repeated simulations by calculating an experimental probability to make a decision about future outcomes (Law of Large Numbers). 3.3 9.4.3.2, 9.4.3.3 Chapter 4 6-8 days total high I can distinguish between the various methods for data collection (sample survey, census, observational studies and experiments). 4.1 9.4.2.1 low I can identify sampling methods (SRS, stratified RS, systematic RS, multi-stage RS, voluntary response, convenience). 4.2 9.4.2.3 high I can evaluate sampling methods and identify potential sources of bias in the data collection process. 4.2 9.4.2.3 medum I can use a table of random digits or technology to select a random sample. 4.3 9.4.3.4 medium I can find the margin of error and write a confidence statement for an estimated 95% confidence interval. 4.4 9.4.2 low I can identify different experiment designs (completely randomized design and randomized block design). 4.5 9.4.2.3 high I can evaluate experimental designs and identify potential lurking variables in the data collection process. 4.5 9.4.2.2, 9.4.2.3 low I can design a good experiment. 4.5 9.4.2.3 Chapter 5 8-9 days total low I can construct a bar graph or pie chart for a set of categorical data. 5.1 9.4.1.1 high I can interpret a bar graph or pie chart for a set of categorical data. 5.1 9.4.1.1 high I can identify when a data display is misleading or distorted. 5.1 9.4.2.1, 9.4.2.2 low I can construct and interpret a graph that shows change over time (line graph or time plot). 5.2 9.4.1.1 high I can calculate statistics for the measure of center of numerical data (mean, median, mode). 5.2 9.4.1.1 high I can calculate statistics for the measure of spread of numerical data (range, IQR, standard deviation). 5.2, 5.5 9.4.1.1 low I can construct a dot plot for a numerical data set. 5.2 9.4.1.1 medium I can interpret and describe a dot plot (SOCCS). 5.3 9.4.1.1 low I can construct a stem-plot for a numerical data set, including split-stem plots. 5.3 9.4.1.1 high I can interpret and describe a stem-plot (SOCCS). 5.3 9.4.1.1 low I can construct a histogram for a numerical data set. 5.4 9.4.1.1 high I can interpret and describe a histogram (SOCCS). 5.4 9.4.1.1 high I can calculate a 5-Number Summary for a set of numerical data {minimum, quartile 1, median, quartile 3, maximum}. 5.5 9.4.1.1 medium I can construct a box-plot for a numerical data set. 5.5 9.4.1.1 high I can interpret and describe a box-plot (SOCCS). 5.5 9.4.1.1 low I can identify outliers in a set of data using the IQR Criterion. 5.5 9.4.1.1 medium I can decide which measures of center (mean, median, mode) and spread (range, standard deviation, IQR) are appropriate to describe a given situation. 5.5 9.4.1.1, 9.4.1.2 high I can analyze/deduce/infer the effects of an outlier and removing a data point from a set of data. 5.5 9.4.1.2 low I can compare more than one set of numerical data using multiple graphical displays (side-by-side box plots and back-to-back stem plots). 5.6 9.4.1.1 high I can determine an appropriate type of graphical display for data. 5.1, 5.2, 5.3, 5.4, 5.5, 5.6 9.4.1.1 Chapter 6 6-7 days total medium I can construct a scatterplot to display the relationship between two numerical variables (with and without technology). 6.1, 6.3, 6.4 9.4.1.3 high I can describe and interpret a scatterplot (SCOFD). 6.1, 6.2, 6.3, 6.4 9.4.1.3 medium I can calculate the correlation coefficient of two variables using technology. 6.3 9.4.1.3 high I can interpret the meaning of the correlation coefficient. 6.2, 6.3, 6.4 9.4.1.3 high I can recognize when arguments based on data confuse correlation and causation. 6.2 9.4.2.2 medium I can identify possible lurking variables in bi-variate data. 6.2 9.4.2.2 medium I can calculate and graph a least squares regression line (LSRL) as a line of best fit. 6.3, 6.4 9.4.1.3 high I can use the LSRL equation to make predictions. 6.3, 6.4 9.4.1.3 medium I can determine the validity of the predictions made with a least squares regression equation (interpolation and extrapolation). 6.3, 6.4 9.4.1.3 medium I can interpret the slope and the y-intercept of the LSRL. 6.3, 6.4 9.4.1.3 high I can describe the effects of an outlier on the correlation coefficient (r) and the LSRL equation. 6.3, 6.4 9.4.1.3 Chapter 7 5-6 days total low I can construct a normal curve for a normal distribution 7.1 9.4.1.4 medium I can identify the approximate mean and standard deviation from a normal curve. 7.1 9.4.1.4 low I can use the Empirical Rule (68-95-99.7) to estimate probabilities and percentages about a normal distribution. 7.1 9.4.1.4 high I can calculate a z-score (standard score). 7.2 9.4.1.4 medium I can use z-scores to compare results for two different situations. 7.2 9.4.1.4 high I can explain what it means for a data point to be at a certain percentile. 7.2 9.4.1.4 high I can use z-scores (standard scores) and the characteristics of a normal distribution to estimate population percentages. 7.2 9.4.1.4 medium I can calculate probabilities for a normal distribution above, below, or between two data points. 7.2 9.4.1.4 low I can work backwards to find a piece of data given a percentile. 7.3 9.4.1.4