
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 retake 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
 retest 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:
 Ask questions in class.
 Read and study your notes.
 See me before or after school in the Math Resource Center for extra help.
 Work on homework with other students from class.
 Watch video tutorials (follow the link on my web page)
 Attend class every day.
Grading
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, LowLearning Targets
Approximate # of Days
Resources
Standards 2007 Benchmarks
Chapter 1
68 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 multistep situation to determine the number of outcomes for an event.
1.5
9.4.3.1
Chapter 2
810 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 2way 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
57 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
68 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, multistage 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
89 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 stemplot for a numerical data set, including splitstem plots.
5.3
9.4.1.1
high
I can interpret and describe a stemplot (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 5Number 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 boxplot for a numerical data set.
5.5
9.4.1.1
high
I can interpret and describe a boxplot (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 (sidebyside box plots and backtoback 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
67 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 bivariate 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 yintercept 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
56 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 (689599.7) to estimate probabilities and percentages about a normal distribution.
7.1
9.4.1.4
high
I can calculate a zscore (standard score).
7.2
9.4.1.4
medium
I can use zscores 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 zscores (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