PROBABILITY AND STATISTICS - 442
2011 – 2012
Instructor: Mrs. Katie Godfrey
(302)654-2495 x 201
kgodfrey@salesianum.org
Website: http://faculty.salesianum.org/korga/
Phase 2
Course Description
½ Credit/semester
Grade 12
This course is designed for the student who wishes to examine real-life problems with real data through
elementary probability and statistics. It is taught for two marking periods. (It is usually joined with
Trigonometry-2, which is taught for the other two). Requiring only Algebra 1 and 2 as prerequisites, this
course is introductory in nature. The topics of probability include elementary probability theorems,
compound events, conditional probability, counting methods, and the normal distribution. Statistical
topics include organizing data graphically and analysis of data numerically. Students will also describe
the relationship between two variables. Probability and Statistics is recommended for students desiring to
continue their education in fields of business, economics, accounting, marketing, or statistics.
Text
Discovering Statistics, Brief Version
Daniel Larose, W.H. Freeman Publishing
Syllabus
First Quarter
Chapter 1: The Nature of Statistics
Chapter 2: Describing Data Using Graphs and Tables
Chapter 3: Describing Data Numerically
Second Quarter
Chapter 4: Describing the Relationship Between Two Variables
Chapter 5: Probability
Chapter 6: Random Variables and the Normal Distribution
Final Exam
The “Final Exam” will be an in-class project applying the objectives of the course.
Assignments
Students are assigned problems following each section. Students also engage in laboratories, computer assignments
on Excel and Minitab, and other related activities pertaining to the objectives listed below.
Students must turn in the assignment when it is due or they will not receive credit. If a student is absent it is their
responsibility to make up the work, but I do not check the missed assignment in this case. If a student misses a quiz
or test they have 48 hours to make it up or he receives a zero.
Grading Policy
To calculate your quarter grade, simply divide the number of points you have earned by the total number of points
that you could have earned at that time in the quarter.
Your final average for the semester will be based on your numerical grades from each of the four quarters and from
your final exam.
Grading Scale
A
100-92.5
B+
92-88.5
B
88-84.5
C+
84-80.5
C
80-76.5
D+
76-72.5
D
72-69.5
F
69-0
Your quarterly grade will be comprised of the following components:
√ GAMEDAY – Your tests will generally be free response and partial credit is awarded so it is best to
show your work.
√ SCRIMMAGES – Quizzes will also be free response, but can be unannounced.
√ PRACTICES – This includes class work, laboratories, and homework assignments. I will check your
homework each time it is assigned. For every three homeworks not completed a student’s grade level will
drop. It is always best to complete all assignments.
√ PARTICIPATION/SPORTSMANSHIP - Asking and answering questions during class will be noted.
Board work and group work will also be taken into account. This is based on focus, pride of work, ability to
work with others, being prepared, and contributing to discussions.
√ EXTRA POINT - I will have extra problems or projects available for all students.
Classroom Policy
 During tests and quizzes I will only clarify the directions, unless there is an error on the test paper.
 Make up policy: All tests and quizzes must be made up 48 hours upon your return from an absence
(barring exceptional circumstances). After that, a grade of zero will be issued for any missing work.
 If school is canceled (due to snow, etc.), whatever was planned on the canceled day will be done on the
day we come back (tests, quizzes, homework, etc.).
 Honor Code Policy: Your work in this class is your personal property. Academic integrity is the
expectation of every Salesianum student. Any student who jeopardizes this by plagiarism, cheating, or
taking another’s work will be held to the consequences of the Honor Code Policy. Please see pages 16-19
in the Student Handbook.
 Only students with a note from Mrs. Gardner may receive extended time on tests.
 You must tell me each time you wish to use extended time on a test. I must know before you begin. If
you do not tell me before you begin the test, you may not use it on that test.
 If you choose to use extended time, you must finish the test after school the same day.
 To obtain information for the class please use my website found through the Salesianum website in the
Faculty Directory link. Homework assignments and projects will be posted on my website.
FAWeb/Netclassroom will be updated weekly with grades and upcoming tests/quizzes.
 If a student fails Prob/Stat he will need to make up the credit through an outside summer course or
through a private tutor and cannot graduate. The student will also be ineligible for school activities
including athletics. A student must have a passing grade of D or above to graduate.
Course Objectives
On the completion of this course the student should be able to:
1) Realize that behind each data set lies a story about real people undergoing real life experiences.
2) Describe what statistics is.
3) State the meaning of descriptive statistics.
4) Understand that inferential statistics refers to learning about a population by studying a sample from that population.
5) Explain what a random sample is, and why we need one.
6) Identify other sampling methods.
7) Explain the main factors that go into designing a good questionnaire.
8) Understand the difference between an observational study and an experiment.
9) Construct and interpret a frequency distribution and a relative frequency distribution for qualitative data.
10) Construct and interpret bar graphs and Pareto Charts.
11) Construct and interpret pie charts.
12) Construct and interpret a frequency distribution and a relative frequency distribution for quantitative data.
13) Use histograms and frequency polygons to summarize quantitative data.
14) Construct and interpret stem-and-leaf displays and dotplots.
15) Recognize distribution shape, symmetry, and skewness.
16) Build cumulative frequency distributions and cumulative relative frequency distributions.
17) Create frequency ogives and relative frequency ogives.
18) Construct and interpret time series graphs.
19) Understand what can make a graph misleading, confusing, or deceptive.
20) Calculate the mean for a given data set.
21) Find the median, and describe why the median is sometimes preferable to the mean.
22) Find the mode of a data set.
23) Describe how skewness affects these measures of center.
24) Understand and calculate the range of a data set.
25) Explain in my own words what a deviation is.
26) Calculate the variance and the standard deviation for a population or a sample.
27) Calculate the weighted mean.
28) Estimate the mean for grouped data.
29) Estimate the variance and standard deviation for grouped data.
30) Find percentiles for both small and large data sets.
31) Calculate z-scores, and explain why we use them.
32) Use z-scores to detect outliers.
33) Calculate percentages using Chebyshev’s Rule.
34) Find percentages and data values using the Empirical Rule.
35) Find quartiles and the interquartile range.
36) Calculate the five-number summary of a data set.
37) Construct a boxplot for a given data set.
38) Apply robust detection of outliers.
39) Construct and interpret crosstabulations for two categorical variables.
40) Construct and interpret clustered bar graphs for two categorical variables.
41) Construct and interpret scatterplots for two quantitative variables.
42) Calculate and interpret the value of the correlation coefficient.
43) Calculate the value and understand the meaning of the slope and the y intercept of the regression line.
44) Predict values of y for given values of x.
45) Explain prediction error, calculate SSE, and utilize the standard error s as a measure of a typical prediction error.
46) Describe how total variability, prediction error, and improvement are measured by SST, SSE, and SSR.
47) Explain the meaning of r2 as a measure of the usefulness of the regression.
48) Understand the meaning of an experiment, an outcome, an event, and a sample space.
49) Describe the classical method of assigning probability.
50) Explain the Law of Large Numbers and the relative frequency method of assigning probability.
51) Understand how to combine events using complement, union, and intersection.
52) Apply the Addition Rule to events in general and to mutually exclusive events in particular.
53) Calculate conditional probabilities.
54) Explain independent and dependent events.
55) Solve problems using the Multiplication Rule.
56) Recognize the difference between sampling with replacement and sampling without replacement.
57) Apply the Multiplication Rule for Counting to solve certain counting problems.
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Use permutations and combinations to solve certain counting problems.
Compute probabilities using combinations.
Identify random variables.
Explain what a discrete probability distribution is and construct probability distribution tables and graphs.
Calculate the mean, variance, and standard deviation of a discrete random variable.
Explain what constitutes a binomial experiment.
Compute probabilities using the binomial probability formula.
Find probabilities using the binomial tables.
Calculate and interpret the mean, variance, and standard deviation of the binomial random variable.
Identify a continuous probability distribution.
Explain the properties of the normal probability distribution.
Find areas under the standard normal curve, given a Z-value.
Find the standard normal Z-value, given an area.