INT202 - Statistics
Semester | |
School | |
Last revision date | 2018-07-16 00:00:02.758 |
Last review date | 2018-07-20 13:52:52.989 |
Subject Title
Statistics
Subject Description
This course provides an introduction to basic statistical concepts and techniques that are common to various disciplines. Statistical methods of data collection, analysis, presentation and interpretation for making generalizations, projections and decisions will be introduced. Both descriptive and inferential techniques will be explored.
Credit Status
Required mathematics course for students in the Bachelor of Interdisciplinary Studies degree program
Learning Outcomes
Upon successful completion of this subject the student will be able to:
- Demonstrate the ability to present, describe and summarize data using graphic representations, measures of central tendency and variation.
- Evaluate probabilities by defining sample spaces and through the use of probability rules, including mutually exclusive and independent cases.
- Distinguish between discrete and continuous random variables and determine expected value and standard deviation of a discrete random variable and binomial probability distribution.
- Determine the probability of intervals on a normal distribution using z-scores and a normal distribution table.
- Calculate the mean and standard error of a random variable and probabilities for a given sample mean using the Central Limit Theorem.
- Use sample data to determine confidence intervals for the mean and proportion of populations.
- Construct a test of hypothesis of a mean or proportion by indicating the null and alternative hypothesis, identifying and calculating the test statistic, and drawing appropriate conclusions.
- Perform simple regression and correlation analysis by determining and interpreting the correlation coefficient, the coefficient of determination and the coefficients of the sample regression line.
- Use a regression equation to predict the value of the dependent variable for a selected value of the independent variable and conduct a test of hypothesis for the coefficient of correlation and each coefficient of regression.
- Determine and interpret confidence intervals and prediction intervals for the dependent variable.
Essential Employability Skills
Execute mathematical operations accurately.
Apply a systematic approach to solve problems.
Use a variety of thinking skills to anticipate and solve problems.
Manage the use of time and other resources to complete projects.
Take responsibility for one's own actions, decisions, and consequences.
Cheating and Plagiarism
Each student should be aware of the College's policy regarding Cheating and Plagiarism. Seneca's Academic Policy will be strictly enforced.
To support academic honesty at Seneca College, all work submitted by students may be reviewed for authenticity and originality, utilizing software tools and third party services. Please visit the Academic Honesty site on http://library.senecacollege.ca for further information regarding cheating and plagiarism policies and procedures.
Discrimination/Harassment
All students and employees have the right to study and work in an environment that is free from discrimination and/or harassment. Language or activities that defeat this objective violate the College Policy on Discrimination/Harassment and shall not be tolerated. Information and assistance are available from the Student Conduct Office at student.conduct@senecacollege.ca.
Accommodation for Students with Disabilities
The College will provide reasonable accommodation to students with disabilities in order to promote academic success. If you require accommodation, contact the Counselling and Disabilities Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.
Prerequisite(s)
INT100 or permission of the coordinator
Topic Outline
- Statistical Concepts; Data Measurement; Graphic Description of Data
- Measures of Central Tendency: Raw and Grouped Data
- Measures of Variation: Raw and Grouped Data; Measures of Relative Standing
- Introduction to Probability
- Probability Rules
- Discrete Probability Distribution; Normal Probability Distribution
- Central Limit Theorem; Statistical Estimation
- Statistical Estimation; Introduction to Hypothesis Testing
- Hypothesis Testing
- Simple Regression Analysis
- Correlation
Prescribed Texts
See Professor's Addendum for information.
Promotion Policy
A+ | 90% to 100% |
A | 80% to 89% |
B+ | 75% to 79% |
B | 70% to 74% |
C+ | 65% to 69% |
C | 60% to 64% |
D+ | 55% to 59% |
D | 50% to 54% |
F | 0% to 49% (Not a Pass) |
OR | |
EXC | Excellent |
SAT | Satisfactory |
UNSAT | Unsatisfactory |
For further information, see a copy of the Academic Policy, available online (http://www.senecacollege.ca/academic-policy) or at Seneca's Registrar's Offices.
Modes of Evaluation
Term Work
GRADING SCHEME
Classroom | Online | ||
Tests (x2) | 20% | Discussion Posts (x3) | 30% |
Mid-Term Exam | 20% | Interactive Exercises (x3) | 30% |
Assignments | 35% | Major Data Project | 40% |
Final Exam | 25% |
To be successful in this course, you must complete all course work as specified, and achieve an overall grade of 50% or more. It is expected that students have a sufficient command of the English language to express themselves clearly in both written assignments and class discussions. For further information on evaluation and academic standing, see the Academic Policy at http://www.senecacollege.ca/academic-policy.
For online delivery: All Seneca College academic policies apply. This includes, but is not limited to policies related to grading, supplemental exams, deferred exams and accommodations. Students must achieve a final grade of 50% in order to pass the course.