Designed specifically for students in Commerce, this course enables students to learn and understand important concepts in statistics through applications in business and every-day life. Using a mastery learning approach, it also develops students’ mathematical skills and confidence, and competence in the use of Excel. Students may work at their own pace to complete the course independently of the class, providing deadlines are met.
This five minute video gives an outline of the nature of the course.
This course provides a foundation of statistics and mathematics from a business oriented user’s point of view. The emphasis is on sensible and correct use of statistical and mathematical tools in real-life problems and critical interpretation of quantitative reporting. It assumes fairly elementary levels of competence in mathematics. Microsoft Excel™ will be used as a tool within the course.
This course has been developed using the principles of Personalised System of Instruction, often known as the Keller plan. As the material is almost entirely based on skill development, this is best learnt at a mastery level. This means that students are expected to “master” the material, as shown by a pass cut-off mark of 80% for all assessed work.
We recognise that people learn at different rates, so students can sit the tests when they are ready for them, and if they do not pass, they can sit again when they feel they have mastered the material. In each section there is an open test that students can do in their own time, and a supervised test that students can do when they have passed any assignments or exercises and the open test for that section. The times available for sitting supervised tests are given on Learn. In order to help students plan their time better, there are deadlines for passing the sections. These are given below. Though there are sufficient testing slots available, it is unwise to leave testing to the last day. Students are permitted to miss two test deadlines (other than the final deadline) without failing the course.
As this is a 15 point course we expect students to spend about 150 hours on the course, which comes to 25 hours per week for a 6 week period. If you do this, you should pass the course. All materials and organisational details will be available through Learn. There are no face-to-face lectures, but rather the first hour timetabled below is a help session and the second hour is a testing session.
Students will be able to:
O1. Use Excel to perform simple calculations.
O2. Read two-dimensional tables correctly and calculate percentages.
O3. Place numbers in order, involving positive and negative numbers, fractions and decimals
O4. Use < and > signs correctly
O5. Rearrange simple algebraic expressions to follow the QMB algebra input protocol
S1. Calculate correctly using percentages, including percentage increase and decrease and GST.
S2. Solve problems using ratios.
S3. Solve problems using exchange rates.
S4. Demonstrate sensible rounding using decimal places and significant figures.
S5. Convert values to and from scientific notation (eg 3.2E6).
S6. Calculate using correct order of operations, including indices and parentheses.
S7. Solve problems involving Sigma (summation) notation.
S8. Create a simple Excel model using desired conventions (The Style Rules).
S9. Use Excel Help to learn about Excel functions.
M1. Convert word problems into algebraic form.
M2. Rearrange and simplify linear equations.
M3. Substitute values into algebraic expressions.
M4. Use Excel and/or algebra to solve linear problems.
M5. Interpret graphs, identifying slopes and intercepts.
M6. Recognise and explain the difference between fitted models and constructed models.
M7. Use Excel to find a line of best fit to bi-variate data and interpret it.
M8. Use Excel to draw graphs from algebraic functions.
M9. Identify trend and seasonality in time series data.
M10. Use index numbers.
M11. Identify appropriate graphs for displaying values.
C1. Recognise the different sources of probability estimates: a priori, frequency and subjective.
C2. Interpret statements of probability.
C3. Identify when events described in words are dependent or independent, mutually exclusive, collectively exhaustive.
C4. Answer questions involving conditional probability by constructing and using a frequency table.
C5. Identify a random variable, and specify whether it is discrete or continuous.
C6. Calculate the mean (expected value) of a random variable with a discrete distribution and interpret it.
C7. Use the Binomial distribution to solve problems, using Excel.
C8. Use the Poisson distribution to solve problems, using Excel.
C9. Use the Normal distribution to solve problems, using Excel.
C10. Solve problems involving a random variable with a discrete distribution.
D1. Identify levels of measurement in data - nominal, ordinal, interval/ratio.
D2. Use Excel to summarise data numerically.
D3. Interpret numerical statistics: mean, median, mode, standard deviation, range.
D4. Interpret and critique statistical graphs including bar, pie and histograms.
D5. Use Excel PivotTables and PivotCharts to summarise data and produce appropriate and correct graphs, including multiple bar/column graphs.
D6. Identify sampling methods, including random, systematic, convenience, cluster and stratified sampling and the limitations of each.
D7. Identify the effects of aspects of the sampling process, including sample size and composition, on the ability to generalise from the sample.
D8. Identify population data and sample data.
D9. Identify possible sources of variation in data: natural, sampling, explainable and bias.
D10. Use Excel to calculate a confidence interval of a mean.
D11. Explain the meaning and usefulness of a confidence interval.
D12. Calculate and interpret the confidence interval of a proportion.
E1. Explain the process underlying hypothesis tests.
E2. Interpret a p-value in context for a given set of hypotheses.
E3. Formulate a null and alternative hypothesis in words for problems involving means, proportions, differences of two means and differences of two proportions.
E4. Use Excel to perform a hypothesis test on one or two means and interpret the results.
E5. Use Excel to perform a hypothesis test on one or two proportions and interpret the results.
E6. Use Excel and PivotTables to perform a Chi-sq test on table data, or comparing with a given distribution, and interpret the results.
E7. Explain the concept of Type I and Type II errors and identify which (or neither) has occurred in a given situation.
E8. Use Excel to plot bi-variate data, find the correlation; interpret the output.
E9. Use Excel to fit a linear regression line; interpret the output.
E10. Evaluate the validity of statements about the nature of statistical thinking, including the concepts of causation, sample size, models, experimentation, statistical significance, effect size and subjectivity.
E11. Determine which test is most appropriate in a given situation, from: test for a mean or a proportion, difference between proportions, difference of two means: independent samples or paired data, chi-sq test for independence, regression.
Course Coordinator / Lecturer
The following gives the dates by which these quizzes must be passed. You may attempt them as soon as you have completed the prerequisites for them, namely the open tests, and any exercises or assignments. The time by which they must be completed is the end of the testing session on the day given (Monday, Wednesday or Friday). The course ends on 10 February.
Section O supervised test - Before end of Monday 9 January (Week 2)
Section S supervised test - Before end of Wednesday 11 January (Week 2)
Section M supervised test - Before end of Monday 16 January (Week 3)
Section C supervised test - Before end of Monday 23 January (Week 4)
Section D1 supervised test - Before end of Wednesday 25 January (Week 4)
Section D2 supervised test - Before end of Monday 30 January (Week 5)
Section E1 supervised test - Before end of Monday 6 February (Week 6)
Section E2 supervised test - Before end of Friday 10 February (End of term)
Final examination: There is an optional final examination held on 10 February.
A Pass grade is achieved when the student has passed all the section tests. Students may sit each test repeatedly until they pass. The Pass grade satisfies the requirements to use the course as a pre-requisite. Students who pass may choose to sit an optional final examination which will lead to a grade C to A+.
Students who do not complete all the sections may carry completed sections over for one additional enrolment in the course within two years. They will need to contact the course co-ordinator to arrange for their credit to carry over.
Relationship to Other Courses
This is a course in the quantitative skills and concepts useful for students majoring in a commerce subject. It is part of the Bachelor of Commerce core course requirements, and of the NZICA requirements for becoming a Chartered Accountant.
The following are provided to help you learn the material and skills:
• Tutorials: All students are expected to attend a timetabled weekly tutorial in a computer lab and bring headphones
• Videos or Audio of lectures, with notes
• Youtube videos developed for the course
• On-line readings
• Practice exercises on-line
• The open tests
• Email contact with the tutor or lecturer
There is no required textbook. Any readings will be given or referenced on Learn. If you have limited experience of the use of Microsoft Excel™, any “teach yourself” book on the subject will be helpful. There are many statistics textbooks available in the library. Students can use whichever ones prove most helpful if they need more resources for learning. There is an iPad app, AtMyPace:Statistics which students may find helpful.
Departmental Academic Policies
The Department assumes that you have read this document.
You should also read the General Course and Examination Regulations
Aegrotat consideration is not available for any items of assessment in this course.
The University of Canterbury considers cheating and plagiarism to be serious acts of dishonesty. All assessed work must be your own individual work unless specifically stated otherwise in the assessment guidelines. Material quoted from any other source must be clearly acknowledged. You must not copy the work of another person (student or published work) in any assessment including examinations, tests and assignments. Any person who is found to have copied someone else's work, or to have allowed their work to be copied, will receive a fail grade for that piece of assessment and may face disciplinary action which may lead to a fine, community service or exclusion from the university.
If an assignment submitted by you is found to have come from another person’s account you will face disciplinary action.
During supervised tests students may not gain access to other material either in or out of the Course Learn Site.
For further information see
All MSCI110 Occurrences