Dr Patrick TOCHE, Department of Finance & Decision Sciences

Probability the year ends well (Spain)

BUSI3007 - Business Research Methods
Dr Patrick TOCHE (Coordinator) 
    Office WLB514, Department of Finance and Decision Sciences, 
    The Baptist University of Hong Kong, 
    34 Renfrew Rd, Kowloon Tong, Hong Kong SAR.
    Contact: patricktoche@hkbu.edu.hk
    Office Hours: See below


The aim of this course is to introduce students to research methods. Material for the course will be uploaded here as it becomes available.

1. On Being Late to Class

You may enter the classroom within 15 minutes of the starting time under these conditions: Make eye contact and wave a discrete hand of apology as you enter the classroom. After the 15-minute tolerance period, wait for the next class break to enter (at half past the hour every hour). 

2. Timetable & Syllabus 

Dr Patrick TOCHE, Department of Finance & Decision Sciences
[PDF]   Course calendar week by week (Labs are in DLB303)
[PDF]   Course weekly timetable with office hours 
[PDF]   Course calendar week by week (single page summary)
[PDF]   University academic calendar 
[PDF]   Course syllabus and topics
[PDF]   Course learning outcomes
[PDF]   Course template


1. In-Class Midterm

Date: Saturday 2nd March 2019 at 2:00pm. 
Open book. No smartphones. No internet access. Only a simple calculator will be allowed. Duration 2 hours. In case of an absence, your final exam grade will be used as a midterm grade. I will stop answering questions about the midterm three days before the deadline. MC sheets that do not pass the scanner will be manually graded at the end of the semester. Fill out the multiple-choice sheets properly. Use a gray pencil, not a pen. Examples of invalid multiple-choice sheets: [1[2[3]. Topics covered: 1, 2, 3, 4, 5 from the list below. Please see your classroom assignment. Midterm directory:  [MIDTERM

2. Take-Home Project

Date: Monday 1st April 2019, 6:20pm in the classroom,
 exact time or earlier MUST BE HANDED TO ME IN PERSON.  Please contact me in person if you have any questions about the project (see my timetable).  I will not answer questions submitted by email.  I will stop answering questions about the project three days before the deadline. The questions will be uploaded about 4 weeks before the deadline, shortly after the midterm. Project directory:  [PROJECT]

3. Participation   [10%]

Participation in class, in the labs, and evidence of effort is rewarded. I may monitor participation at random times (especially during lab sessions). Do not confuse participation with attendance. I do not monitor attendance and do not reward it. 
Do take participation seriously as it can mark the difference between a B+ and an A-. Participation marks will be available at the end of the semester.

4. Final   [50%]

Date: Tuesday 7th May 2019, 9:00am-11:00am.  This is a closed-book examination. Only a simple calculator will be allowed. Bring your own calculator. All topics covered in class are examinable. See from the list below for the full list. R
efer to end-of-chapter problems and to the model answers for examples. The examination layout is based on this sample [PDF] with answer sketches [PDF]. See the Appendix with tables and formulas at the end. I will stop answering questions about the final three days before the examination. Last Questions/Answers session scheduled for Tuesday 30th April 2019, 2:00pm in DLB-719.

5. Grades   [100%]

Course grades are letter grades from the following categories: A, A-, B+, B, B-, C+, C, C-, D, F. They will be finalised at the end of the semester after an audit and departmental review. Partial grades will be made available for some of the course components (see password-protected 'anonymous' PDF files). Grades directory: [GRADES]

LECTURES [Handout + Slides + Problems + Labs]


1.    Introduction to Statistics

       [Handout]   [Slides]   [Problems]   [Lab]

2.    Probability - Basic Concepts & Rules

       [Handout]   [Slides]   [Problems]   [Lab]

3.    Data - Frequency Tables & Histograms

       [Handout]   [Slides]   [Problems]   [Lab]

4.    Data - Centrality & Dispersion

       [Handout]   [Slides]   [Problems]   [Lab]

5.    Data - Asymmetry & Quantiles

       [Handout]   [Slides]   [Problems]   [Lab]

6.    Probability - Discrete Distributions

       [Handout]   [Slides]   [Problems]   [Lab

7.    Probability - Continuous Distributions

       [Handout]   [Slides]   [Problems]   [Lab

8.    Methods - Sampling & Inference

       [Handout]   [Slides]   [Problems]   [Lab

9.   Estimation - Confidence Intervals

       [Handout]   [Slides]   [Problems  [Lab] 

10.   Estimation - Hypothesis Testing

       [Handout]   [Slides]   [Problems]   [Lab] 

11. Estimation - Statistical Correlation

       [Handout]   [Slides]   [Problems]   [Lab] 

12.  Estimation - Simple Regression

       [Handout]   [Slides]   [Problems]   [Lab] 

13.  Estimation - Multiple Regression

       [Handout]   [Slides] 

++   Revision - Summary & Cheatsheets



    Distributions: Explore barcharts, histograms, density lines

       [Local]   [Online]  


1b.  Introduction to R

       [Get Started]   [Get Data]  

8b.  Methods - Data Collection & Survey Design

       [Handout]   [Slides]   [Problems]   [Videos

13.  Econometric Applications




Model answers and raw scores for the midterm will be provided in anonymous files. The password will be communicated in person only. You may not circulate the model answers on websites or via email. Raw scores for the project will also be uploaded in an anonymous file. But the participation and final examination grades will not. I will broadcast a message via Moodle when the scores are available. Please get back to me about problems as soon as the grades are made available. Numeric grades are computed from your raw scores (with weights for each component) and then converted to letter grades according to the Department's conversion scale. Grades are then reviewed by the Department and released after the end of the semester.  Typically a very small percentage of students fail the course. This usually happens because they give up in the middle of the semester and stop participating and submitting assignments. If you choose to drop out of the course, do it by the deadline. On rare occasions students have failed because their performance in the final examination was very poor (the final examination accounts for 50% of the total grade). While most students should be able to pass the course, getting a B is not automatic and getting an A is quite demanding. The Department's guidelines are that there should be no more than 25% of grades in the A-range (A and A-). Last semester about 1/4 of the students received a grade in the A range, 1/2 in the B range and 1/4 in the C range. See this summary [PDF]. All the best!






1. Main Textbook
Douglas A. Lind, William G Marchal, Samuel A. Wathen, Statistical Techniques in Business and Economics, The McGraw-Hill/Irwin Series in Operations and Decision Sciences, 17th edition (2017), 978-1259666360. My lectures roughly follow this textbook.

2. Other Textbook
William G. Zikmund, Barry J. Babin, Jon C. Carr, Mitch Griffin, Business Research Methods, South-Western, 9th edition (2013), 978-1439080672. This covers the "survey design" topic in detail. My lectures do not use this textbook. 


1. Applewood Auto Group Dataset

   [Applewood.xlsx]   Lind, 17th edition

2. Major League Baseball Dataset

   [Major_League_Baseball_2016.xlsx]   Lind, 17th edition

3. North Valley Real Estate Dataset

  [Real_Estate.xlsx]   Lind, 17th edition

4. American Society of PeriAnesthesia Nurses

  [Aspan_Membership.xls]   Lind, 15th edition   

5. McGivern Jewellers Dataset

  [McGivern_Jewellery.xls]   Lind, 15th edition


You are welcome to switch sessions, subject to space in the classroom. Naturally students who are actually enrolled in the session will be given priority. 

Mon 15:30 - 18:20 : WLB208  + DLB303 (Labs)
Tue  09:30 - 12:20 : DLB719  + DLB303 (Labs)
Wed 09:30 - 12:20 : DLB719  + DLB303 (Labs)
Wed 14:30 - 17:20 : DLB719  + DLB303 (Labs)
Thu  09:30 - 12:20 : WLB206  + DLB303 (Labs)
Thu  15:30 - 18:20 : WLB206  + DLB303 (Labs)


Please help me adhere to the following time management. Thanks!

09:30 - 12:20 Sessions
09:30  Start
10:20  Break 1
10:30  Re-start
11:20  Break 2
11:30  Re-start
12:20  Stop

12:30 - 15:20 Sessions
12:30  Start
13:20  Break 1
13:30  Re-start
14:20  Break 2
14:30  Re-start
15:20  Stop

14:30 - 17:20 Sessions
14:30  Start
15:20  Break 1
15:30  Re-start
16:20  Break 2
16:30  Re-start
17:20  Stop

15:30 - 18:20 Sessions
15:30  Start
16:20  Break 1
16:30  Re-start
17:20  Break 2
17:30  Re-start
18:20  Stop