1DA3 – Winter 2023
Commerce 1DA3
Business Data Analytics
Winter 2023 Course Outline
Operations Management Area
DeGroote School of Business
McMaster University
COURSE OBJECTIVE
This course provides an introduction to the application of inferential data analysis and statistics in decision-
making for business problems. Various data analytics concepts are discussed and used to address problems,
including probability concepts, interval and confidence estimation, hypothesis testing, analysis of variance,
simple and multiple linear regression, etc.
SCHEDULE AND CONTACT INFORMATION
C01: We 12:30PM – 01:20PM HSC 1A1
Mo 12:30PM – 01:20PM HSC 1A1
C02: Th 10:30AM – 11:20AM LRW B1007
Tu 10:30AM – 12:20PM LRW B1007
C03: Th 08:30AM – 09:20AM LRW B1007
Tu 08:30AM – 10:20AM LRW B1007
C04: Th 02:30PM – 03:20PM BSB 147
Tu 02:30PM – 04:20PM BSB 147
C05: We 08:30AM – 09:20AM HSC 1A1
Mo 08:30AM – 10:20AM HSC 1A1
T01: Fr 02:30PM – 03:20PM BSB 147
T02: Fr 08:30AM – 09:20AM HSC 1A1
T03: Fr 10:30AM – 11:20AM HSC 1A1
T04: Fr 12:30PM – 01:20PM HSC 1A1
T05: Th 12:30PM – 01:20PM CNH 104
All Sections: Teaching Assistants:
Dr. Behrouz Bakhtiari TBA on Avenue to Learn
Instructor announcement section.
Drop-in Hours
Wednesdays:
10:00AM – 11:00AM (DSB 232)
degroote.mcmaster.ca
, 1DA3 – Winter 2023
COURSE ELEMENTS
Credit Value: 3 Leadership: No IT skills: Yes Global view: Yes
A2L: Yes Ethics: Yes Numeracy: Yes Written skills: No
Participation: Yes Innovation: No Group work: No Oral skills: No
Evidence-based: Yes Experiential: Yes Final Exam: Yes Guest speaker(s): No
COURSE DESCRIPTION
The main emphasis will be on the applications of inferential data analysis in business. Students learn different
aspects of working with and making sense of data and learn how to use data to provide insight into different
business problems. Students in this course will engage with concepts from descriptive, diagnostic as well as
predictive analytics to address problems from different disciplines of business. Some examples include the
application of visualization, probabilities, confidence intervals, hypothesis testing, simple and multiple
regressions, etc. Application of data analysis and statistics techniques with spreadsheets (MS Excel) will also be
introduced in the course.
Numerous examples will illustrate the practical applications of statistical analysis in business. Emphasis will be
placed on connecting theory to real-world problems from different business disciplines.
LEARNING OUTCOMES
This course deals with basic statistical methods, in converting data into information, and further yet - into
knowledge. Primary focus is on business related data, but data coming from other sources (e.g., economic,
social, etc.) will also be explored, analyzed and discussed. Upon completion of the course, students will be able
to:
➢ understand, describe, summarize, visualize and interpret data (both qualitative and quantitative)
➢ understand randomness and basic probability concepts (random variables, probability density functions,
etc.)
➢ estimate, test and draw inferences about important characteristics of data
➢ identify the hypothesis that needs to be tested and conduct hypothesis testing
➢ understand output of different statistical analyses (outputs are usually similar regardless of the software used
to perform the analysis).
➢ Understand, test and draw inference on comparisons between parameters relating to two or multiple
populations
➢ understand correlation and measure the strength of linear correlation between variables.
degroote.mcmaster.ca
Commerce 1DA3
Business Data Analytics
Winter 2023 Course Outline
Operations Management Area
DeGroote School of Business
McMaster University
COURSE OBJECTIVE
This course provides an introduction to the application of inferential data analysis and statistics in decision-
making for business problems. Various data analytics concepts are discussed and used to address problems,
including probability concepts, interval and confidence estimation, hypothesis testing, analysis of variance,
simple and multiple linear regression, etc.
SCHEDULE AND CONTACT INFORMATION
C01: We 12:30PM – 01:20PM HSC 1A1
Mo 12:30PM – 01:20PM HSC 1A1
C02: Th 10:30AM – 11:20AM LRW B1007
Tu 10:30AM – 12:20PM LRW B1007
C03: Th 08:30AM – 09:20AM LRW B1007
Tu 08:30AM – 10:20AM LRW B1007
C04: Th 02:30PM – 03:20PM BSB 147
Tu 02:30PM – 04:20PM BSB 147
C05: We 08:30AM – 09:20AM HSC 1A1
Mo 08:30AM – 10:20AM HSC 1A1
T01: Fr 02:30PM – 03:20PM BSB 147
T02: Fr 08:30AM – 09:20AM HSC 1A1
T03: Fr 10:30AM – 11:20AM HSC 1A1
T04: Fr 12:30PM – 01:20PM HSC 1A1
T05: Th 12:30PM – 01:20PM CNH 104
All Sections: Teaching Assistants:
Dr. Behrouz Bakhtiari TBA on Avenue to Learn
Instructor announcement section.
Drop-in Hours
Wednesdays:
10:00AM – 11:00AM (DSB 232)
degroote.mcmaster.ca
, 1DA3 – Winter 2023
COURSE ELEMENTS
Credit Value: 3 Leadership: No IT skills: Yes Global view: Yes
A2L: Yes Ethics: Yes Numeracy: Yes Written skills: No
Participation: Yes Innovation: No Group work: No Oral skills: No
Evidence-based: Yes Experiential: Yes Final Exam: Yes Guest speaker(s): No
COURSE DESCRIPTION
The main emphasis will be on the applications of inferential data analysis in business. Students learn different
aspects of working with and making sense of data and learn how to use data to provide insight into different
business problems. Students in this course will engage with concepts from descriptive, diagnostic as well as
predictive analytics to address problems from different disciplines of business. Some examples include the
application of visualization, probabilities, confidence intervals, hypothesis testing, simple and multiple
regressions, etc. Application of data analysis and statistics techniques with spreadsheets (MS Excel) will also be
introduced in the course.
Numerous examples will illustrate the practical applications of statistical analysis in business. Emphasis will be
placed on connecting theory to real-world problems from different business disciplines.
LEARNING OUTCOMES
This course deals with basic statistical methods, in converting data into information, and further yet - into
knowledge. Primary focus is on business related data, but data coming from other sources (e.g., economic,
social, etc.) will also be explored, analyzed and discussed. Upon completion of the course, students will be able
to:
➢ understand, describe, summarize, visualize and interpret data (both qualitative and quantitative)
➢ understand randomness and basic probability concepts (random variables, probability density functions,
etc.)
➢ estimate, test and draw inferences about important characteristics of data
➢ identify the hypothesis that needs to be tested and conduct hypothesis testing
➢ understand output of different statistical analyses (outputs are usually similar regardless of the software used
to perform the analysis).
➢ Understand, test and draw inference on comparisons between parameters relating to two or multiple
populations
➢ understand correlation and measure the strength of linear correlation between variables.
degroote.mcmaster.ca
