bus5qda quantitative data analysis
QUANTITATIVE DATA ANALYSIS
BUS5QDA
Not currently offered
Credit points: 15
Subject outline
In this subject, you will develop your quantitative data analysis skills and learn techniques which are commonly used by researchers to answer important questions and by senior managers in making informed business decisions. Topics in the first component of this subject include; descriptive statistics, probability distributions, parametric estimation methods, parametric and non-parametric hypothesis tests, and both simple and multiple regression analysis. In addition to the linear regression modelling, the subject will cover panel data analysis. This knowledge will then be extended with advanced techniques including limited dependent variable models such as logit, probit models, ordered probit and tobit. Authentic assessments in this subject will promote critical thinking, problem solving and inquiry whilst strengthening your analytical, report writing and communication skills.
SchoolLa Trobe Business School (Pre 2022)
Credit points15
Subject Co-ordinatorMuhammad Al Mamun
Available to Study Abroad/Exchange StudentsNo
Subject year levelYear Level 5 - Masters
Available as ElectiveNo
Learning ActivitiesLectures, labs sessions, online videos, readings, group discussions, and assessment tasks, interactive lab session, research articles.
Capstone subjectNo
Subject particulars
Subject rules
Prerequisites Students must be admitted in one of the following courses: LHCOM, LDPH or Students must have completed BUS1BAN
Co-requisitesN/A
Incompatible subjectsN/A
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Career Ready
Career-focusedNo
Work-based learningNo
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Subject options
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