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Quantitative Analysis
This course is designed to equip candidates with the essential knowledge, skills, and attitudes necessary to effectively use quantitative analysis ...
tools in business operations and decisionmaking. Through a comprehensive exploration of mathematical techniques, set and probability theories, operational research, hypothesis testing, and linear programming, candidates will gain the ability to solve complex business problems and make informed decisions.
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 Description
 Curriculum
 Reviews
This course is designed to equip candidates with the essential knowledge, skills, and attitudes necessary to effectively use quantitative analysis tools in business operations and decisionmaking. Through a comprehensive exploration of mathematical techniques, set and probability theories, operational research, hypothesis testing, and linear programming, candidates will gain the ability to solve complex business problems and make informed decisions.
Learning Outcomes
Upon successful completion of this course, candidates will be able to:
 Use Mathematical Techniques to Solve Business Problems: Apply various mathematical methods to analyze and solve problems encountered in business settings.
 Apply Set and Probability Theories in Business Decision Making: Utilize set theory and probability principles to assess risk and make strategic business decisions.
 Apply Operation Research Techniques in Decision Making: Implement operational research methods to optimize business processes and improve decisionmaking.
 Apply Hypothesis Testing in Analyzing Business Situations: Conduct hypothesis tests to interpret data and derive meaningful insights in business contexts.
 Apply Linear Programming to Solve Practical Business Problems: Use linear programming models to find optimal solutions for resource allocation and other business challenges
Functions

1FunctionsVideo lesson

2EquationsVideo lesson

3InequalitiesVideo lesson

4Linear EquationsVideo lesson

5Quadratic EquationsVideo lesson

6Cubic FunctionsVideo lesson

7Exponential FunctionsVideo lesson

8logarithmic functionsVideo lesson

9Application of mathematical functionsVideo lesson
Matrix Algebra
Calculus

17DifferentiationVideo lesson

18Rules of differentiationVideo lesson

19Differentiation of exponential FunctionsVideo lesson

20Differentiation of logarithmic functionsVideo lesson

21Turning pointsVideo lesson

22Application of differentiation to business problemsVideo lesson

23IntegrationVideo lesson

24Rules of integrationVideo lesson

25Integration of exponential functionsVideo lesson

26Integration of Logarithmic functionsVideo lesson

27Applications of integration to business problemsVideo lesson
Descriptive Statistics

28Arithmetic meanVideo lesson

29Weighted arithmetic meanVideo lesson

30Geometric meanVideo lesson

31Harmonic meanVideo lesson

32Median and modeVideo lesson

33Range, quartile, deciles, percentiles & mean deviationVideo lesson

34Standard deviationVideo lesson

35Coefficient of variationVideo lesson

36Pearsonâ€™s coefficient of skewnessVideo lesson

37Product coefficient of skewnessVideo lesson

38Pearsonâ€™s coefficient of kurtosisVideo lesson

39Product coefficient of kurtosisVideo lesson
Probability

40IntroductionVideo lesson

41Operations of setsVideo lesson

42Venn diagramsVideo lesson

43Probability TheoryVideo lesson

44Types of eventsVideo lesson

45Laws of probabilityVideo lesson

46Conditional probabilityVideo lesson

47Probability treesVideo lesson

48Application of probabilityVideo lesson

49Discrete and continuous probability distributionsVideo lesson

50Application of probability distributionsVideo lesson
Hypothesis Testing and Estimation

51The arithmetic meanVideo lesson

52Standard deviationVideo lesson

53Hypothesis tests on the meanVideo lesson

54Hypothesis tests on proportionsVideo lesson

55Hypothesis tests on the difference between two proportionsVideo lesson

56ChiSquare tests of goodness of fit and independenceVideo lesson

57Hypothesis testing using R statistical softwareVideo lesson
Correlation and Regression Analysis

58Correlation AnalysisVideo lesson

59Measures of correlationVideo lesson

60Using R softwareVideo lesson

61Regression AnalysisVideo lesson

62Assumptions of linear regressionVideo lesson

63Coefficient of determinationVideo lesson

64Standard error of the estimateVideo lesson

65Standard error of the slopeVideo lesson

66t and F statisticsVideo lesson
Time series
Linear programming
Course details
Duration
3 Months
Lectures
81
Video
45 hours
Level
Foundation
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Working hours
Monday  9:30 am  6.00 pm 
Tuesday  9:30 am  6.00 pm 
Wednesday  9:30 am  6.00 pm 
Thursday  9:30 am  6.00 pm 
Friday  9:30 am  5.00 pm 
Saturday  Closed 
Sunday  Closed 