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MATH399N Applied Managerial Statistics

The location in relation to the above said coursework or module can be said to be Chamberlain College of Nursing. The study level in relation to the above said module or coursework can be said to be graduate level. The unit code in relation to the above stated module can be said to be MATH399N.

The following can be said to be the primary Learning outcomes of the above said module: -

  1. Produce adequate graphical as well as numerical descriptive statistics in relation to the different kinds of the data.

  2. Make an application of the probability rules as well as the concepts in connection to the discrete as well as the continuous random variables in order to answer the questions in any business context.

  3. Demonstrate or show the knowledge of the significance of the specific ‘Central Limit Theorem’ (also known as CLT) as well as its applications.

  4. Conduct as well as interpret a series of the hypothesis tests in order to aid the decision making in any business context.

  5. Utilize the simple/multiple regression models in order to analyse the underlying and fundamental relations amidst the variables with the help of the hypothesis testing.

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Managerial Statistics

The Decision-making can be said to be at the very core or heart of the management. In the specific Digital Age, there can be said to have been an abundance of the data available on the consumer actions, the motivations as well as the objectives that could be utilized in order to improve the managerial decision-making. The managerial statistics permits a person to draw the conclusions on the basis of the sample data, in order to test the portfolio strategies, in order to test for the managerial bias, as well as in order to estimate the product or the service reliability.  The above said module or coursework actually covers the essential or fundamental tools as well as the concepts in relation to the statistics as they are applied in relation to the management: the causation, the descriptive statistics, the exploratory data analysis, the sampling, the statistical relations, as well as the statistical inference. The students who might be able to complete the above said module or coursework shall be able to acquire a detailed understanding in relation to the basic statistical measures as well as analyses, as well as any proficient grasp of the regression as any data-analytic methods that are utilized daily in the business. 

It is important to note that in the above said module or coursework, the ‘Course Hours’ can be said to be approximately 15 to 30 hours.

  • Learning Goals

The above said module or coursework has been designed and shaped in order to develop the essential and fundamental knowledge as well as skills for the leveraging of the statistics in dealing with the present management challenges. The methods in the above said module or coursework actually include the descriptive statistics, the probability distributions, the sampling, the confidence intervals, the hypothesis testing as well as the utilization of the SAS computer software for the statistical applications. The topics in the above said module or coursework are actually organized around the practical case studies of the business analytics in an extensive variety of the industries.

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    The following can be said to be the Learning Outcomes of the above said module: -

Upon the successful completion and conclusion of the above said module or coursework, the specific students shall gain the ability to: -

  • Understand or comprehend the statistical skills that are mandated in the management today

  • Explore the best practices in the managerial decision making

  • Propose any particular framework for the improvement of the data-based procedures in the specific organizations

  • Analyse as well as evaluate pr assess the limitations in relation to the business analysis

  • Given any specific research question, articulate or formulate the appropriate hypotheses, choose the test statistics, then describe the particular evaluation criteria, and afterwards draw an adequate or a suitable business conclusion

  • The concepts as well as the theories in relation to which the students are actually exposed in the course of the above said module or coursework

§ The Confidence intervals

§ The Data distributions

§ The Data Dashboards

§ The Decision Models

§ The Hypothesis testing

§ The Portfolio Management

§ The Probability

§ The Regression Analysis

§ The Sampling

§ The Statistical Inference

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Following can be said to be the Course Objectives (which are the further Student Learning Outcomes)

The primary objective of the above said module or coursework can be said to provide a specific understanding for the particular graduate business student in relation to the statistical concepts in order to include the measurements regarding the location as well as the dispersion, the probability, the probability distributions, the sampling, the estimation, the hypothesis testing, the regression, as well as the correlation analysis, the multiple regression as well as the business/economic forecasting. Upon the completion or the conclusion of the above said module or coursework, the student or the learner shall be able to learn to actually perform the following: -

1) The manner in which the measures in relation to location as well as the measures in relation to dispersion (grouped as well as ungrouped data cases) could be calculated as well as applied.

2) the manner in which the discrete as well as the continuous probability distributions could be applied in relation to the various business problems.

3) Perform the Test relating to the Hypothesis as well as compute the confidence interval for any population parameter for the single sample as well as the 2 sample cases.

4) Learn the non-parametric test like the Chi-Square test in relation to the Independence as well as the Goodness of the Fit.

5) Compute as well as interpret the specific results of the ‘Bivariate and Multivariate Regression and Correlation Analysis’, for the forecasting and certainly perform the ANOVA as well as the F-test.

Weightage of the MATH399N Code:

The weightage is 100 per cent.

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