Demonstrate the value of inferential statistics and statistical modeling in the context o

The objective here is to explore the database attached (with Michael Jordan’s career numbers playing the regular NBA season with the Bulls and Wizards). Corelate this data creating “managerial questions” and explaining them
demonstrating the value of inferential statistics and statistical modeling in the context of Management Decision Support Systems. It encompasses model conceptualization, development, inferential assessment, interpretation and implementation within a management context.

Formulate 2 (mininum – make it 3 or 4) questions, but related, meaningful (non-trivial) management questions to which appropriate statistical techniques from the areas of inferential statistics and predictive modeling can be applied.

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Decision Making based on Confidence Interval Estimation
– The foundations of Inferential Analysis
(Descriptive Statistics; Probability; Sampling; Sampling Distributions)
– Confidence Interval Estimation
Application Discussion -Statistical Quality Control and Quality Control Chart

Decision Making through Hypothesis Testing
– The Hypothesis Testing Process and Concepts:
The concept of Hypothesis Testing (Type I and Type II Errors)
One-sided tests, Two sided tests, Level of Significance, p-value
– One Sample Scenarios:
One Sample Test (Means, Proportions, Variance)

Decision Making through Hypothesis Testing
– Two Sample Scenarios:
Difference in Means (Independent Samples and Paired Samples)
Equality of Variances (Two Populations)

Decision Making through Hypothesis Testing
– Multiple Sample Scenarios (Means and Proportions)
Proportions: Chi square Tests of Association, Test for Equality of Multiple Proportions and Test for Independence of Association
Means: Analysis of Variance (Multiple Comparison of Means) One Factor ANOVA

Decision Making through Hypothesis Testing
– Multiple Sample Scenarios (Multiple Means Across Segmented Samples)
Analysis of Variance (Multiple Comparison of Means)
Two-f actor ANOVA with Interaction Effect

Statistical Modeling – The Regression Approach
Simple Linear Regression Analysis – Basic Concepts and Model Building
Developing and Interpreting Simple Linear Regression Models
Testing the Significance of a Simple Linear Regression Model


Application Discussion -Statistical Quality Control and Quality Control Charts

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