Statistic for Management 8th Edition by Levin Richard, Siddiqui Masood, Rubin David, Rastogi Sanjay ISBN 8184957491 9788184957495

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Product details:
ISBN 10: 8184957491
ISBN 13: 9788184957495
Author: Levin Richard, Siddiqui Masood, Rubin David, Rastogi Sanjay

provides a comprehensive introduction to the concepts and applications of statistics in business and management. The textbook covers essential statistical techniques and methodologies used to analyze and interpret data for decision-making in business contexts. It emphasizes practical applications through real-world examples, helping students and professionals understand how statistical tools can be used to improve business processes, optimize operations, and make informed decisions. The 8th edition is updated with new examples, case studies, and statistical software tools to reflect current trends in business analytics and data-driven decision making.

Statistic for Management 8th Edition Table of contents:

Chapter 1: Introduction to Statistics and Statistical Thinking

• Definition and Importance of Statistics
• Types of Data: Qualitative vs. Quantitative
• Overview of Statistical Methods
• The Role of Statistics in Management Decision Making

Chapter 2: Descriptive Statistics: Organizing and Summarizing Data

• Frequency Distributions and Graphs
• Measures of Central Tendency: Mean, Median, Mode
• Measures of Dispersion: Range, Variance, Standard Deviation
• Measures of Position: Percentiles, Z-Scores

Chapter 3: Probability and Probability Distributions

• Introduction to Probability Theory
• Basic Probability Rules
• Random Variables and Probability Distributions
• The Binomial and Normal Distributions
• The Central Limit Theorem

Chapter 4: Sampling and Sampling Distributions

• Sampling Techniques and Methods
• Sampling Distribution of the Sample Mean
• The Law of Large Numbers
• Estimation Using Sampling Distributions

Chapter 5: Estimation: Confidence Intervals

• Point Estimates and Interval Estimates
• Confidence Intervals for the Population Mean
• Confidence Intervals for Proportions
• Sample Size Determination

Chapter 6: Hypothesis Testing

• The Logic of Hypothesis Testing
• Types of Hypotheses: Null and Alternative
• Types of Errors: Type I and Type II
• Testing for Population Mean, Proportions, and Variances
• P-Value Approach and Critical Value Approach

Chapter 7: Comparison of Two Population Means and Proportions

• Independent and Paired Samples
• Hypothesis Testing for Two Population Means
• Testing Differences Between Two Proportions
• Confidence Intervals for Two Means

Chapter 8: Analysis of Variance (ANOVA)

• The Concept of ANOVA
• One-Way ANOVA: Testing for Equality of Means
• Two-Way ANOVA: Interaction Between Factors
• Post-Hoc Testing and Interpretation of Results

Chapter 9: Chi-Square Tests

• Chi-Square Test for Goodness of Fit
• Chi-Square Test for Independence
• Contingency Tables
• Applications of Chi-Square Tests in Business

Chapter 10: Regression Analysis

• Simple Linear Regression
• Least Squares Method
• Coefficient of Determination (R²)
• Multiple Regression Analysis
• Model Assumptions and Diagnostics

Chapter 11: Correlation and Covariance

• Pearson Correlation Coefficient
• Covariance and Its Interpretation
• Correlation vs. Causation
• Applications of Correlation in Business

Chapter 12: Time Series Analysis and Forecasting

• Components of Time Series Data
• Moving Averages and Exponential Smoothing
• Trend Analysis
• Seasonal Variations and Forecasting Models

Chapter 13: Non-Parametric Methods

• When to Use Non-Parametric Tests
• The Sign Test and Wilcoxon Tests
• Kruskal-Wallis and Friedman Tests
• Applications of Non-Parametric Methods

Chapter 14: Statistical Quality Control

• Introduction to Quality Control
• Control Charts for Variables and Attributes
• Process Capability Analysis
• Six Sigma and Statistical Process Control (SPC)

Chapter 15: Decision Analysis and Game Theory

• Decision Making Under Uncertainty
• Decision Trees and Payoff Tables
• Expected Value of Perfect Information
• Introduction to Game Theory

Chapter 16: Advanced Topics in Management Statistics

• Multivariate Analysis
• Cluster Analysis and Factor Analysis
• Discriminant Analysis
• Time Series Forecasting with Advanced Methods

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