Test Bank for Business Statistics Australia New Zealand 7th Edition by Eliyathamby Selvanathan, Saroja Selvanathan, Gerald Keller ISBN 0170279170 9780170279178

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ISBN 10: 0170279170
ISBN 13: 9780170279178
Author:  Eliyathamby Selvanathan, Saroja Selvanathan, Gerald Keller

Statistical data analysis is the backbone of sound business decision making, and finding the right tool to analyse a particular business problem is the key. By learning the fundamentals of statistical reasoning and data analysis, you will be on the way to becoming a better manager, analyst or economist. By providing a framework for solving statistical problems, this seventh Australian and New Zealand edition of Business Statistics teaches skills that you can use throughout your career. The book shows you how to analyse data effectively by focusing on the relationship between the kind of problem you face, the type of data involved and the appropriate statistical technique for solving the problem. Business Statistics emphasises applications over theory. It illustrates how vital statistical methods and tools are for today’s managers and analysts, and how to apply them to business problems using real-world data. Using a proven three-step Identify-Compute-Interpret (ICI) approach to problem solving, the text teaches you how to: 1. IDENTIFY the correct statistical technique by focusing on the problem objective and data type; 2. COMPUTE the statistics doing them by hand and using Excel; and 3. INTERPRET results in the context of the problem. This unique approach enhances comprehension and practical skills. The text’s vast assortment of data-driven examples, exercises and cases covers the various functional areas of business, demonstrating the statistical applications that marketing managers, financial analysts, accountants, economists and others use. Completely up-to-date, the seventh edition offers comprehensive coverage, current examples and an increased focus on applications in the real world.

Business Statistics Australia New Zealand 7th Table of contents:

Chapter 1: What is Statistics

• Introduction to Statistics: The basics of statistics, key concepts, and the role of statistics in various industries, especially business.

• Statistical Applications in Business: How businesses use statistics for decision-making.

• Managerial Use of Statistics: Discusses how managers utilize statistical tools to guide organizational decisions.

• Computers and Online Resources: The role of computers in statistics, and resources available for learning, including an introduction to Microsoft Excel.

Chapter 2: Types of Data, Data Collection, and Sampling

• Types of Data: Describes nominal, ordinal, and numerical data.

• Methods of Collecting Data: Discusses various data collection techniques.

• Sampling Plans: Importance of sampling, and how to plan and execute it effectively.

• Errors in Sampling: Differentiates between sampling and non-sampling errors.

Chapter 3 & 4: Graphical Descriptive Techniques for Nominal and Numerical Data

• Graphical Techniques: Introduces various charts and graphs used to display data for different types of variables (nominal, ordinal, and numerical).

• Time-series Data: How to represent and interpret time-series data.

• Assessing Graphical Excellence: Importance of clear and honest data representation.

Chapter 5: Numerical Descriptive Measures

• Measures of Central Location: Measures like mean, median, and mode.

• Measures of Variability: Range, variance, standard deviation, etc.

• Box Plots: A graphical representation of data variability.

• Guidelines for Data Exploration: Best practices for exploring and summarizing data.

Chapter 6 & 7: Probability and Random Variables

• Probability: Concepts like joint, marginal, and conditional probability.

• Probability Rules and Bayes’ Law: Rules for calculating probabilities, including Bayes’ Theorem.

• Random Variables and Distributions: Discusses discrete (binomial, Poisson) and continuous distributions (normal, exponential).

Chapter 8: Continuous Probability Distributions

• Focus on the normal distribution, exponential distribution, and their applications in data modeling.

Chapters 9-12: Statistical Inference and Hypothesis Testing

• Sampling Distributions: How sample means and proportions behave.

• Estimation: Techniques for estimating population parameters, such as means and proportions.

• Hypothesis Testing: Testing assumptions about population parameters, p-values, Type I and Type II errors.

Chapters 13-16: Advanced Statistical Inference Techniques

• Comparison of Two Populations: Hypothesis testing and estimation when comparing two populations or proportions.

• Variance Inference: Techniques for comparing population variances.

• Analysis of Variance (ANOVA): One-way and two-way ANOVA to compare more than two groups.

• Chi-Squared Tests: For categorical data analysis, including tests for independence and goodness of fit.

Chapters 17-21: Regression Analysis and Model Building

• Linear Regression: Simple and multiple regression models for analyzing relationships between variables.

• Model Building: Selecting and refining statistical models, including polynomial and nonparametric models.

• Nonparametric Statistics: Tests that do not rely on assumptions about population distributions, such as the Wilcoxon tests.

Chapters 22-23: Applications

• Time Series Analysis and Forecasting: Methods to analyze data over time and predict future values using techniques like exponential smoothing and regression.

• Index Numbers: Construction and interpretation of index numbers, including consumer price indices, for comparing data across time or between different entities.

Appendices and Additional Resources

• Excel Instructions: A guide for using Microsoft Excel for statistical analysis.

• Statistical Tables: Tables of critical values for various statistical tests.

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Eliyathamby Selvanathan,Saroja Selvanathan,Gerald Keller,Business Statistics,New Zealand