Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-1 Outline Sept. 2005 1. Mark L, Berenson, David M. Levine, Timonthy C. Levine, Basic.

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Presentation transcript:

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-1 Outline Sept Mark L, Berenson, David M. Levine, Timonthy C. Levine, Basic Business Statistics– Concepts and Applications, 10rd Edition, 2005 ,華泰文化 2. 林惠玲 陳正倉著 應用統計學 ─ 二版,雙葉書廊發行 2003 週次 內容 1 Introduction to Statistics 2 Charts and Graphs 3 Describing Data: Measures of Location 4 Describing Data: Measures of Dispersion 5 Probability 6 Discrete Probability Distributions 7 Discrete and Normal Probability Distribution 8 Normal Probability Distribution 9 Sampling Methods and Sampling Distributions 10 Midterm Exam

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap Sampling Methods and Sampling Distributions 12 Statistical Inference: Estimation for Single Populations 13 Statistical Inference: Hypothesis Testing for Single Populatiosn 1 14 Statistical Inference: Hypothesis Testing for Single Populatiosn 2 15 Statistical Inferences about Two Populations 16 Analysis of Variance 1 17 Analysis of Variance 2 18 Final Exam.

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-3 下學期 1 Matrices and Determinants 2 Linear Regression and Correlation 1 3 Linear Regression and Correlation 2 4 Multiple Regression and Correlation Analysis 1 5 Multiple Regression and Correlation Analysis 2 6 Multiple Regression and Correlation Analysis 3 7 Nonparametric Methods: Chi-Square Applications 1 8 Nonparametric Methods: Chi-Square Applications 2 9 Midterm Exam.

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap Nonparametric Methods: Analysis of Ranked Data 11 Statistical Quality Control 12 Index Number 13 Time Series and Forecasting 1 14 Time Series and Forecasting 2 15 Time Series and Forecasting 3 16 An Introduction to Decision Making 17 Final Exam.

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-5 評量方式 平常考試佔 %. 期中考試佔 30 % 期末考試佔 30 %. 課程參與度佔 10 %.

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-6 相關網站連結 數學知識 Probability and Statistics 統計大家談 統計生活館 統計計算程式設計 機率概念與應用網路研究 互動式統計輔助教學 機率統計網路學習館 統計網路學習館 數學領域 機率與統計

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc. Chap 1-7 Chapter 1 Introduction and Data Collection Basic Business Statistics 10 th Edition

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-8 Learning Objectives In this chapter you learn: How Statistics is used in business The sources of data used in business The types of data used in business

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-9 Basic Concepts of Statistics Statistics is concerned with: Processing and analyzing data Collecting, presenting, and transforming data to assist decision makers

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-10 Key Definitions A population (universe) is the collection of all members of a group A sample is a portion of the population selected for analysis A parameter is a numerical measure that describes a characteristic of a population A statistic is a numerical measure that describes a characteristic of a sample

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-11 Population vs. Sample a b c d ef gh i jk l m n o p q rs t u v w x y z PopulationSample b c g i n o r u y Measures used to describe a population are called parameters Measures computed from sample data are called statistics

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-12 Two Branches of Statistics Descriptive statistics Collecting, summarizing, and presenting data Inferential statistics Drawing conclusions about a population based only on sample data

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-13 Descriptive Statistics Collect data e.g., Survey Present data e.g., Tables and graphs Characterize data e.g., Sample mean =

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-14 Inferential Statistics Estimation e.g., Estimate the population mean weight using the sample mean weight Hypothesis testing e.g., Test the claim that the population mean weight is 120 pounds Drawing conclusions about a population based on sample results.

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-15 Collecting Data Secondary Data Compilation Observation Experimentation Print or Electronic Survey Primary Data Collection

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-16 Types of Data Data CategoricalNumerical DiscreteContinuous Examples: Marital Status Political Party Eye Color (Defined categories) Examples: Number of Children Defects per hour (Counted items) Examples: Weight Voltage (Measured characteristics)

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Levels of Measurement and Measurement Scales Interval Data Ordinal Data Nominal Data Highest Level (Strongest forms of measurement) Higher Levels Lowest Level (Weakest form of measurement) Categories (no ordering or direction) Ordered Categories (rankings, order, or scaling) Differences between measurements but no true zero Ratio Data Differences between measurements, true zero exists

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Levels of Measurement and Measurement Scales Interval Data Ordinal Data Nominal Data Height, Age, Weekly Food Spending Service quality rating, Standard & Poor’s bond rating, Student letter grades Marital status, Type of car owned Ratio Data Temperature in Fahrenheit, Standardized exam score Categories (no ordering or direction) Ordered Categories (rankings, order, or scaling) Differences between measurements but no true zero Differences between measurements, true zero exists EXAMPLES:

Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 1-19 Chapter Summary Reviewed basic concepts of statistics:  Population vs. Sample  Parameter vs. Statistic  Primary vs. Secondary data sources Defined descriptive vs. inferential statistics Reviewed types of data and measurement scales  Categorical vs. Numerical data  Discrete vs. Continuous data  Nominal and Ordinal scales  Interval and Ratio scales