1. Chapter 1 Introduction 1-1

2. Learning Objectives  To learn the basic definitions used in statistics and some of its key concepts.  To obtain an overview of the material in the text. 1-2

3. Basic Definitions and Concepts  Population: The specific collection of objects of interest.  Sample: Any subset or sub-collection of the population.  Census: A sample that consists of the whole population.  Measurement: A number or attribute computed for each member of a population or of a sample.  Parameter: A number that summarizes some aspect of the population as a whole.  Statistic: A number computed from the sample data. 1-3

4. Basic Definitions and Concepts  Statistics: A collection of methods for collecting, displaying, analyzing, and drawing conclusions from data.  Descriptive Statistics: The branch of statistics that involves organizing, displaying, and describing data. It utilizes numerical and graphical methods to look for patterns in a data set, to summarize the information revealed in a data set and to present that information in a convenient form.  Inferential Statistics: The branch of statistics that consists of methods for drawing and measuring the reliability of conclusions about a population based on information obtained from a sample of the population. 1-4

5. Basic Definitions and Concepts  A measure of reliability is a statement about the degree of uncertainty associated with a statistical inference.  Example: Based on our analysis, we think 56% of soda drinkers prefer Coke to Pepsi, ± 5%.  These ideas will be developed in chapter 7. 1-5

6. Basic Definitions and Concepts  Qualitative variable: allows for the classification of individuals based on some attribute or characteristic. It is a non-numerically valued variable.  Quantitative variable: provides numerical measures of individuals. Arithmetic operations such as addition and subtraction can be performed on the values of the quantitative variable and provide meaningful results. A discrete variable is a quantitative variable that either has a finite number of possible values or a countable number of possible values. A continuous variable is a quantitative variable that has infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps. A continuous variable can be measured to any desired level of accuracy. 1-6

7. Basic Definitions and Concepts  Qualitative data: Measurements or observations for which there is no natural numerical scale, but which consist of attributes, labels, or other non-numerical characteristics.  Quantitative data: Numerical measurements or observations that arise from a natural numerical scale. 1-7

8. Overview of the Text  Chapter 4 deals with statements of probability.  Chapter 5 deals with discrete random variables.  Chapter 6 deals with continuous random variables and the Central Limit Theorem (CLT).  Chapter 7 deals with confidence intervals.  Chapter 8 deals with hypothesis testing. 1-8

9. Key Takeaways  Statistics is a study of data: Describing properties of data (descriptive statistics) and drawing conclusions about a populations based on information in a sample (inferential statistics).  The distinction between a population together with its parameters and a sample together with its statistics is a fundamental concept in inferential statistics.  Information in a sample is used to make inferences about the population from which the sample was drawn. 1-9

10. Key Takeaways  Statistics computed from samples vary randomly from sample to sample.  Conclusions made about population parameters are statements of probability. 1-10