1. Vocabulary of Statistics Part One

2. Stastistics Original word came from: Original word came from: State Arithmetic

3. Variable A characteristic or attribute that can assume different values. A characteristic or attribute that can assume different values. example: What color shoes are you wearing? example: What color shoes are you wearing? example: How many times a week do you eat fruit? example: How many times a week do you eat fruit?

4. Data The values (measurements or observations) that the variables can assume. The values (measurements or observations) that the variables can assume. Example: I am wearing a green shirt. Example: I am wearing a green shirt. Example: 4 times a week I eat an apple. Example: 4 times a week I eat an apple.

5. Random variables Where value is determined by chance Where value is determined by chance Example: Rolling a pair of dice. Example: Rolling a pair of dice. Example: Flipping a coin. Example: Flipping a coin.

6. Example Suppose that an insurance company studies its records over the past several years and determines that, on average, 3 out of every 100 automobiles the company insures were involved in an accident during a 1-year period. What is the variable? What is the data? Is the data random?

7. Data Set A collection of data values. A collection of data values. Each individual value is called a data value or a datum Each individual value is called a data value or a datum

8. Data can be used in different ways. The body of knowledge called statistics is sometimes divided into two main areas, depending on how the data are used. The two areas are: Descriptive statistics Inferential statistics

9. Descriptive Statistics Used to describe a situation. Used to describe a situation. U.S. Census – average age, income, number of children, etc. U.S. Census – average age, income, number of children, etc.

10. Descriptive Statistics Consists of the collection, organization, summarization, and presentation of data. Consists of the collection, organization, summarization, and presentation of data.

11. Inferential Statistics Use of a sample to infer (predict) the particulars of a population. Use of a sample to infer (predict) the particulars of a population. Inferential statistics use probability – the chance of an event occuring. Inferential statistics use probability – the chance of an event occuring. Probability theory is used in areas like gaming and insurance. Probability theory is used in areas like gaming and insurance.

12. Population: Consists of all subjects (human or otherwise) that are being studied. Population: Consists of all subjects (human or otherwise) that are being studied. Sample: A group of subjects selected from a population. Sample: A group of subjects selected from a population.

14. Inferential Statistics Consists of generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions. Consists of generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions.

15. Inferential Statistics If the subjects of a sample are properly selected, most of the time they should possess the same or similar characteristics as the subjects of the population. If the subjects of a sample are properly selected, most of the time they should possess the same or similar characteristics as the subjects of the population. Your assignment: Write a paragraph explaining how you would take a random sample of people who live in Muskogee. Keep in mind; you need to devise a method that will not be biased in any way. Your assignment: Write a paragraph explaining how you would take a random sample of people who live in Muskogee. Keep in mind; you need to devise a method that will not be biased in any way.