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Chapter 1:Statistics: The Art and Science of Learning from Data

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**1. **Chapter 1:Statistics: The Art and Science of Learning from Data 1.1: How Can You Investigate Using Data?
1.2: We Learn about Populations Using Samples
1.3: What Role Do Computers Play in Statistics?

**2. **Section 1.1 Learning Objectives How Can You Investigate Using Data?
Data and examples of collecting data.
Define Statistics
Identify three aspects of a study

**3. **Learning Objective 1: Data Data is information we gather with experiments and with surveys.
Example: Experiment on low carbohydrate diet
Data could be measurements on subjects before and after the experiment
Example: Survey on effectiveness of a TV ad
Data could be percentage of people who went to Starbucks since the ad aired

**4. **Learning Objective 2: Define Statistics Statistics is the art and science of:
Designing studies
Analyzing resultant data
Translating data into knowledge and understanding

**5. **Learning Objective 3: Statistical Methods Design: Planning how to obtain data
Description: Summarizing the data
Inference: Making decisions and predictions

**6. **Learning Objective 3: Descriptive Statistics Methods for summarizing data
Summaries usually consist of graphs and numerical summaries of the data

**7. **Learning Objective 3: Examples of Design Statistics Design questions:
How to conduct the experiment, or
How to select people for the survey
to insure trustworthy results
Examples:
Planning the methods for data collection to study the effects of Vitamin E on athletic strength
For a marketing study, how do you select people for your survey to provide proper coverage
DescriptionDescription

**8. **Learning Objective 3: Examples of Descriptive Statistics Description:
Summarize the raw data and present it in a useful format (e.g., average, charts or graphs)
Examples:
A meteorologist constructs a graph showing the total precipitation in Bloomington, IL for each of the months of 2005.
The average age of the students in a statistics class is 25 years.
DescriptionDescription

**9. **Learning Objective 3: Inference Methods of making decisions or predictions about a populations based on information obtained from a sample.

**10. **Learning Objective 3: Examples of Inferential Statistics Inference: Make decisions or predictions based on the data
Examples:
There is a relationship between smoking cigarettes and getting emphysema.
From past figures, it is predicted that 47% of the registered voters in Illinois will vote in the primary. DescriptionDescription

**11. **Section 1.2 Learning Objectives We Learn about Populations Using Samples
Subjects
Population and sample
Descriptive statistics and inferential statistics
Sample Statistics and Population Parameters
Randomness and Variability

**12. **Learning Objective 1: Subjects Subjects
The entities that we measure in a study
Subjects could be individuals, schools, rats, counties, widgets

**13. **Learning Objective 2: Population and Samples Population: All subjects of interest
Sample: Subset of the population for whom we have data
Researchers often want to answer questions about some large group of individuals (this group is called the population). Often researchers can’t measure all individuals in the population,
So they measure a subset of individuals that is chosen to represent the entire population (this subset is called a sample)
The researchers then use statistical techniques to make conclusions about the population based on the sample
Researchers often want to answer questions about some large group of individuals (this group is called the population). Often researchers can’t measure all individuals in the population,
So they measure a subset of individuals that is chosen to represent the entire population (this subset is called a sample)
The researchers then use statistical techniques to make conclusions about the population based on the sample

**14. **Learning Objective 2: Example: The Sample and the Population for an Exit Poll In California in 2003, a special election was held to consider whether Governor Gray Davis should be recalled from office.
An exit poll sampled 3160 of the 8 million people who voted. Define the sample and the population for this exit poll.
The population was the 8 million people who voted in the election.
The sample was the 3160 voters who were interviewed in the exit poll.

**15. **Learning Objective 3 Descriptive vs. Inferential Statistics Descriptive Statistics refers to methods for summarizing the data. Summaries consist of graphs and numbers such as averages and percentages
Inferential statistics refers to methods of making decisions or predictions about a population based on data obtained from a sample of that population.

**16. **Learning Objective 3: Descriptive Statistics Example

**17. **Learning Objective 3: Inferential Statistics Example Calculating a confidence interval:
By surveying 1000 likely voters, we find a sample proportion of 39% who approve of the job President Bush is doing.
We are 95% confident that the population proportion of likely voters who approve of the job President Bush is doing is between 36% and 42%.

**18. **Learning Objective 4: Sample Statistics and Population Parameters A parameter is a numerical summary of the population
Mean (µ) number of cigarettes smoked by all teenagers
Proportion (p) of all teenagers who smoked in the last month

**19. **Learning Objective 4: Sample Statistics and Population Parameters A statistic is a numerical summary of a sample taken from the population
Mean number of cigarettes smoked per day by a sample of teenagers
Proportion of a sample of teenagers who smoked in the last month

**20. **Learning Objective 5: Randomness Simple Random Sampling: each subject in the population has the same chance of being included in the sample
Randomness is crucial to insuring that the sample is representative of the population so that powerful inferences can be made

**21. **Learning Objective 5: Variability Measurements may vary from subject to subject, and
Measurements may vary from sample to sample
Predictions will therefore be more accurate for larger samples.

**22. **Section 1.3 What Role Do Computers Play in Statistics? Using Technology
You, not technology, must select valid analyses
Data files
Large sets of data are typically organized in a spreadsheet format known as a data file
Each row contains measurements for a particular subject
Each column contains measurements for a particular characteristic
Databases
An existing archive collection of data files
Sources should always be checked for reliability

**23. **Section 1.3 What Role Do Computers Play in Statistics? Applets
A short application program for performing a specific task
Useful for performing activities that illustrate the ideas of statistics