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

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What percentage of the people surveyed reported watching 0 hours of TV a day? ... The sample was the 3160 voters who were interviewed in the exit poll. ... – PowerPoint PPT presentation

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


1
Chapter 1Statistics The Art and Science of
Learning from Data
  • Learn .
  • What Statistics Is
  • Why Statistics Is Important

2
Chapter 1
  • Learn
  • How Data is Collected
  • How Data is Used to Make
  • Predictions

3
Section 1.1
  • How Can You Investigate using Data?

4
Health Study
  • Does a low-carbohydrate diet result in
    significant weight loss?

5
Market Analysis
  • Are people more likely to stop at a Starbucks if
    theyve seen a recent TV advertisement for their
    coffee?

6
Heart Health
  • Does regular aspirin intake reduce deaths from
    heart attacks?

7
Cancer Research
  • Are smokers more likely than non-smokers to
    develop lung cancer?

8
To search for answers to these questions, we
  • Design experiments
  • Conduct surveys
  • Gather data

9
Statistics is the art and science of
  • Designing studies
  • Analyzing data
  • Translating data into knowledge and understanding
    of the world

10
Example from the National Opinion Center at the
University of Chicago
  • General Social Survey (GSS) provides data about
    the American public
  • Survey of about 2000 adult Americans

11
Example from GSS Do you believe in life after
death?
12
Three Main Aspects of Statistics
  • Design
  • Description
  • Inference

13
Design
  • How to conduct the experiment
  • How to select the people for the survey

14
Description
  • Summarize the raw data
  • Present the data in a useful format

15
Inference
  • Make decisions or predictions based on the data.

16
Example from GSS On a typical day, about how
many hours do you personally watch television?
17
What percentage of the people surveyed reported
watching 0 hours of TV a day?
18
Example Harvard Medical School study of Aspirin
and Heart attacks
  • Study participants were divided into two groups
  • Group 1 assigned to take aspirin
  • Group 2 assigned to take a placebo

19
Example Harvard Medical School study of Aspirin
and Heart attacks
  • Results the percentage of each group that had
    heart attacks during the study
  • 0.9 for those taking aspirin
  • 1.7 for those taking placebo

20
Example Harvard Medical School study of Aspirin
and Heart attacks
Example Harvard Medical School study of Aspirin
and Heart attacks
  • Can you conclude that it is beneficial for
    people to take aspiring regularly?

21
Section 1.2
  • We Learn About Populations Using Samples

22
Subjects
  • The entities that we measure in a study
  • Subjects could be individuals, schools,
    countries, days,

23
Population and Sample
  • Population All subjects of interest
  • Sample Subset of the population for whom we have
    data

24
Example Format
  • Picture the Scenario
  • Question to Explore
  • Think it Through
  • Insight
  • Practice the concept

25
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.

26

Example The Sample and the Population for an
Exit Poll
Example The Sample and the Population for an
Exit Poll
  • Whats 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.

27
Descriptive Statistics
  • Methods for summarizing data
  • Summaries usually consist of graphs and numerical
    summaries of the data

28
Types of U.S. Households
29
Inference
  • Methods of making decisions or predictions about
    a populations based on sample information.

30
Parameter and Statistic
  • A parameter is a numerical summary of the
    population
  • A statistic is a numerical summary of a sample
    taken from the population

31
Randomness
  • Simple Random Sampling each subject in the
    population has the same chance of being included
    in that sample
  • Randomness is crucial to experimentation

32
Variability
  • Measurements vary from person to person
  • Measurements vary from sample to sample

33
Inferential Statistics are used
  • To describe whether a sample has more females or
    males.
  • To reduce a data file to easily understood
    summaries.
  • To make predictions about populations using
    sample data.
  • To predict the sample data we will get when we
    know the population.
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