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BCOR 1020 Business Statistics

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Chapter 1 Key Definitions ... Exploratory data analysis (EDA) Data Mining. Computer-intensive statistics. Design of experiments ... – PowerPoint PPT presentation

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Title: BCOR 1020 Business Statistics


1
BCOR 1020Business Statistics
  • Lecture 1 January 15, 2008

2
Overview
  • Introduction
  • Syllabus
  • Course Expectations
  • Clickers
  • Chapter 1
  • Key Definitions
  • Why Study Statistics?
  • Uses of Statistics
  • Statistical Challenges
  • Written Reports and Presentations
  • Statistical Pitfalls
  • An Evolving Field

3
Introduction
  • About the Instructor
  • Syllabus Overview of Course Topics
  • Course Expectations (My Expectations)
  • Office Hours
  • Instructor
  • TAs

4
Chapter 1 Key Definitions
  • Statistics is the science of collecting,
    organizing, analyzing, interpreting, and
    presenting data.
  • Statistics is the science of making inferences
    about and entire population based of a sample
    from that population.

Sample statistics are computed Size n
Population Characterized by Parameters Size N
5
Chapter 1 Key Definitions
  • A statistic is a single measure (number) used to
    summarize a sample data set. For example, the
    average height of students in this class.
  • Two primary uses for statistics
  • Descriptive statistics the collection,
    organization, presentation and summary of data.
    (Computational/Mechanical)
  • Inferential statistics generalizing from a
    sample to a population, estimating unknown
    parameters, drawing conclusions, making
    decisions. (Analytical typically using
    probability theory)

6
Chapter 1 Why Study Statistics?
  • Your textbook cites the following reasons
  • Communication Understanding the language of
    statistics facilitates communication and improves
    problem solving.
  • Computer Skills The use of spreadsheets for data
    analysis and word processors or presentation
    software for reports improves upon your existing
    skills.
  • Information Management Statistics help summarize
    large amounts of data and reveal underlying
    relationships.
  • Technical Literacy Career opportunities are in
    growth industries propelled by advanced
    technology. The use of statistical software
    increases your technical literacy.
  • Career Advancement Statistical literacy can
    enhance your career mobility.
  • Quality Improvement Statistics helps firms
    oversee their suppliers, monitor their internal
    operations and identify problems.

7
Chapter 1 Uses of Statistics
  • As mentioned earlier, there are generally two
    primary uses of statistics
  • Descriptive (early chapters)
  • Inferential (later chapters)

8
Chapter 1 Uses of Statistics
  • Some specific examples from business
  • Auditing Sample from over 12,000 invoices to
    estimate the proportion of incorrectly paid
    invoices.
  • Marketing Identify likely repeat customers for
    Amazon.com and suggests co-marketing
    opportunities based on a database of 5 million
    Internet purchases.
  • Purchasing Determine the defect rate of a
    shipment and whether that rate has changed
    significantly over time.
  • Forecasting Manage inventory by forecasting
    consumer demand.

9
Clickers Relevance of Statistics1
  • Based on what has been discussed so far,
  • do you feel that Statistics will be important
  • in your future career?
  • A Yes
  • B No

10
Clickers Relevance of Statistics2
  • Based on what has been discussed so far,
  • how important do you feel Statistics will be
  • in your future career?
  • A very important
  • B important
  • C somewhat important
  • D not important

11
Chapter 1 Statistical Challenges
  • Working with Imperfect Data State any
    assumptions and limitations and use generally
    accepted statistical tests to detect unusual data
    points or to deal with missing data.
  • Dealing with Practical Constraints You will face
    constraints on the type and quantity of data you
    can collect.
  • Upholding Ethical Standards Know and follow
    accepted procedures, maintain data integrity,
    carry out accurate calculations, report
    procedures, protect confidentiality, cite sources
    and financial support.
  • Using Consultants Hire consultants at the
    beginning of the project, when your team lacks
    certain skills or when an unbiased or informed
    view is needed.

12
Chapter 1 Written Reports and Presentations
  • In this course, you will be required to submit
    written
  • reports for two projects. In your career, you
    will be
  • required to submit written reports often and to
    give
  • oral presentations occasionally.
  • Your textbook has very good advice for presenting
  • statistical information, both in written reports
    and in
  • oral presentations.
  • Read and use these sections (beginning with
    section 1.5)!!!

13
Chapter 1 Statistical Pitfalls
  • Pitfall 1 Making Conclusions about a Large
    Population from a Small Sample
  • Be careful about making generalizations from
    small samples (e.g., a group of 10 consumers).
  • Pitfall 2 Making Conclusions from Nonrandom
    Samples
  • Be careful about making generalizations from
    retrospective studies of special groups (e.g.,
    the first 50 potential customers on a mail-list
    or your best 50 customers).
  • Pitfall 3 Attaching Importance to Rare
    Observations from Large Samples
  • Be careful about drawing strong inferences from
    events that are not surprising when looking at
    the entire population (e.g., winning the
    lottery).

14
Chapter 1 Statistical Pitfalls
  • Pitfall 4 Using Poor Survey Methods
  • Be careful about using poor sampling methods or
    vaguely worded questions (e.g., anonymous survey
    or quiz).
  • Pitfall 5 Assuming a Causal Link Based on
    Observations
  • Be careful about drawing conclusions when no
    cause-and-effect link exists (e.g., most shark
    attacks occur between 12p.m. and 2p.m.).
  • Pitfall 6 Making Generalizations about
    Individuals from Observations about Groups
  • Avoid reading too much into statistical
    generalizations (e.g., men are taller than women).

15
Chapter 1 Statistical Pitfalls
  • Pitfall 7 Unconscious Bias
  • Be careful about unconsciously or subtly allowing
    bias to color handling of data (e.g., heart
    disease in men vs. women).
  • Pitfall 8 Attaching Practical Importance to
    Every Statistically Significant Study Result
  • Statistically significant effects may lack
    practical importance (e.g., Austrian military
    recruits born in the spring average 0.6 cm taller
    than those born in the fall).

16
Chapter 1 An Evolving Field
  • Statistics is a relatively young field, having
    been developed mostly during the 20th century.
  • Its mathematical frontiers continue to expand
    with the aid of computers.
  • Major recent developments include
  • Exploratory data analysis (EDA)
  • Data Mining
  • Computer-intensive statistics
  • Design of experiments
  • Statistical Quality Process Control
  • Robust product design
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