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Quote of the Day
Oh, people can come up with statistics to
 prove anything. 14% of people know
 that. ---Homer Simpson


      What are Statistics?
Chapter 1:The Nature of
Probability and Statistics

              Section 1:
      Descriptive and Inferential
             Statistics
Stats in Daily Life
   Of the people in the US, 14% said they feel
    happiest in June, and 14% said they feel
    happiest in December.
   The average in-state college tuition and fees
    for 4-year pubic college is $5,836.
   Every day in the US about 120 golfers claim
    that they made a hole-in-one.
   4 out of 5 doctors leaves one doctor.- Chevy
    Chase
What is Statistics?
   The science of conducting studies to
    collect, organize, summarize, analyze
    and draw conclusions from data.
What is Data?
   The values that the variables can
    assume.
   A collection of values forms a Data
    Set
       Each Value in the data set is called:
         
             Data Value or
            Datum
What is a variable?
   A characteristic or attribute that can
    assume different values.
Types of Statistics
1. Descriptive Statistics
        Consists of the collection, organization,
         summarization, and presentation of data
        Ex: Government Census
            Taken every ten years
         
             Describes average income, family size, etc..
       What does this mean?
        Basically used to describe a situation.
Types of Statistics
2.       Inferential Statistics
         Consists of generalizing from samples
          to populations, performing estimations
          and hypothesis tests, determining
          relationships among variables, and
          making predictions.
          
              Ex: Winning the lottery
                 1 in a million
        What does this mean ?
         Used to predict the outcome of an event.
What is the difference between a
Population and a Sample?

    Population- consists of all subjects
     that are being studied.
    Sample- is a group selected from a
     population.
Population
Sample
Assignment
   Page 26
       #’s 1-6
Section 2: Types of Variables
       Qualitative Variables:
         Variables that can be placed into distinct
          categories, according to some
          characteristic or attribute.
         Ex: Gender, Eye color, Geographic
          Location
2 Types of Variables
   Quantitative Variables:
       Variables that are numerical and can be
        ordered or ranked.
       Ex: Age, height, weight, body temp
       Classified by two groups
            Discrete Variables
            Continuous Variables
Practice
   Page 26 #8
Discrete Variables
   Assume values that can be counted
   Assigned numbers such as 0,1,2,3,…
   Ex:
       # of children
       # of students
Continuous Variables
   Can assume an infinite number of
    values between any two specific values.
   Obtained by measuring
   Often include fractions and decimals.
   Ex:
       Temperature
       Time
       Length
Practice
   Page 27 #9
Measurement Scale
   Used to categorize, count, or measure
    variables.
   Types:
       Nominal
       Ordinal
       Interval
       Ratio
Nominal Level of Measurement
   Classifies data into mutually exclusive,
    exhausting categories in which no order
    or ranking can be imposed on the data.
   Ex:
       Male/Female
       Single/Married/Divorced/Widowed/Separated
       Democratic/Republican
Ordinal Level of Measurement
   Classifies data into categories that can
    be ranked; however, precise differences
    between the ranks do not exist.
   Ex:
       Letter Grades (A, B, C, D, F)
       1st, 2nd, 3rd, etc
       Small, Medium, Large
       Freshman, Sophomores, Juniors, Seniors
Interval Level of Measurement
   Ranks data, and precise differences
    between units of measures do exist:
    however, there is no meaningful zero.
   Ex:
       Temperature: 72°F and 73°F, difference of
        1°F, but 0°F does not mean no heat
        present
       IQ: 109 and 110, difference of 1 point, but
        0 does not mean there is no intelligence.
Ratio Level of Measurement
   Possesses all the characteristics of interval
    measurements, and there exists a true zero.
   In addition, true ratios exists when the same
    variables is measured on two different
    members of the population.
   Ex:
       Salary
       Time
       Age
Practice
   Page 26 #7
Section 3: Data Collection and
Sampling Techniques.
   Types:
       Random
       Systematic
       Stratified
       Cluster
Random Sampling
   Selection based on chance or random
    numbers.
   Procedure:
       Assign number to each subject in
        population
       Select numbers at random from “hat”
Random Sampling


1    2    3    4    5    6    7




8    9    10   11   12   13   14




15   16   17   18   19   20   21
Systematic Sampling
   Procedure:
       Number each subject in population
       Select every kth subject
   Example:
       Population: 100 Sample: 10
       Kth term: 100/10=10
       1, 11, 21, 31, 41, 51, 61, 71, 81, 91
Systematic Sampling
Population: 21 Sample: 7
21/7=3: kth term is 3.




 1      2      3       4    5    6    7




 8      9      10      11   12   13   14




 15     16     17      18   19   20   21
Stratified Sampling
   Procedures:
       Population divided into groups called:
        Strata
       Groups have common characteristic
        needed for study.
       Samples randomly selected from each
        strata
Stratified Sampling
Cluster Sampling
   Population is divided into groups called:
    Clusters
   Select some clusters
   Survey every member of the cluster for
    sample

   Used with large populations
Cluster Sampling
Other sampling methods
   Convenience sampling
       Use subjects that are convent
       Ex: asking people as they enter the mall
   Sequential sampling
   Double sampling
   Multistage sampling
Convenience Sampling

    Do you want to
    take a survey?
Practice
   Page 27 #12
Section 4: 2 Types of Studies
       Observational Study
        Researchers merely observe what is
         happening or what has happened in the
         past
        Try to draw conclusions based on these
         observations.
        Ex: studying creatures in the wild
            “Meerkat Manor”
Section 4: 2 Types of Studies
   Experimental study
       Researchers manipulate one of the
        variables
       Tries to determine how to the manipulation
        influences other variables.
       Ex: New medication and placebos
Practice
   Page 27-28 #17
Statistical Studies include….
   Independent variables
       In an experimental study is the one that is
        being manipulated by the researcher.
       Also called: Explanatory variable

   Dependent variables
       Resultant variable
       Also called: Outcome variable
Misuses of Statistics
   Suspect Samples
       Too small
       Convenience
       Volunteers

   Changing the subject
       Increase of 3%
       Increase of $600,000
Misuses of Statistics
   Detached Statistics- no comparison
       “Works 5 times faster”
       “1/3 fewer calories”


   Implied Connection
       “Eating fish may help you achieve better in
        school”
Misuses of Statistics
   Misleading Graphs- Chapter 2

   Faulty Survey Questions
       “Do you feel there should be a 4 day
        school week?”
       “Do you feel there should be a 4 day
        school week from 4 am to midnight?”
Section 1-6: Computers and
Calculators
   Computer and Calculators GOOD
End of Chapter 1