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Spring 2014 chapter 1
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  • 1. Chapter 1 The Functions of Statistics
  • 2. Two Classes of Statistics: 1. Descriptive 2. Inferential
  • 3. Descriptive Statistics: Functions of Descriptive Statistics: a) Data reduction:  allow a few numbers to summarize many b) Measures of association  quantify strength and direction of a relationship. Types of Descriptive Statistics:  Univariate Descriptive Statistics:  Describes the distribution of a single variable  Bivariate Descriptive Statistics  Summarize relationship between two variables  Multivariate Descriptive Statistics  Summarize relationship between 3 or more variables
  • 4. Inferential Statistics:  Functions of Inferential Statistics: a) Aids researchers in drawing inferences from samples to populations  Population  all cases in which the researcher is interested.  Samples  carefully chosen subsets of the population. b) Used to test significance of hypotheses
  • 5. Types Of Variables  Variables may be:  Independent or dependent  Discrete or continuous  Nominal, ordinal, or interval-ratio
  • 6. Types Of Variables: Independent or Dependent  In causal relationships: CAUSE  EFFECT independent variable  dependent variable
  • 7. Types Of Variables: Discrete or Continuous  Discrete variables are measured in units that cannot be subdivided.  Anything regarding people  Wrong when you hear the average number of children per household being 2 ½…  Continuous variables are measured in a unit that can be subdivided infinitely.
  • 8. Types of Variables: Level Of Measurement  Levels of Measurement represent different levels of numerical information contained within the variable: 1. Nominal 2. Ordinal 3. Interval-ratio
  • 9. Nominal Level Variables  Used to classify or categorize  Simplest (or crudest) level of measurement  Numbers are for classification purposes only  Examples: Religion: 1 = Protestant, 2 = Catholic, 3=Jew, 4=None, 5=Other Gender (dichotomy): 1 = Female, 0 = Male
  • 10. Ordinal Level Variables  Used to rank or order in a logical way  Scores can be ranked from high to low or from more to less  Offers the property of “more than” or “less than” to classifications
  • 11. Example of an Ordinal Level Variable: “Do you agree or disagree that University Health Services should offer free contraceptives?” 5=strongly agree 4=agree 3=neutral 2=disagree 1=strongly disagree  Because you can distinguish between the scores of the variable using terms such as “more, less, higher, or lower” the variable is ordinal.
  • 12. Interval-ratio Variables  Scores are “actual” numbers  Ratio variables meet the criteria for interval but also have meaningful and true zero points  Have equal intervals between scores indicating exact distance, thus:  Can indicate “how much more” (or less)  Permits the use of mathematical operations  Examples: Age (in years) Income (in dollars) Number of children  A true zero point (0 = no children)  Equal intervals: each child adds one unit
  • 13.  Different statistics require different mathematical operations (ranking, addition, square root, etc.)  The level of measurement of a variable tells us which statistics are permissible and appropriate.
  • 14. Determining the Level of Measurement of a Variable
  • 15. Classify the level of measurement of the following variables and tell level of measurement:  The numbers on an athlete’s jersey  The dorm you live in  Number of children in a family  Fear of crime ( a lot, some, none)  Number of hours per day respondent watches tv  Tuition in dollars
  • 16. Homework Assignment for Chapter 1:  Problems 1.5 and 1.7