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Descriptive & Inferential Statistics

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Descriptive & Inferential Statistics Merryellen Towey Schulz, Ph.D. College of Saint Mary EDU 496 The Meaning of Statistics Several Meanings Collections of numerical ... – PowerPoint PPT presentation

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Title: Descriptive & Inferential Statistics


1
Descriptive Inferential Statistics
  • Merryellen Towey Schulz, Ph.D.
  • College of Saint Mary
  • EDU 496

2
The Meaning of Statistics Several Meanings
  • Last years enrollment figures
  • Average enrollment per month last year
  • Evaluators made a projection of next years
    enrollments
  • Collections of numerical data
  • Summary measures calculated from a collection of
    data
  • Activity of using and interpreting a collection
    of numerical data

3
Descriptive Statistics
  • Use of numerical information to summarize,
    simplify, and present data.
  • Organized and summarized for clear presentation
  • For ease of communications
  • Data may come from studies of populations or
    samples

4
Descriptive Statistics Associated with Methods
and Designs
5
Descriptive Stats Vocabulary
  • Central tendency
  • Mode
  • Median
  • Mean
  • Variation
  • Range
  • Standard deviation
  • Normal distribution

6
Descriptive Stats Vocabulary contd
  • Standard score
  • Effect size
  • Correlation
  • Regression

7
Inferential Statistics
  • To generalize or predict how a large group will
    behave based upon information taken from a part
    of the group is called and INFERENCE
  • Techniques which tell us how much confidence we
    can have when we GENERALIZE from a sample to a
    population

8
Inferential Stats Vocabulary
  • Hypothesis
  • Null hypothesis
  • Alternative hypothesis
  • ANOVA
  • Level of significance
  • Type I error
  • Type II error

9
Examples of Descriptive and Inferential Statistics
  • Descriptive Statistics
  • Graphical
  • Arrange data in tables
  • Bar graphs and pie charts
  • Numerical
  • Percentages
  • Averages
  • Range
  • Relationships
  • Correlation coefficient
  • Regression analysis
  • Inferential Statistics
  • Confidence interval
  • Margin of error
  • Compare means of two samples
  • Pre/post scores
  • t Test
  • Compare means from three samples
  • Pre/post and follow-up
  • ANOVA analysis of variance

10
Problems With Samples
  • Sampling Error
  • Inherent variation between sample and population
  • Source is chance or luck
  • Results in bias
  • Sample statistic -- a number or figure
  • Single measure -- how sure accurate
  • Comparing measures --see differences
  • How much due to chance?
  • How much due to intervention?

11
What Is Meant By A Meaningful Statistic
(Significant)?
  • Statistics, descriptive or inferential are NOT a
    substitute for good judgment
  • Decide what level or value of a statistic is
    meaningful
  • State judgment before gathering and analyzing
    data
  • Examples
  • Score on performance test of 80 is passing
  • Pre/post rules instruction reduces incidents by
    50

12
Interpretation of Meaning
  • Population Measure (statistic)
  • There is no sampling error
  • The number you have is real
  • Judge against pre-set standard
  • Inferential Measure (statistic)
  • Tells you how sure (confident) you can be the
    number you have is real
  • Judge against pre-set standard and state how
    certain the measure is
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