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ttests

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A statistical difference is a function of the difference between means relative ... Power = 1- . Explanations for Type I errors - a. An unusual sample ... – PowerPoint PPT presentation

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Title: ttests


1
t-tests Confidence Intervals
2
What Does Difference Mean?
  • The t-test is to determine if there is a
    difference between two measures.
  • A sample and a population?
  • Two independent samples?
  • Related Samples?

3
Statistical Analysis
Control group mean
Treatment group mean
Is there a difference?
4
What Does Difference Mean?
Medium variability
5
What Does Difference Mean?
Medium variability
High variability
6
What Does Difference Mean?
Medium variability
High variability
Low variability
7
What Does Difference Mean?
The mean difference is the same for all three
cases.
Medium variability
High variability
Low variability
8
What Does Difference Mean?
Medium variability
High variability
Which one shows the greatest difference?
Low variability
9
What Does Difference Mean?
  • A statistical difference is a function of the
    difference between means relative to the
    variability.
  • A small difference between means with large
    variability could be due to chance.
  • Like a signal-to-noise ratio.

Which one shows the greatest difference?
Low variability
10
Steps in Hypothesis Testing
  • Establish hypotheses to be tested
  • State a criterion for making a decision or
    identify a and critical values
  • Collect and describe sample data.
  • Do the math using inferential statistics
  • Make a statistical decision

11
Errors in Hypothesis Tests
  • Type I Error ?- Rejecting a null hypothesis
    that is true
  • Type II Error ? - Failing to reject a null
    hypothesis that is false.

12
Outcomes in Hypothesis Testing
13
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14
Decisions in Hypothesis Testing
15
Graphical Representation of Statistical Power
16
Statistical Power, a, and ß
  • Power 1-ß
  • Explanations for Type I errors - a
  • An unusual sample
  • Something other than our manipulation produced a
    difference in the means
  • Explanations for Type II errors - ß
  • An unusual sample in the opposite direction
  • The change was too small to detect
  • There was too much variability in the sample

17
The t statistic
The objective in the hypothesis testing process
is to have large t values as an aid in the
decision making process.
18
Impact of Sample Size and Standard Deviation on
Statistical Power
Power is also impacted by difference between the
means and a
19
Types of t tests
  • One sample t tests
  • Related samples t tests
  • Repeated measures
  • Matched groups
  • Independent samples t tests

?
20
Related Samples t tests
df n - 1
21
Independent Samples t tests
df n - 2
22
Estimated Standard Error of the Difference
Between Two Groups
23
Confidence Intervals
  • A tool for making estimations about populations
    based on sample data
  • More useful than t-tests in that they answer
    questions about differences, but also about how
    much difference
  • Have a both a level of confidence and a degree of
    accuracy

24
Calculating Confidence Intervals
  • Point estimates
  • Interval estimates

Point Estimate Sample mean Difference between
sample means Mean of differences
Interval Estimate Point Estimate Fudge factor
Fudge Factor t value estimated standard error
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