Exam 10: Statistical Significance
Exam 1: Introduction to Statistics 24 Questions
Exam 2: Levels of Measurement25 Questions
Exam 3: Graphical Statistics25 Questions
Exam 4: Measures of Central Tendency25 Questions
Exam 5: Measures of Dispersion25 Questions
Exam 6: Curves and Distributions22 Questions
Exam 7: Frequency Distributions22 Questions
Exam 8: Elementary Relationships: Crosstabulation Tables20 Questions
Exam 9: Hypotheses and Sampling Distributions21 Questions
Exam 10: Statistical Significance22 Questions
Exam 11: Testing for Significance: the Chi-Square Test22 Questions
Exam 12: Testing for Significance in Two Groups: the T-Test21 Questions
Exam 13: Testing for Significance in Multiple Groups: the Analysis of Variance Statistic20 Questions
Exam 14: The Concept of Association19 Questions
Exam 15: Testing for Association: Phi19 Questions
Exam 16: Testing for Association: Pearsons R and Regression21 Questions
Exam 17: Doing Real Research: Elementary Multivariate Relationships19 Questions
Exam 18: Box Plots3 Questions
Exam 19: Skewness and Kurtosis3 Questions
Exam 20: Ordinal-Level Tests of Significance2 Questions
Exam 21: Multiple Comparison Tests3 Questions
Exam 22: Nominal Level Tests of Association4 Questions
Exam 23: Ordinal Level Tests of Association4 Questions
Exam 24: Addendum Probability3 Questions
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If a statistical program's probability output doesn't say differently,it is almost always a 2-tailed probability.
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A probability level is just another name for the likelihood of random error.
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Random error distributions can be used to estimate the amount of error likely to occur in a sample.
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While it is common to use p = .05 as the criteria for significance,you don't absolutely have to.
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If an inferential statistic's calculated value is statistically significant,that means:
(Multiple Choice)
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When you have a one-tailed relationship,what would you normally do with the associated probability level?
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If you don't have the probability associated with an inferential statistic's value and degrees of freedom
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If a zero association exists,which of the following hypotheses would be supported?
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Statistical significance does not mean that something is important.
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If your probability level is lower than your alpha level,you should
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Under which condition below would you reject a null hypothesis?
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An inferential statistic cannot be interpreted unless you have:
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A Chi-square test with an associated probability level cannot be interpreted unless you have the actual Chi-square value.
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If an inferential test result is significant,you no longer have to worry about the direction of a hypothesis.
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