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25 Cards in this Set
- Front
- Back
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What are the five steps of hypothesis testing (in order)?
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1. Identify populations and state research and null hypotheses.
2. Determine characteristics of the comparison distribution. 3. Establish cutoff sample score/critical value. 4. Calculate test statistic. 5. Make decision about the null hypothesis and draw conclusions about the research question. |
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Population one
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The population of interest. This is the population to which you've applied a treatment or that has a characteristic of interest.
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Population two
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The population to which you are comparing those exposed to a treatment or with a characteristic of interest. This is often a "general population."
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Research hypothesis
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Hypothesis that specifies a difference between populations.
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Directional hypothesis
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Research hypothesis that predicts a specific direction of difference between populations.
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Non-directional hypothesis
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Research hypothesis that indicates a difference between populations, but does not predict the direction of that difference.
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Null hypothesis
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Hypothesis that negates the prediction made in a research hypothesis.
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The three main characteristics we need to know about the comparison distribution
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1. Shape
2. Mean 3. Standard deviation |
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Comparison distribution
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The distribution of scores if the null hypothesis is true.
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Cutoff sample score
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The point on a comparison distribution that defines the line between population one being "different' or "not different" from population two.
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Significance level
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The probability that population one differs from population two by chance alone.
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When do you use a one-tailed hypothesis test?
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When you have a directional research hypothesis.
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When do you use a two-tailed hypothesis test?
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When you have a non-directional hypothesis.
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How can you identify a directional research hypothesis?
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There is a comparison word in the research hypothesis (e.g, higher, lower, more, less, greater, fewer).
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When do you reject the null hypothesis?
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When the test statistic you calculate is farther from the mean than the cutoff sample score (in the predicted direction).
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When do you NOT reject the null hypothesis?
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When the test statistic you calculate is not more extreme than the cutoff sample score.
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What does it mean if you do not reject the null hypothesis?
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It means that population one does not differ from population two in the way that was predicted by the research hypothesis.
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Type I error
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Rejecting the null hypothesis when there is no true difference between populations.
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Type II error
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Not rejecting the null hypothesis when there truly is a difference between populations.
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What is another name for type I error?
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False positive
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What is another name for type II error?
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False negative
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What happens to the probability of type I error if you select a higher (i.e., less stringent) significance level?
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The chance of a type I error increases.
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What happens to the probability of type I error if you select a lower (i.e., more stringent) significance level?
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The chance of a type I error decreases.
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What is the relationship between type I error and type II error?
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As the probability of type I error increases, the probability of type II error decreases. As the probability of type I error decreases, the probability of type II error increases.
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Hypothesis
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Statement that predicts how two populations are expected to differ.
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