Flashcards in Chapter 16 Significance Testing - A Real Effect? Deck (25)

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## Alpha

### Percentage of the probability area under H0 that forms the 'rejection region'; level set for acceptable probability of Type 1 error under H0

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## Beta

### If the null hypothesis is not true, this is the probability that a Type 2 error will be made

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## Significance Test/Decision

### Test performed in order to decide whether the null hypothesis should be retained or rejected

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## Significance

### A significant effect is declared when the probability of the finding occurring under H0 is less than the set level of alpha

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## Inferential Test/Statistics

### Procedures for making inferences about whole populations form which samples are drawn. e.g., significance tests

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## Null Hypothesis

### Assumption of no effect in the population from which samples are drawn (e.g., no mean population difference or zero correlation)

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## Alternative Hypothesis (H1)

### Assumption than an effect exists (e.g., that populations differ or population correlation is not zero)

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## Logical Probability

### A measure of probability calculated from logical first principles

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## Probability

### A numerical measure of pure 'chance' (randomly based) occurrence of events

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## Empirical

### A measure of probability based on existing frequencies of occurrence of target effects

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## Significance Levels

### Levels of probability at which it is agreed to reject H0. If the probability of obtained results under H0 is less than the set level, H0 is rejected.

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## Critical Value

### Value that the result of the test statistic (e.g. z) must reach in order for the null hypothesis to be rejected

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## Non-Directional Hypothesis

### Hypothesis that does not state in which direction a difference or correlation exists

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## Probability Distribution

### A histogram of the probabilities associated with the complete range of possible events

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## Rejection Region

### Area of (sampling) distribution where, if a result falls within it, H0 is rejected; the more extreme area cut off by the critical value

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## Type I Error

### Mistake made in rejecting the null hypothesis when it is true

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## Type II Error

### Mistake made in retaining the null hypothesis when it is false

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## Effect Size

### The size of the effect being investigated (difference or correlation) as it exists in the population

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## Power

### 1-Beta. The probability of not making a Type II error if a real effect exists; the probability of obtaining a case or sample statistic above the level cut off by beta in the population defined by the alternative hypothesis.

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## p is less than or equal to .1

### Significance level generally considered too high for rejection of the null hypothesis but where, if p under H0 is this low, further investigation might be merited

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## p is less than or equal to .05

### Conventional significance level

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## p is less than or equal to .01

### Significance level preferred for greater confidence than that given by the conventional one and that should be set where research is controversial or a one-shot-only trial

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## Directional Hypothesis

### Hypothesis that states which way a difference or correlation exists - e.g. population mean A > population mean B, or correlation is negative

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## One-tailed test

### Test referring to only one tail of the distribution under H0; may be used if the alternative hypothesis is directional (but controversial)

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