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19 Cards in this Set
- Front
- Back
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Descriptive statistics are used to summarize data and inferential statistics are used to ________.
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make inferences about a population based on data collected from a sample drawn from that population, and to do so with a pre-defined degree of confidence.
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An investigator uses a sample ________ to estimate a population ________.
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statistic
parameter |
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Symbols for Mean:
Population parameter = ________ Sample statistic = ________ |
μ (mu)
x̄-with-line-over-it ("X bar") or M |
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Symbols for Standard Deviation:
Population parameter = ________ Sample statistic = ________ |
σ (sigma)
S or SD |
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Symbols of Variance:
Population parameter = ________ Sample statistic = ________ |
σ^2 (sigma squared)
S^s (s-squared) or V |
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The Central Limit Theorem makes 3 predictions about a sampling distribution.
The first prediction relates to shape. It states: ________ |
Regardless of the shape of the distribution of individual scores in the population, as the sample size increases, the sampling distribution of the mean approaches a normal distribution.
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The Central Limit Theorem makes 3 predictions about a sampling distribution.
The second prediction relates to the mean. It states: ________ |
The mean of the sampling distribution of the mean is equal to the population mean.
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The Central Limit Theorem makes 3 predictions about a sampling distribution.
The third prediction relates to the standard deviation. It states: ________ |
The standard deviation of the sampling distribution of the mean is equal to the population standard deviation divided by the square root of the sample size
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The standard deviation of a sampling distribution of the mean is called the ________. The formula for this is ________.
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standard error of the mean
SEM = σ / √N |
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The standard error of the mean provides an estimate of the extent to which the mean of any one sample randomly drawn from a population can be expected to vary from the ________ as the result of _________.
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population mean
sampling error |
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As your sample size decreases, your SEM _________. Or, put another way, the smaller your sample, the more likely you will have ________ in your sample statistic.
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increases
error |
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The ________ hypotheses is stated in a way that implies the IV does not have an effect of the DV, whereas the ________ hypothesis is stated in a way that implies that the IV does have an effect on the DV.
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null
alternative |
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Hypotheses are always stated in terms of the sample statistic. True or False?
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False. The null and alternative hypotheses are always expressed in terms of a population parameter.
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After obtaining your data and running your analyses, you obtain a value that indicates where the sampling statistic falls in the sampling distribution. This statistic lies in the ________ if falls in one or both tails of the sampling distribution and the ________ if it falls in the central portion of the sampling distribution.
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rejection region, or region of unlikely values
retention region, or region of likely values |
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An investigator would retain the null hypothesis if the statistic landed in the ________ of the sampling distribution. Alternatively, an investigator would reject the null hypothesis if the statistic landed in the ________ of the sampling distribution.
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retention region
rejection region |
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The size of the rejection region in a sampling distribution depends on ________.
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α (alpha)
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Rejecting a true null hypothesis is referred to as a ________. The probability of this happening is equal to ________.
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Type I error
alpha |
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Retaining a true a false null hypothesis is referred to as a ________. The probability of this happening is equal to ________ and is more likely when these contributing factors are present: ________, ________, and ________.
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Type II error
β (beta) value of alpha is low, sample size is small, and the IV is not administered at a sufficient intensity. |
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When a statistical test allows the investigator to reject a false null hypothesis, the test is said to have ________. There are many factors which maximize the likelihood of this happening, such as ________.
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statistical power
increase alpha increase sample size increase effect size minimize error use a 1-tail test if appropriate use a parametric test |
