Unit 2 Test Flashcards

(42 cards)

1
Q

Raw Score

A

unchanged scores that are the direct result of measurement

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2
Q

Z-Score

A

specifies the precise location of each X value within a distribution

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3
Q

Deviation Score

A

measures the distance in points between X and μ and indicates whether X is located above or below the mean

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4
Q

Z-Score Transformation

A

if every X value is transformed into a z-score then the distribution of z-scores will have the following properties: Normal Shape, mean of 0, standard deviation of 1

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5
Q

Standardized Distribution

A

composed of scores that have been transformed to create predetermined values for μ and σ

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6
Q

Standardized Score

A

scores that have been standardized

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7
Q

Probability

A

fraction or proportion of all the possible outcomes

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8
Q

Random Sample

A

requires that each individual in the population has an equal chance of being selected

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9
Q

Independent Random Sample

A

probability of selecting any particular individual is independent of those individuals who have already been selected for the sample

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10
Q

Sampling with Replacement

A

Sampling with Replacement to keep the probabilities from changing form one selection to the next, it is necessary to return each individual to the population before you make the next selection

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11
Q

Unit Normal Table

A

complete listing of z-scores and proportions

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12
Q

Percentile Rank

A

the percentage of the individuals in the distribution who have scores that are less than or equal to the specific score

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13
Q

Percentile

A

when a score is referred to by it’s percentile rank

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14
Q

sampling error

A

the natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter

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15
Q

distribution of sample means

A

collection of sample means for all of the possible random samples of a particular size (n) that can be obtained from a population

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16
Q

Sampling Distribution

A

distribution of statistics obtained by selecting all of the possible samples of a specific size from a population

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17
Q

Central Limit Theorem

A

for any population with a mean μ and standard deviation σ, the distribution of sample means for sample size n will have a mean of μ and a standard deviation of σ/ √n and will approach a normal distribution as n approaches infinity

18
Q

Expected Value of M

A

the mean of the distribution of sample means is equal to the mean of the population of scores, μ

19
Q

Standard Error of M

A

standard deviation for the distribution of sample means. provides a measure of how much distance is expected on average between a sample mean (M) and a population mean (μ)

20
Q

Law of large numbers

A

the larger the sample size (n), the more probable it is that the sample mean is close to the population mean

21
Q

Hypothesis Test

A

statistical method that uses sample data to evaluate a hypothesis about a population

22
Q

Null Hypothesis

A

in the general population there is no change, no difference, or no relationship. Independent variable has no effect on the dependent variable for the population

23
Q

alternative hypothesis

A

there is a change, difference, or relationship for the general population. independent variable has an effect of the dependent variable

24
Q

level of significance

A

is a probability value that is used to define the concept of “very unlikely” in a hypothesis test

25
critical region
extreme sample values that are very unlikely to be obtained if the null hypothesis is true.
26
Type I error
(say treatment has an effect when there is no effect)
27
Type II Error
say treatment has no effect when there is an effect
28
Beta
probability of a type II error
29
Significant
when a result is very unlikely to occur when the null hypothesis is true
30
Test Statistic
indicates that the sample data are converted into a single, specific statistic that is used to test a hypotheses
31
Directional Test/ One-Tailed Test
statistical hypotheses specify either an increase or a decrease in the population mean
32
Effect Size
provide a measurement of the absolute magnitude of a treatment effect
33
Cohen's d
measures mean difference in terms of the standard deviation
34
Power
probability that the test will correctly reject a false null hypothesis
35
Alpha Level
probability that the test will lead to a Type I error if the null hypothesis is true
36
estimated standard error
an estimate of the real standard error when the value of σ is unknown
37
t statistic
used to test hypotheses about an unknown population mean μ, when the vaule of σ is unknown
38
degrees of freedom
describe the number of scores in a sample that are independent and free to vary
39
t distribution
complete set of t values computed for every possible random sample for a specific sample size (n) or a specific degrees of freedom (df)
40
estimated d
measure of effect size when population values are not known and you must substitute the corresponding sample values in their place
41
r^2
percentage of variance accounted for by the treatment
42
confidence interval
interval, or range of values, centered around a sample statistic