Exam #1 Flashcards

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1
Q

Summation of x divided by n

A

mean

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2
Q
Summation of (x- pop. mean) squared
Summation of (x- sample mean) squared
A

Sum of squares (ss)

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3
Q

SS divided by N

ss divided by N-1

A

variance

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4
Q

square root of variance squared

A

standard deviation

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5
Q

X - pop mean divided by variance

X - sample mean divided by variance

A

z score of individuals

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6
Q

sample mean - population mean divided by (variance divided by square root of sample size)

A

z-score of means

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7
Q

Nominal

A

categorical

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8
Q

ordinal

A

rank order

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9
Q

interval

A

equal distance between measurements

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10
Q

rational

A

meaningful zero

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11
Q

Kurtosis

A

peakedness of the distribution

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12
Q

lepokurtosis

A

a lot of scores in the middle

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13
Q

platykurtosis

A

flat

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14
Q

When do you use the median?

A
  1. skewed/non normal
  2. undetermined values (SAT scores)
  3. open ended items (1,2,3, >4)
  4. ordinal
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15
Q

When do you use a bar graph?

A

Nominal (qualitative) (categorical)

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16
Q

when do you use a histogram?

A

interval or ratio (quantitative)

17
Q

What effects variability?

A
  1. outliers
  2. sample size if really small
  3. stability under sampling
  4. open ended distributions
18
Q

SS interpret

A

Summed squared distance from the mean

19
Q

variance interpret

A

typical squared distance from the mean

20
Q

Standard deviation interpret

A

typical distance between an individual score and an average score

21
Q

sampling error

A

error between a sample statistic and the corresponding population parameter

22
Q

distribution of sample means

A

set of means from all the possible random samples of a specific size selected from a specific population

23
Q

expected value of M

A

the mean of the distribution of sample means, equal to the population mean

24
Q

standard error of M

A

standard deviation of sample mean

variance(m) = variance/ square root of n

25
Q

Central Limit Theorem

A

normal is n=30 or more

26
Q

what is standard error determined by?

A

(1) the size of the sample and

(2) the standard deviation of the population from which the sample is selected

27
Q

Law of large numbers

A

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

28
Q

Use of a sample not randomly selected in an experiment

A

limits the degree to which the results can be generalized to a population

29
Q

We generally like the standard deviation when we are trying to describe a sample of data because

A

it is expressed in units of the raw metric

30
Q

SS definition

A

the sum of the squared deviation

31
Q

variance definition

A

the mean squared deviation

32
Q

Standard deviation definition

A

square root of the variance and provides a measure of the standard distance from the mean

33
Q

mean definition

A

the sum of the scores divided by the number of scores