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Psych Stats 201 > Psych Stats Quiz #1 4/3/23 > Flashcards

Psych Stats Quiz #1 4/3/23 Flashcards

1
Q

descriptive stats

A

used to summarize and describe a set of data in a clear and convenient fashion usually through numerical values

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2
Q

ex of descriptive stats

A

GPA - summarizes all grades your earned in college

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3
Q

inferential stats

A

because its not practical/realistic/ethical to measure everyone in a population inferential stats draws inferences about a population based upon an observed sample

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4
Q

ex of inferential stats

A

smoker study - studying a subset of smokers to apply observed data to the greater smoking population

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5
Q

sample

A

subset of scores from a population - measure relatively small group of people

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6
Q

population

A

collection of measurements that share a common characteristic, not necessarily people

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7
Q

random sample

A

selected so that every score in the population has an equal chance of being included
ex. sample of smokers for the smoker study

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8
Q

variability

A

people (observations) differ from one another
describes the extent to which scores in a group differ from one another or how spread out or scattered they are

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9
Q

reasons for variability

A

individual differences
unsystematic differences in procedure
research manipulation

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10
Q

measurement

A

the use of a rule to assign a number to a specific observation of a variable
ex. length or weight

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11
Q

measurement scale property: category

A

observations assigned a different number representing the category

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12
Q

measurement scale property: ordinal

A

can be used to measure those with the least amount to the most amount

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13
Q

measurement scale property: equal intervals

A

1 unit difference remains constant

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14
Q

measurement scale property: absolute zero

A

0 represents absence of something

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15
Q

type of scale: nominal

A

categories - qualitative but not quantitative
ex. breed of dog

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16
Q

type of scale: ordinal

A

ranks
ex. class rank = 1 vs 2 vs 3 but doesn’t describe the interval between the ranks

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17
Q

type of scale: interval

A

spacing between intervales is known but there is no absolute zero point
ex. temperature (C or F)

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18
Q

type of scale: ratio

A

spacing between intervals is known and a zero point exists
ex. time and distance

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19
Q

frequency distribution

A

how many times each score value is repeated via table or figure (bar graph)

20
Q

histogram: shape

A

normal distribution bell curve - most scores cluster in the middle and then extreme scores at the tails
ex. IQ scores

21
Q

histogram: symmetrical distributions

A

more than one peak - bimodal distribution

22
Q

histogram: skewed distributions

A

the direction of skew is determined by which direction the tail of the distribution points
if the tail goes in a positive direction = positively skewed and vice versa for neg

23
Q

histogram: central tendency

A

a typical or representative score value near the center of the distribution

24
Q

variability

A

how different are the scores from one another

25
Q

variable

A

a measurement that changes from one observation to the next
ex. CESD changes from one smoker to the next

26
Q

constant

A

measurements that stay the same from one observation to the next
ex. boiling point of water

27
Q

measures of central tendency: mean

A

numerical average, the sum of scores divided by sample size
∑x/n

28
Q

measures of central tendency: median

A

the score value with half the scores above and below
50th percentile
organize from least to greatest and find middle
if odd number add together and divide by 2

29
Q

measures of central tendency: mode

A

the most frequently occurring score
can be more than 1 in a given set

30
Q

measures of central tendency: symmetrical distribution

A

unimodal distribution means that the three scores will be the same spot/number

31
Q

measures of central tendency: skewed distributions

A

extreme scores have a larger effect on the mean
in these cases the median may be better

32
Q

measures of variability: range

A

largest score minus smallest socre
doesn’t show the completely different distributions of values
very different sets could have the same range

33
Q

measures of central tendency: sample variance

A

(s²) = sum of squared deviations of each score from the mean divided by n-1
variance determines the deviation around the mean

34
Q

measures of central tendency: sample variance formula

A

s² = ∑(x - M)²/ n - 1
sum of (all values subtracted from the mean) squared/ divided by the number of cases minus 1

35
Q

measures of central tendency: sample variance steps

A
  1. compute the mean
  2. compute each deviation
  3. square each deviation
  4. sum all the squares (sum of the square deviations from the mean)
36
Q

measures of central tendency: standard deviations (s)

A

the square root of the variance
the measure of how dispersed the data is in relation to the mean
low deviation = the data is clustered around the mean
high deviation = the data is more spread out

37
Q

validity

A

how well the measurement rule actually measures the variable under consideration as opposed to some other variable
ex. some intelligence test measures actual intelligence rather than being influenced by creativity or memory

38
Q

reliability

A

an index of how consistently the rule assigns the same number to the same observation
ex. an intelligence test is reliable if it assigns the same number to an individual each time they take the text

39
Q

cumulative frequency

A

the frequency of a score value plus the frequency of all smaller score values
ex.
Month # cars sold CF
January 20 20
February 30 20 + 30 = 50
March 15 50 + 15 = 65
April 18 65 + 18 = 83

40
Q

relative frequency

A

divide the score value’s frequency by the total number of observations in the distribution
score value = 3
# of observations = 10

rf = 3/10

41
Q

cumulative relative frequency

A

tabulation of the relative frequencies of all measurements at or below a given score value

42
Q

class interval

A

range of score values

43
Q

grouped frequency distribution

A

tabulation of the number of measurements in each class interval

44
Q

relative frequency histogram

A

heights of bars represent relative frequencies of score values (or class intervals)

45
Q

population variance

A

average of the squared deviations of each score from the mean (μ)
ex. {3,7,11}
sum of the square of distances = 32
32/3 = 10.6

46
Q

population standard deviation (σ)

A

the positive square root of the population variance

Psych Stats 201 (5 decks)

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