Flashcards in Psychology 202 - Test 1 Deck (36):
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data
information
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statistics
branch of mathematics focused on organization, analysis, and interpretation of a group of numbers
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descriptive statistics
used to describe a group of numbers from a study
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inferential
used to draw conclusions from collected data
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variable
characteristic of something or someone that can have different vaules
i.e. people, [usually] mind
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constant
if the characteristic does not/can not vary
- dependent on perspective
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values
numbr or category
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score
particular value on a variable
- tells how much there is of what is being measured
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equal-interval variable
a variable in which the numbers stand for approximately equal amounts of what is being measured
i.e. in stress rating, difference between 4 & 6 is the same as the difference between 7 & 9
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ratio scale
used if the equal-interval variable has an absolute zero point
i.e. number of siblings > zero means something and is important
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absolute zero point
value of zero on the variable indicates complete absence of the variable
i.e. number of siblings > zero = no siblings
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rank order variable
a variable where numbers stand ONLY for the relative ranking
- ordinal variables
- provides less info/less accurate than equal-interval but sometimes easier/only info available
i.e. olympics (1,2,3) but 1 & 2 can be close while three was far behind them
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nominal variable
variable in which the values differ as names or categories
i.e. favorite sports team
*can go from nominal to numeric but not the other way around
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discrete variable
specific values and nothing in between
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continuous variable
has infinite number of values in between any two values
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population
the entire group of people that is studied
- can range from small to the entire world depending on the question
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sample
a subset of the population
- small/more manageable group to study
-(hopefully) identical to population > generalizability
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frequency table
table that lists all values that are possible along with the number of cases that have that value
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relative frequency table
tells frequency AND frequency relative to other scores
- divide number of cases in each value by total number of cases
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histogram
graphic representatio of frequency of scores
- x = possible values
- y = number of cases
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number of peaks (histogram)
1 peak = unimodal
2 peaks = bimodal
3+ peaks = multimodal
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symmetrical distributions
roughly equal scores on both sides of the peak
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skewed distributions
unequal scores on each side of the peak
- positively skewed > more scores on left side
- negatively skewed > more scores on the right side
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normal curve
symmetrical, bell shaped curve that has changes in curve direction at exactly 1 standard deviation above and 1 standard deviation below the mean
- theoretical distribution
- mode, median, and mean are all exactly the same number
- Middle point = average point = most frequent point
- more scores you have = closer you get to normal distribution
- assume data would look like normal curve if we had enough
- 68.2% = 1 SD
- 95.4% = 2 SD
- 99.7% = 3 SD
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platykurtic
most values have roughly the same frequency
- upside down plate
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leptokurtic
very few values have a high frequency
- tower
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measure of central tendency
single number that we use to describe a distribution of scores
- representative of all scores
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mean
mathematical average of a group of scores
- μ = population, M = sample
- mean = Σx/N
- most stable measure of central tendency
- takes all scores into account
- can be value no one got
- incredibly sensative to outliers
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mode
most frequent score in a distribution
- only measure that can be used with nominal data
- says nothing about other scores
-doesn't tell the placement of the score
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median
score in the middle of a distribution
- scores in order from smallest to largest and find middle score
- can be the same as mode
- can be score no one has/received
- does not mean there is equality in the range
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variability
the amount of variation in a distribution of scores
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range
the difference between the highest and lowest score
- very unstable
- no additional stats calculated
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variance
measure of variability that considers how different each score in a distribution is from the mean
- extremely important in stats
- population = δ
- sample = SD
- variance = Σ(x - M)²/N
- SS = Σ(x - μ)²
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standard deviation
the average amount that a set of scores differ from one another (how much scores vary)
- population =
- sample = SD
- standard deviation = √Σ(x - μ)²/N
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z-score
number of standard deviations above or below the mean an actual score is
- standardizes scores
- z = (x - M)/SD
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