PSY201: Chapter 2 - Frequency Distributions Flashcards

1
Q

Frequency Distributions basics

A

simplifying + organizing data

organized tabulation showing exactly how many individuals located in each category on scale of measurement

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2
Q

Frequency Distributions basics

A

presents an organized pic of entire set of scores

shows where each individual is located relative to others in distribution

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3
Q

Frequency Distributions Tables

A

2 columns - 1 listing categories (X) + 1 for frequency (f)

X column, values listed from highest to lowest, without skipping any

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4
Q

Frequency Distributions Tables

A

frequency column - tallies determined for frequencies for each X value
sum of frequencies should equal N

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5
Q

Frequency Distributions Tables

A

3rd column - proportion (p) for each category: p = f/N
sum of the p column = 1.00
4th column - % of distribution corresponding to each X - multiplying p by 100
sum of the % column = 100%.
5th column for cumulative percent

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6
Q

Regular Frequency Distribution

A

Summarizes sets of data that require little additional organization
data span relatively narrow range of values/categories
All raw data shown

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7
Q

Grouped Frequency Distribution

A

Used when set of scores covers wide range of values

Group data into intervals – ranges of values - to make easier to understand

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8
Q

Grouped Frequency Distribution

A

X column lists groups of scores - class intervals

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9
Q

Grouped Frequency Distribution Rules

A
  1. interval width selected so table has approx 10 class intervals
  2. Width simple number (2, 5, 10)
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10
Q

Grouped Frequency Distribution Rules

A
3. Bottom score in each class interval multiple of width
width of 10, bottom score multiple of 10
4. Intervals should all have the same width & cover complete range scores
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11
Q

Grouped Frequency Distribution

A

Real Limits
Advantage of no ambiguity of class membership
No gaps
easily transformed into graphical representation (frequency histogram), directly from table

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12
Q

Frequency distribution graphs

A

Visual representation of frequencies
Useful because they show the entire set of scores
can determine highest score, lowest score, + where scores are centered
shows whether scores clustered together/scattered over wide range

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13
Q

Frequency distribution graphs

A

In most, X values listed on the X axis + frequencies listed on the Y axis

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14
Q

Frequency distribution graphs

A

X consist of numerical scores from interval/ratio scale ⇒ histogram/polygon
nominal/ordinal ⇒ bar graphs

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15
Q

Graphs for Interval/Ratio scales: Histograms

A
Bar centered above each score/class interval  
height of bar = frequency + width extends to real limits
adjacent bars touch
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16
Q

Graphs for Interval/Ratio scales Polygons

A

dot centered above each score - height of dot = frequency
join dots with straight lines
additional line drawn at each end to bring graph back to zero frequency

17
Q

Polygons

A

for plotting frequency of continuous variables
Communicates same info
shape of distribution emphasized
Can be superimposed on a histogram

18
Q

Graphs for Nominal or Ordinal data: Bar graphs

A

X nominal/ordinal
gaps/spaces left betw adjacent bars
scale made up of distinct categories – not continuous/not necessarily same size

19
Q

Pie charts

20
Q

Relative frequency

A

Many pops so large - impossible to know exact frequency

distributions can be shown using relative frequency instead

21
Q

Smooth curve

A

scores in pop measured on interval/ratio scale ⇒ present distribution as smooth curve not a jagged polygon
emphasizes fact that distribution not showing exact frequency for each category

22
Q

Shape

A

graph shows shape of distribution

symmetrical if left side of the graph is (roughly) mirror image of the right side

23
Q

Shape

A

bell- shaped normal distribution

skewed - scores pile up on one side of the distribution, leaving “tail” of few extreme values on other side

24
Q

positively skewed distribution

A

scores tend to pile up on left side of the distribution with tail tapering off to the right

25
negatively skewed distribution
scores tend to pile up on the right side + tail points to the left
26
Grouped Frequency Distribution
values in intervals ⇒ apparent limits of the interval | upper + lower boundaries involve real limits
27
Stem-and-Leaf Displays
stem-and-leaf display provides very efficient method for obtaining + displaying frequency distribution Each score divided into stem consisting of first digit/digits, + leaf consisting of final digit
28
Stem-and-Leaf Displays
write leaf for each score beside its stem organized picture of entire distribution number of leafs beside each stem = frequency individual leafs identify individual scores.
29
Percentile Ranks
relative location of individual scores within a distribution | percentage of individuals with scores equal to/less than X value
30
Interpolation
cumulative % identifies percentile rank for upper real limit
31
Interpolation
mathematical process based on assumption that scores + % change in regular, linear fashion as you move through interval from one end to other
32
Interpolation
1. Find width of interval on both scales. 2. Locate position of intermediate value in interval fraction = distance from top of interval/interval width 3. Use fraction to determine distance from top of interval on other scale distance = fraction x width (of scale we want to find) 4. Use distance from top to determine position on other scale
33
linear interpolation
"Assumption of linearity permits computation of intermediate percentile ranks and percentiles
34
Interpolation
single interval measured on 2 separate scales endpoints known Given intermediate value on 1 of the scale task is to estimate corresponding intermediate value on other scale.