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

A

-

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
Q

negatively skewed distribution

A

scores tend to pile up on the right side + tail points to the left

26
Q

Grouped Frequency Distribution

A

values in intervals ⇒ apparent limits of the interval

upper + lower boundaries involve real limits

27
Q

Stem-and-Leaf Displays

A

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
Q

Stem-and-Leaf Displays

A

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
Q

Percentile Ranks

A

relative location of individual scores within a distribution

percentage of individuals with scores equal to/less than X value

30
Q

Interpolation

A

cumulative % identifies percentile rank for upper real limit

31
Q

Interpolation

A

mathematical process based on assumption that scores + % change in regular, linear fashion as you move through interval from one end to other

32
Q

Interpolation

A
  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
Q

linear interpolation

A

“Assumption of linearity permits computation of intermediate percentile ranks and percentiles

34
Q

Interpolation

A

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.