14. Descriptive Statistics Flashcards

(31 cards)

1
Q

descriptive Statistics

A

The branch of statistics dealing with how to describe and summarize data.

How can I communicate the important characteristics of my data?

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2
Q

frequency distribution

A

a (chart) showing the unique values of the data set, along with their frequency within the data set

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3
Q

bar graph

A

used to depict a frequency distribution of CATEGORICAL variables (space between bars)

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4
Q

histogram

A

used to depict a frequency distribution of a QUANTITATIVE variable (no space between bars)

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5
Q

mean

A

sum of all values divided by number of values

X = E(x) / n

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6
Q

median

A

centermost value when the set is ordered

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7
Q

mode

A

most frequent value in a set

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8
Q

mean, median & mode

A

measures of central tendency

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9
Q

nominal

A

a variable that can be CATEGORIZED, but not quantified.

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10
Q

ordinal

A

a variable that can be RANKED, but not quantified.

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11
Q

interval

A

a variable that can be QUANTIFIED, without a true relationship to 0

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12
Q

ratio

A

a variable that can be QUANTIFIED, where 0 indicates absence of quantity

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13
Q

variance

A

measure of average distance to mean, measured in square units

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14
Q

standard deviation

A

measure of average distance to mean

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15
Q

variance (formula)

A

E(x-M)^2 / n

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16
Q

standard deviation

A

(E (x-M)^2 / n ) ^1/2

17
Q

normal distribution

A

a distribution where 68% falls within one standard dev, 95% within 2 standard dev, and 99.7 within 3 standard devs of the mean

18
Q

unstandardized difference between means

A

compare two data sets
by finding the difference between the data set means, in natural units.
(ie. M1 - M2)

19
Q

cohen’s d

A

compare two data sets
by finding the difference between the data set means, in standardized units.
ie) M1 - M2 / SD
note: The SD can be for set 1 or 2

20
Q
  1. 2 = small
  2. 5 = medium
  3. 8 = large
A

thresholds of effect size for interpreting cohen’s d

21
Q

effect size

A

magnitude of relationship between two variables

22
Q

Pearson correlation coefficient

A

vector value [-1,1] that describes magnitude (absolute value) and direction (sign) of relationship between variables, when when variable is controlled for.

p = E (Zx Zy) / n

  • only valid for linear relationships*
  • scatterplot data first*
23
Q

partial correlation coefficient

A

vector value describing magnitude and direction of relationship between variables, when more than one variable is controlled for.

24
Q

curvilinear regression

A

technique used to determine nature of relationship between variables that have a curviliear relationship (ie. elliptical)

25
regression analysis
using one or more independent variables to predict the values of the dependent variables
26
regression analysis (appropriate cases)
predict values dependent variable with quantitative IV and DV
27
ANOVA (appropriate cases)
predict dependent variable values with categorical IV, quantitative DV
28
ANCOVA (appropriate cases)
predict dependant variable values with mixed IVs and quantitative DV
29
``` simple regression Y = dependent variable value m = slope = regression coefficient x = the single IV value b = y intercept of the line of regression ```
regression analysis in which only one IV is controlled for | Y = mx + b
30
``` multiple regression Y = dependent variable value m1 = first regression coefficient x1 = first x value m2 = second regression coefficient x2 = second x value ... etc b = line of regression y intercept ```
regression analysis in which more than one IV is controlled for Y = mx1 + mx2 + ... + b
31
contingency table
used to compare the relationship of categorical variables. | if % are horizontal, compare down the columns, else reverse