analysis and distributions Flashcards

1
Q

what is a scatterplot?

A

display relations between two quantative variables

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2
Q

how to know if a relationship is strong or weak

A
  1. strong = points lie close to the line
  2. weak = points are widely scattered
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3
Q

what does it mean when variables are correlated?

A

variables are related

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4
Q

what is the purpose of a correlation analysis? (3)

A

determine

  1. if linear relationship
  2. direction of relationship
  3. strength of relationship
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5
Q

what are correlation coefficients

A

number between 1 and -1

tells us strength and direction of relationship

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6
Q

what does a positive correlation coefficent mean?

A

positive relationship

positive correlation

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7
Q

what does a negative corellation coeeficient mean?

A

negative relationship

negative correlation

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8
Q

what is the difference between linear and non linear relationship?

A

linear = measuring correlations okay

non linear = cant measure correlations

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9
Q

what are the two types of coefficient

A
  1. pearson r
  2. spearman r
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10
Q

what is pearson r coefficient?

A
  1. calculated from raw scores
  2. suitable for interval or ratio data
  3. highly affected by outliers
  4. not suitable for skewed data
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11
Q

what is spearman r coefficient?

A
  1. calculated from ranking raw scores
  2. suitable for ordinal data
  3. marginally affected by outliers
  4. suitable for skewed data
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12
Q

what is a density curve?

A

histogram distribution of scores of ppt

useful when lots of ppt

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13
Q

what do density curves show?

A

the overall pattern of a distribution

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14
Q

density curve + median

A

point that divides area into two equal parts

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15
Q

density curve + quartiles

A

point that divide area under curve into quarters

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16
Q

density curve + mode

A

positions at the peak of the curve

17
Q

density curve + mean

A

balancing point of the curve

18
Q

what does symmetrical density curve mean?

A

mean = median = mode

19
Q

what does skewed density curve mean?

A

mean does NOT = median and mode

20
Q

how is a normal distribution described?

A

by a normal curve

21
Q

what is a normal curve? (5)

A
  1. symmetrical
  2. single peaked
  3. tail meet x axis at infinity
  4. location determined = mean
  5. shape determined = standard devation
22
Q

how to assume if data is normally distributed?

A

statistical tests

23
Q

what to do if data is not normally distributed

A

use a non parametric test

24
Q

what are z scores / standard scores?

A

allow us to compare values from different data sets

25
what is the standard score z of an observation ?
deviation of x from mean / standard deviation
26
how to get a standard normal distribution
standardising all values of a normal distribution
27
what does a standard normal distribution do?
allow us to determine proportions of observations
28
why are parametric & non parametric tests used?
test significant differences between data sets
29
what are 2 key things about parametric tests?
1. make assumptions about population parameters 2. require interval or ratio data
30
what does a violation of test assumptions leads to?
erroneous interpretations of the data
31
3 key things about non parametric tests
1. make no assumptions on popular parameters 2. can use nominal data 3. not as powerful as parametric tests
32
why is the chi square test for goodness of fit used? (4)
1. used on unrelated data 2. used to answer q about proportions 3. used to compare different levels of a variable 4. compare sample proportions to population proportions
33
what are observed frequencies?
number of ppt measured in indivdual catergories
34
what are expected frequencies
frequencies predicted by the null hypothesis
35