Statistics/Stat Approaches Flashcards

(32 cards)

1
Q

Mean

A

Addition of all samples divided by number of samples

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2
Q

Median

A

Point above which have of the observations fall

  • not affected by outliers
  • more accurate than the “average” in skewed distributions
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3
Q

Mode

A

Most common observed variable

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4
Q

Right Skewed Distribution

A

Tail is on the right hand side

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5
Q

Left Skewed Distribution

A

Tail is on the left hand side

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6
Q

Measures of spread (2)

A

1) Range
2) Percentile
3) Variance
4) Standard Deviation

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7
Q

Box and Whisker plot contains: (7)

A

1) High outlier
2) Maximum whisker
3) Upper quartile (Q3)
4) Median
5) Lower quartile (Q1)
6) Minimum whisker
7) Low Outlier

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8
Q

Variance

A

S^2
is the sum of the squares of differences from the mean / degrees of freedom minus 1

S^2 = (difference)^2 + (difference)^2 / (n-1)

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9
Q

Standard Deviations

A

S

  • square root of the sample variance
  • estimates average variation of n-values from the mean
  • tells us how much variability is expected among individuals
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10
Q

Binary or dichotomous data

A

numbers or % in each category

yes/no style answers

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11
Q

Nominal Data

A

number and % of subjects in each category

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12
Q

Ordinal Data

A

Numbers and % of subjects in each category

  • median
  • smallest and largest
  • values/range
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13
Q

Quantitative Data

A

Graph and visualize the distribution

  • mean/median/mode
  • smallest and largest
  • values/range
  • percentiles
  • variances
  • standard deviations
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14
Q

How are confidence intervals derived and interpreted

A

Ex) 95% CI

  • The interval from ___ to ___ has a 95% chance (probability) to contain the true population mean
  • greater sample size = smaller CI
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15
Q

Concept of hypothesis testing and steps (3)

A
  • Hypothesis testing involves comparison of groups
    1) Test statistic (t-distribution, z-dist, f-dist)
    2) P-value
    3) p-value compared to alpha (0.05, 0.1, etc)
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16
Q

Interpretation of p-values

A

P-value is an indication of the “data occurring” if the null was true

p < alpha = reject Ho
p > alpha = Do not reject Ho

17
Q

How are Chi-squared tests derived from 2x2 tables

A

2x2 tables are expanded to show observed vs. expected numbers

Chi-squared uses differences in observed vs. expected numbers to calculate chi-squared statistic

18
Q

Alternate hypothesis

A

Ha: two groups are different

19
Q

What does it mean when a CI for means/risk difference contains 0?

A

Means it is non-significant

20
Q

What does it mean when CI for odds ratio/risk ratio contains 1?

A

Non-significant

21
Q

What does it mean when CI for odds ratio/risk ratio contains 1?

A

Non-significant

22
Q

Parametric Tests (3)

A

When data is normally distributed

1) T-test
2) ANOVA
3) Regression

23
Q

Non-Parametric Tests (2)

A

When data is not normally distributed

1) Wilcoxon rank test
2) Kruskal-wallis test

24
Q

T-test

A

Parametric test

  • Test whether the mean of a sample or population is different from a particular value
  • one sample or one group OR
  • two groups (2 sample t-test)
25
ANOVA
- Parametric test ( continuous normal distribution) - Test equality of the means between 2 or more populations - groups must have equal variance
26
Paired T-test
Same organism used for 2 or more observations - Parametric test - continuous and normally distributed - 2 comparison groups but one organism
27
Linear Regression
- outcome continuous, normally distributed - Parametric test - 1 or more predictors leads to 1 outcome Time = race distance + sex
28
Wilcoxon rank test
- Non-parametric data (continuous, not normally distributed) - test mean of sample/pop. is different to particular value - equivalent to 1 sample t-test, or 2 sample t-test - can also be used for paired samples/populations
29
Kruskal-Wallis test
Non-Parametric data (continuous, not normally distributed) - used to test equality of MEDIANS or two or more samples/populations - 2 or more comparison groups - Equivalent to ANOVA
30
Homoscedasticity
Equal variance
31
Logarithmic Regression
Not normally distributed outcome Outcome: Dichotomous/binary 1 or more predictor leads to outcome odds ratio converted to probability
32
Logarithmic Regression
Not normally distributed outcome Outcome: Dichotomous/binary 1 or more predictor leads to outcome odds ratio converted to probability (odds) heart disease (yes/no) = age (years) + family history (yes/no) + smoking (years)