statistics Flashcards

1
Q

types of variables

A
  • qualitative: either dichotomous (binary), nominal, ordinal
  • quantitative: discrete or continuous
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2
Q

dichotomous
qualitative variable

A

data where every observation is in one of two categories (yes/no)

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3
Q

nominal
qualitative variable

A
  • 3 or more categories; no inherent ordering
  • ex cow breeds
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4
Q

ordinal
qualitative variables

A
  • categories in 3 or more categories with categories having inherent order
  • ex; gum colour; normal, pale, white
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5
Q

discrete data (counts)
quantitative variable

A
  • can only have values as whole numbers
  • ex; number of animals, heart rate, bacterial count
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6
Q

continuous
quantitative variable

A

have any value within a defined range
measurement
ex body weight, blood pressure, age, hormone concentration

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7
Q

descriptive statistics

A

conducted to explore patterns in data and to validate/ check the data

depend on the type of data

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8
Q

mean

A

average

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9
Q

median

A

line them all up and choose one in middle; not affected by a few extremes
- more accurate indicator of average

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10
Q

mode

A

most commonly observed variable

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11
Q

normal distribution

A

mode, median and mean are very similar

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12
Q

percentile

A
  • a number that indicates the percentage of values less than or equal to that number
  • 50th percentile is the median
  • 25% percentile means that at this data point 25% of data is less than that value
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13
Q

box and whisker plot

A

the box is the 25-75% percentile (lower and upper quartile), the line in the box is the median
any dots outside of the range are outliers; either more or less than 3/2 times of lower/upper quartile

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14
Q

variance and standard deviation are measures of

A

the spread of data around the mean

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15
Q

variance s^2

A

the sum of the squares of the difference of each of n values from the mean, divided by degrees of freedom (n-1)

so take the mean, then each data point that point minus the mean

square root it

then divide by n-1

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16
Q

standard deviation s

A

square root of variance
estimates the average variation of n the values from the mean
tells us how much variability can be expected among individuals

2/3s of the valies will be within mean +/- one standard deviation

95% of values will be within mean +/- 2 standard deviations

17
Q

standard error of the mean (SEM)

A

standard deviation/ square root of number sampled

how close sample mean is to actual mean in target population

17
Q

confidence interval (one sample only ie one type of experiment)

A

if you have a x confidence interval then in every 100 samples you collect x amount of them contain the actual mean

NOT CORRECT; if i do an experiment today there is x% chance i get the actual pop mean

18
Q

confidence interval example

A

mean +/= tSEM

t will be given to us

gives a range

19
Q

null hypothesis

A

there is NO difference between groups

20
Q

alternative hypothesis

A

hypothesis that there is a difference between groups

21
Q

want to disprove the

A

null hypothesis

22
Q

steps in hypothesis testing

A

1) from observed data, a test statistic is calculated
2) the probability (p-value) of observing a test statistic as large or larger than observed, if the null hypothesis is true is calculated
3) p value is compared to a cut off termed level of significance; should be small because we don’t want to reject null hypothesis when it is true

23
Q

p value

A

probability of observing a test statistic as large or larger than that observed, if null hypothesis is true
- if p very small, unlikely null is true; reject null hypothesis, 0.05 is alpha
- if p is large then data are consistent w the null hypothesis

24
Q

confidence (2 types of experiments)

A
  • 2 experiments; if x% confidence interval for mean contains 0, then there is no difference between the groups
  • so if the confidence interval ie range does NOT include zero then it is unlikely there is no difference ie between groups so we reject the null hypothesis
25
Q

chi square

A

2 variables
2 outcomes
yes/no
dichotomous

yes exposure no exposure
yes injury no injury
ex dogfights and injury

26
Q

one sample t test

A
  • want to find mean but not really, it does find you the mean but more importantly the p value and this goes for all of them
  • one variable, one group
  • continuous, normally dist

ex height in cows

27
Q

2 sample t test

A
  • one variable, 2 groups
  • continuous, normally dist

ex height in cows and humans

28
Q

paired t test

A
  • one variable 2 PAIRED groups
  • continuous, normally dist

ex blood pressure in high fibre diets vs low fibre diets

29
Q

anova analysis of variance

A
  • one variable, 3 or more groups
  • continuous, normally dist
  • ex height on cows, humans and goats
30
Q

wilcoxon’s signed rank test one sample

A
  • one variable, one group
  • continuous, NOT normally dist
31
Q

wilcoxon’s rank sum test

A

one variable, 2 groups
continuous not normally distributed

32
Q

wilcoxon’s signed rank test 2 matched pairs

A

one variable, 2 paired groups
continuous, not normally dist

33
Q

kruskal wallis

A
  • 1 variable, 3 or more groups
    continuous, not normally dist
34
Q

kaplan-meier curve with log rank

A

measures survival rate using log ranked tests