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BIOL 315 > Midterm > Flashcards

Midterm Flashcards

(58 cards)

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1
Q

what is population

A

set of all “subjects” relevant to scientific hypothesis

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2
Q

what are parameters

A

quantities describing a population

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3
Q

what are variables

A

characteristics that differ among individuals

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4
Q

describe two categorical variables

A

nominal and ordinal

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5
Q

describe two numerical variables

A

interval and ratio scaled

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6
Q

what is nominal scale

A

categorically discrete (species, sex, diet)

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7
Q

what is ordinal

A

ordering (small, medium, large)

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8
Q

what is interval scaled

A

intervals, arbitrary 0 (celsius, years BC)

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9
Q

what is ratio scaled

A

natural zero point (mass, abundance, duration)

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10
Q

what is a sample

A

subset of “subjects” selected from statistical population that are actually examined during particular study

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11
Q

what are sample statistics

A

calculated from collected sample to estimate population parameter

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12
Q

what is random sampling

A

equal chance of being selected, independent

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13
Q

what is haphazard sampling

A

does not follow systematic way of collecting samples

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14
Q

what are descriptive statistics

A

quantities that capture important features of frequency distribution

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15
Q

what is frequency distribution

A

describes the # of times (frequency) each value of a variable occurs in a sample

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16
Q

what are 3 measures of location

A

mean (average), median (middle value), mode (commonly occurring value)

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17
Q

what is measures of spread

A

description of variation around the typical individual

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18
Q

what is a residual

A

difference btw observation and mean

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19
Q

what are degrees of freedom

A

describe the # of values in a calculation that are free to vary

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20
Q

what is a positive skew

A

tail on right

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21
Q

what is a negative skew

A

tail on left

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22
Q

what is estimation

A

process of inferring a population parameter from sample data

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23
Q

what is sampling distribution

A

probability distribution of all values for an estimate that we might have obtained when we sampled the population (pot the distribution of means calculated from sampling the population)

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24
Q

what is bias

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A

difference between the mean of the sampling distribution of a sample statistic, and the true population value

25
what is standard error
standard deviation of the sampling distribution of a sample statistic measures sampling error (standard deviation (s) of sample/square root of sample size (n))
26
what is a 95% confidence interval
if you sampled repeated, 95% of the time the resulting interval would contain the true population
27
what is probability
likelihood of hypothesis given data
28
what is hypothesis testing
inferring whether statistical claims about the parameters (statistical hypotheses) are true or not
29
assumption of null hypothesis
any variation we see is due to sampling error alone
30
what is null hypothesis
specific statement about population parameter made for purpose of argument
31
what is alternate hypothesis
represents all other possible parameter values except that is stated in the null hypothesis (mutually exclusive and exhaustive)
32
what is the null distribution
probability distribution of test statistic values when a random sample is taken from a hypothetical population for which the null hypothesis is true
33
how to determine p value
compare test statistic value to the null distribution and determine probability of obtaining the data
34
what is significance value
probability used as a criterion for rejecting the null hypothesis
35
P-value = significance level
reject null
36
p-value>significance level
fail to reject
37
example of good biological conclusion
The probability of winning a wrestling match differs significantly from 0.50 when the athlete is wearing a red shirt (name of test, test statistic, n (or df), P
38
what is a critical value
boundary btw values that support null and those that lead to reject null (if test statistic more extreme you reject null)
39
at critical values, area under tails
one tailed - 5% | two tailed - 2.5%
40
what is type 1 error
reject true null (false positive)
41
what is type 2 error
failing to reject false null (false negative)
42
what does power depend on
what alternative hypothesis is true | type 1 error rate sample size (precision)
43
what is power
the probability we will reject a false null
44
what is a binomial distribution
discrete distribution that arises from the outcome of a number of "Bernoulli Trials"
45
what are 3 characteristics of bernoulli trials
- only 2 possible outcomes - outcome of each bernoulli trial is independent - probability of success is identical for all trials
46
what are 3 characteristics of binomial distribution
- distribution is completely determined by the parameters p (probability of success) and n (# of trials) - mean of binomial distribution is mean = np - variance of binomial distribution ??????
47
what is a poisson distribution
distribution describes the frequency distribution of events that occur rarely and randomly. success are described in blocks of time or space (rather than probability for a given trial)
48
what are the 4 conditions of poisson
- probability of 2 or more occurrences in a single sample subdivision is negligibly small - probability of 1 occurrence in a sample subdivision is proportional to the size of the subdivisions (in time or space) - outcome in 1 subdivision of the sample unit is independent of the outcome in all other subdivisions - probability of an occurrence is identical for all sample subdivisions
49
what are two analysis of frequency tests and what do they analyze
goodness of fit contingency analysis analyze frequency of observations in different categories (compares observed freq of observations in different categories to expected freq under some observation; if they are sufficiently different, reject null
50
what are two tests for the analysis of categorical data
chi squared test | log likelihood ratio test (G test)
51
for chi-squared what do Oi Ei and k mean
Oi-observed frequency (# of observations) in category i Ei-expected frequency k-total number of categories
52
what steps do both tests involve
-calculate expected freq for each category calculate test stat based on dissimilarity btw observed and expected -compare test stat to chi squared distribution w/ appropriate df
53
what is goodness of fit
compares frequencies/counts to discrete probability distribution tests whether observed distribution of counts across classes consistent w/ what you'd expect based on hypothesized probability distribution asks if hypothesized prob. is a good "fit" to observed data
54
what is the null hypothesis for goodness of fit
proportion of observation in a category are equal to expected proportions
55
how does the contingency test differ from goodness of fit
asking whether two categorical variables are associated with each other (variable is "contingent" or "dependent on" the other)
56
what are extrinsic expectations/hypotheses
are when expected freq are derived from info other than the data analyzing
57
what are intrinsic expectations/hypotheses
when expected freq are derived from the data you are analyzing (no info asumed prior to study)
58
what is a contingency table
analyze whether which row observations into is contingent on which column it falls into and vice versa

BIOL 315 (1 decks)

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