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Experimental Design And Data Analysis > Definitions > Flashcards

Definitions Flashcards

1
Q

What happens in inductive reasoning?

A

From a specific premise to general conclusions

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2
Q

What happens in deductive reasoning?

A

From a general premise to specific conclusions

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3
Q

What is the definition of a hypothesis?

A

Statement that is tested by investigation (preferably experimental), in contrast to a model or theory

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4
Q

What is a research hypothesis?

A

A hypothesis derived from questions, models and theories

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5
Q

What is a statistical hypothesis?

A

Come from statistics and represent tests of the predictions of the research hypothesis

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6
Q

What is a sample study?

A

Estimate the value of a parameter for a population

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7
Q

What is an observational study?

A

Explain how two population parameters relate to each other without interfering or affecting the individuals

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8
Q

What is an experiment?

A

Intervention to explore causality

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9
Q

What is sample or empirical distribution?

A

The pattern that the data makes

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10
Q

What is Population distribution?

A

The pattern that the whole group of interest makes

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11
Q

What is uncertainty?

A

The region in which the parameter could fall

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12
Q

What is the sampling distribution?

A

The sample distribution of a statistic

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13
Q

What is kurtosis?

A

Sharpness of the peak of a frequency-distribution curve

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14
Q

What is a type 2 error?

A

Not rejecting a false H0

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15
Q

What is a type 1 error?

A

Incorrectly rejecting a true H0

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16
Q

What is a p-value?

A

The probability of getting a sample as extreme or more extreme as ours given that the null hypothesis is true

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17
Q

What is accuracy?

A

How close a measurement is to the true value intended to be measured

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18
Q

What is Precision?

A

How repeatable a measure is, irrespective of how close it is to the actual value

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19
Q

What is bias?

A

Systematic lack of accuracy

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20
Q

What is an experimental unit?

A

The physical entity which can be assigned to a treatment

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21
Q

What is a treatment group?

A

A group of experimental units that all receive the same treatment

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22
Q

What is an experimental factor?

A

A set of treatments and controls

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23
Q

What is replication?

A

The process of assigning several experimental units to the same treatment/intervention

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24
Q

What is independence and pseudoreplication?

A

Value of a measurement from one unit is not affected by the values of other units

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25
Q

What is the standard error?

A

Precision of mean as an estimated parameter

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26
Q

What does standard deviation show?

A

Spread of data

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27
Q

What is a priori?

A

Knowledge considered to be true without investigation (like π=3.14)

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28
Q

What is the F-distribution?

A

Partition of variability

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29
Q

What is homoscedasticity?

A

Assumption of equal variances in different groups being compared

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30
Q

What is residual term?

A

The difference between the observed Y value and the fitted Y value for the same X

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31
Q

What are influential cases?

A

Extreme values that might influence the regression results when included or excluded from the analysis

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32
Q

What is a binary response?

A

A response or trait that takes on one of two possibilities

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33
Q

What are examples of sampling units?

A

Cohorts of patients
Clusters of related genes
Regions in tissues or genes

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34
Q

What are examples of experimental units?

A

Individual organisms
Tissue culture plates

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35
Q

What is a control group?

A

Group used for comparison - not always needed

36
Q

What is a feature of an experimental group?

A

Vary by only one variable
Randomly sampled
At least three replicas

37
Q

What is an independent variable?

A

The one we change between groups

38
Q

What is a dependent variable?

A

The one that changes in the experimental group as a result

(Ie depends on another thing)

39
Q

What is a controlled variable?

A

The one we keep constant

40
Q

What is an experimental variable?

A

Actual property measured by the individual observation

41
Q

What is a random variable?

A

Measured property whose results are not known before a sample is taken

42
Q

What is falsificationism?

A

Hypotheses are there to be disproved because proof is logically impossible

43
Q

What are the steps of a falsificationist test?

A

Observation of a pattern or a deviation from a pattern

Explanation of an observed pattern is a model or a theory

Predictions deduced from the model or theory

Experimental tests

44
Q

Practicalities to think about when asking questions in biology

A

Ethics
Has the material been prepared in a way that doesnt affect outcome
Can we study material of interest under Lab conditions
Suitable experimental system
Justifiable assumptions

45
Q

What does hypothesis formulation depend on?

A

Systematic observation

46
Q

What are the advantages of experimentation?

A

Reliable evidence to infer causality
Distinguish between hypothesis
Independently assess the effect of external factors on variables

47
Q

What are the disadvantages of experimentation?

A

Experiments involve artificial manipulations that can be amplified by the laboratory environment

The bigger space or time the thing occupies, the harder it is to experiment on

Experiments are directly challenged by their natural variability

Drawing general conclusions from experiments is not always possible

48
Q

What should a set of units represent?

A

A sample of a clearly designed population - all the possible observations we are interested in

49
Q

What are the types of numerical data?

A

Discrete (counts) and continuous (measurements)

50
Q

What are the different types of categorical data?

A

Nominal (categories with no ranked order)
Ordinal (Ranked/ ordered categories)

51
Q

What is a sample space?

A

All potential values for a variable

52
Q

What is external validity?

A

Can we generalise (from mice to humans)

53
Q

What is internal validity?

A

Does the sample accurately reflect what is going on in the group we are studying

54
Q

What is the difference between sample and population distribution?

A

Sample = the pattern the data makes

Population = the pattern the whole group of interest makes

55
Q

What does the area underneath a normal distribution curve represent?

A

The proportion of the population being that thing

56
Q

What is the central limit theorem?

A

If you have a population with a mean and a standard deviation and take big enough random samples from the population, then the distribution of the sample means will be approx normally distributed

57
Q

What is standard error of the mean?

A

How much uncertainty there is in the estimate of the population mean

58
Q

What are confidence intervals calculated using?

A

The standard error of the mean

59
Q

What are the main functions of graphs?

A

Exploration
Analysis
Presentation and communication of results
Aid stats analysis

60
Q

What do dot plots show?

A

Skewness and large or small values

61
Q

Why are box plots useful?

A

Resistant to extreme values and show distribution

62
Q

What can scatter plots identify?

A

Normality and linearity

63
Q

What are the graph integrity principles?

A

Numbers depicted on the graph should be proportional to the numbers reported by the data

Clear and complete labelling

Show data variations not design variations

Number of variable dimensions must not exceed the number of dimensions in the data

Graphs must not quote data out of context

64
Q

When do you use a t statistic?

A

When you don’t know the standard deviation and can assume normal distribution

65
Q

What are the steps of the hypothesis test?

A

Formulate hypothesis
Calculate test statistic
Consider decision rule
State decision rule
Conclude and report

66
Q

What is a decision rule?

A

T statistic or P value

Something that tells us when to reject the null hypothesis

67
Q

What is the difference between a database and a spreadsheet?

A

Database: meaningfully structured and stored, always electronic,

Spreadsheet: interactive computer application, collection of a variable of interest aiming at answering a scientific question, table of variables with all observations of a variable of the same type

68
Q

What are the sources of bias?

A

Non random sampling
Conditioning of biological material
Interference by the process of investigation
Investigator bias

69
Q

When do you have to use nonparametric tests?

A

When the sample size is small
you dont know the distribution
Cant assume data is normally distributed

70
Q

Why do we use parametric tests where possible?

A

More informative and powerful than non-parametric tests

71
Q

What does a sign test do?

A

Decides whether the data are equally likely to be on either side of a reference value

72
Q

What are the assumptions of a sign test?

A

Ordinal, continuous dataset
A set of independent measurements

73
Q

What is the Wilcoxon signed rank test?

A

Rank of an observation amongst a set of observations

74
Q

What does the Mann-Whitney-Wilcoxon test do?

A

Decide whether population distributions are identical without assuming normality

75
Q

What does the random test measure?

A

Whether the observed data are different from a random distribution generated by reordering the observed data

76
Q

What are the assumptions of the random test?

A

Observational independancy

77
Q

What are the criticisms of the bonferroni correction?

A

General null hypotheses are rarely of interest
Counterintuitive as interpretation depends on the number of tests

78
Q

What is the purpose of ANOVA?

A

Comparing means across groups or factors

79
Q

What does correlation measure?

A

Degree of a relationship between two variables

80
Q

What is the parametric correlation test?

A

Pearson correlation coefficient

81
Q

What are the assumptions of the Pearson correlation coefficient?

A

Variables must be normally distributed
Relationship between them is assumed to be linear

82
Q

What are the non-parametric correlation measures?

A

Spearman’s rank correlation coefficient

Kendalls rank correlation tau

83
Q

Why would you use Kendall’s rank over spearman’s?

A

Smaller values
Less sensitive to potential errors
P-values are more accurate with smaller sample sizes
Better statistical properties
Interpretation is very direct

84
Q

What does simple linear regression investigate?

A

A linear association between an outcome and an independent variable

85
Q

What are the types of regression diagnosis plots?

A

Residuals vs fitted
Normal q-q
Scale-location
Residuals vs leverage

86
Q

What is cooks distance used to find?

A

Influential outliers

Experimental Design And Data Analysis (1 decks)

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