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Chem Bio > Chemometrics quizzes > Flashcards

Chemometrics quizzes Flashcards

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1
Q

Difference between nominal and ordinal variable

A

Nominal is categorical and cant be ranked ordinal is also categorical and a number but can be ranked

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2
Q

Whats the difference between discrete and continuous variables

A

discrete variables are specific numebrs like integers and continuous can exist between real numbers

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3
Q

Inferential vs descriptive stats?

A

Inferential stats make an inference based off the data (analyzes it - draws conclusions) - descriptive just describes it (eg mean, median mode)

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4
Q

What does the null hypo mean and what is the alternative hypo

A

null is that there there is no sig difference between the groups or means -alt is that there is

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5
Q

What is a two tailed t test

A

a t test that looks for differnce both greater and less than (either direction

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6
Q

Why do we use post hoc tests with ANOVA

A

to see specifically the relationship between groups - which groups specifically have a statistically significant relation

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7
Q

With bonferroni adjusted p value - what do you use to adjust the p value

A

of tests/comparisons

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8
Q

In two way anova how many factors do you have

A

2

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9
Q

When checking for normal dist - is p < or> than 0.05 for normal

A

p>0.05

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10
Q

know how to name a box and whisker plot

A

we have the whisker and the interwuartile range
we also have min, max, lower quartile, upper quartile and median

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11
Q

What is a correlation matrix

A

its a matrix showing correlation between all combinations of variables

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12
Q

what is one way repeated measures ANOVA

A

When the same subjects are measured more than once (eg same subject but different time points

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13
Q

With correlatoins what does the magnitude of the correlation describe

A

Strenght of relation

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14
Q

Name 2 ways 1st order poynomial regressions differ from 2nd order

A

Different DOF, quadratic has C term, quadratic non linear

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15
Q

What is a residual and when they are all summed what do they equal

A

Distance of each point from best fitted line - all summed up they equal 0

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16
Q

if slope not statiscally significant (p > 0.05) what does this mean - if the overal model has ap value not sig what does this mean

A

If slope not sig that means no relationship between x and y (b=0)
if model not significant - doesnt effectively predict

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17
Q

What is the difference between two way anova and MANOVA

A

more than one variable

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18
Q

What is the equation for linear regression

A

y = mx + b

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19
Q

Things to check on influence plot

A

Outliers, Leverage poitsn and influence

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20
Q

4 assumptions for linear regression

A

error in x negligible, dependant vriable needs to be normally dist, variance in error across y should be constant and x and y are continuous and independant

21
Q

What is the parametric Mann whitney U

A

2 sample independant t test

22
Q

What is the non parametric equivalent for the one way anova test

A

Kruskal Wallis

23
Q

Difference between supervised and unsupervised learning

A

Supervised - we know outcome and this informs the model - unsupervised only give data no existing info or input

24
Q

What are the two things used to calculate PCA scores

A

Magnitude (concentration) and influence (variance)

25
Q

difference between PCA scores plot and PCA loading plot

A

PCA scores plot shows pC scores for each group on 2d plane
Loadings plot - shows individual feature within whole experiment and which incluence the PC’s the most

26
Q

How do robust methods work

A

they use the median or other forms of means that arent as effected by outliers

27
Q

what is MAD

A

median absolute deviation - a way to describe variation in data set with outliers - it is the median of the absolute value distances form the median

28
Q

Before you do PCA - what do you do

A

scale /transofrm the data - normalize

29
Q

what is PARSIMONY

A

Getting to the core explanation of a system with the least amount of info

30
Q

What test do you run for sig relationship between categorical variables

A

chi squared

31
Q

Whats difference between logistic and poisoson regression

A

Poisson is counts - dependant variable is counts, logistic - dependant variable is just categorical

32
Q

4 ingredients in machine learning

A

A model
a loss function
a way to improv the model (optimization)
and data

33
Q

what does PLS-DA stand for

A

Partial Leas square discriminant analysis

34
Q

what is aglglormerative clustering

A

each observation as own clulster - and join them together until one cluster

35
Q

What does height in dendogram indicate

A

order in which clusters joined ( can indicate distance)

36
Q

What is K in regards to clustering

A

K is # of clusters desired

37
Q

What is overfitting in Machine earning

A

model only fits your data - not generlaizable

38
Q

Within a confusion matrix what is sensitivity and specificity

A

sensitivity is TP /(TP+FN)
specificty TN/(FP + TN)

39
Q

What are ensemble methods

A

use multipe learning algorithimgs to obtain better predictive performance

40
Q

4 quantities of power analysis

A

power, sample size, alpha, effect size

41
Q

2 principle for appropriate sampling

A

randomization and representation

42
Q

What does R^2 tell you in cal curve-

A

how close do measure smatch linear model

43
Q

Matrix effects - what are they

A

behaviour of cal curve changed due to matrix components

44
Q

what is weighted regression

A

Cal curve set to go through points that have the lowest variation

45
Q

What is the main difference between QA and QC

A

QA before data collected - QC are actions performed at all stages of sample analysis

46
Q

What does a Shewhart chart show

A

Sequential plot of observations obtained from a qc material analyzed in successive runs together with warning and action limits to ID when things went wrong

47
Q

What is the main reason to use system suitability

A

ensure instrument is working properly before you start study

48
Q

Blanks

A

Field and Trip Blank
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Chem Bio (17 decks)

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