Chemometrics quizzes Flashcards

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
difference between PCA scores plot and PCA loading plot
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
How do robust methods work
they use the median or other forms of means that arent as effected by outliers
27
what is MAD
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
Before you do PCA - what do you do
scale /transofrm the data - normalize
29
what is PARSIMONY
Getting to the core explanation of a system with the least amount of info
30
What test do you run for sig relationship between categorical variables
chi squared
31
Whats difference between logistic and poisoson regression
Poisson is counts - dependant variable is counts, logistic - dependant variable is just categorical
32
4 ingredients in machine learning
A model a loss function a way to improv the model (optimization) and data
33
what does PLS-DA stand for
Partial Leas square discriminant analysis
34
what is aglglormerative clustering
each observation as own clulster - and join them together until one cluster
35
What does height in dendogram indicate
order in which clusters joined ( can indicate distance)
36
What is K in regards to clustering
K is # of clusters desired
37
What is overfitting in Machine earning
model only fits your data - not generlaizable
38
Within a confusion matrix what is sensitivity and specificity
sensitivity is TP /(TP+FN) specificty TN/(FP + TN)
39
What are ensemble methods
use multipe learning algorithimgs to obtain better predictive performance
40
4 quantities of power analysis
power, sample size, alpha, effect size
41
2 principle for appropriate sampling
randomization and representation
42
What does R^2 tell you in cal curve-
how close do measure smatch linear model
43
Matrix effects - what are they
behaviour of cal curve changed due to matrix components
44
what is weighted regression
Cal curve set to go through points that have the lowest variation
45
What is the main difference between QA and QC
QA before data collected - QC are actions performed at all stages of sample analysis
46
What does a Shewhart chart show
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
What is the main reason to use system suitability
ensure instrument is working properly before you start study
48
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