Probablility

Question 1

probability

Answer 1

provides mathematical framework for thinking about the uncertainty of future events

Question 2

compound events

Answer 2

Independence do you like conditional probability knew line random variable

Question 3

Probability density function

Answer 3

Cumulative density function knew line quintiles and percentiles

Question 4

Classical Probability distributions

Answer 4

binomial (discrete), negative binomial (discrete),Poisson (discrete), Uniform (continuous), normal/gaussian (continuous), exponential (continuous),power law (continuous)

Question 5

binomial (discrete)

Answer 5

tbc

Question 6

negative binomial (discrete)

Answer 6

tbc

Question 7

Poisson (discrete)

Answer 7

tbc

Question 8

Uniform (continuous)

Answer 8

tbc

Question 9

normal/gaussian (continuous)

Answer 9

tbc

Question 10

exponential (continuous)

Answer 10

tbc

Question 11

power law (continuous)

Answer 11

tbc

Question 12

statistics

Answer 12

provide a mathematical framework to collect analyse interpret and present data

Question 13

descriptive statistics

Answer 13

used to describe and summarise the data

Question 14

inference statistics

Answer 14

used to make predictions by taking samples of data from a population of making generalisations about that population

Question 15

Central limit theorem CLT

Answer 15

if we repeatedly take independent random samples of the size and from population under when Anna is large the distribution of the samples means it will approach a normal distribution. This allows us to make inferences from a sample about a population without needing the characteristics of the whole population. Confidence intervals hypothesis testing and P value analysis are all based on the CLT.

Question 16

law of large numbers LLN

Answer 16

if an experiment is repeated independently a large number of times the average should be close to the expected value.

Question 17

sampling

Answer 17

the process of collection and selection of data the goal is to make a statistical inference about a population from a small set of observations

Question 18

random sampling

Answer 18

Every member in your population has equal chance of being sampled

Question 19

stratified sampling

Answer 19

the population is split into groups and then members are randomly sampled from each group

Question 20

cluster sampling

Answer 20

the population is first split into groups or clusters and then some clusters of randomly selected to be in your sample

Question 21

Systematic sampling

Answer 21

every member in your population is ordered into a list you then choose a random point and then select every Kth member

Question 22

sampling errors

Answer 22

errors introduced to your data via sampling excuse in the data in some way therefore not reflective of the real world distribution. this can be combated by increasing the sample size and ensuring the sample accurately represents the entire population.

Question 23

hypothesis testing

Answer 23

a tool used to determine the probability that a given hypothesis is true

Question 24

hypothesis testing process

Answer 24

formulates the null hypothesis
choose a test statistic
calculate the P value
compare the P value to a significant value alpha

Question 25

Z-test

Answer 25

test to determine if the sample mean is the same as the population mean

Question 26

T-test (one sample )

Answer 26

test to determine if the mean of a normally distributed population is different from a hypothesise value

Question 27

T-test (two-sample )

Answer 27

tested determine if the means of two populations are significantly different from one another

Question 28

chi-square test (goodness of fit)

Answer 28

test to determine how the observed data fits some given probability distribution

Question 29

chi squared test (for independence )

Answer 29

test to determine if two categorical variables are related

Question 30

Correlation

Answer 30

describe the relationship between two variables in a context such that one variable affects another

Question 31

Pearson coefficient

Answer 31

the degree of the relationship between linear linearly related variables

Question 32

Spearman rank coefficient

Answer 32

computed on ranks and depicts monotonic relationships also known as the person correlation coefficient between rank variables

Question 33

linear algebra

Answer 33

provides a mathematical framework to operate on matrices