statistics

Question 1

random error

Answer 1

lecture : can be conceptualised as sample variability

notes: can’t avoid it only way is to test the whole population which is impossible but you can minimise by increasing sample size

Question 2

bias (systemic error)

Answer 2

a difference between the observed value and true value due to all causes except sampling variability

Question 3

random sample

Answer 3

each member of the population has an equal chance of being chosen

Question 4

properties of a good sample

Answer 4

representative by structure
random
representative by number of cases

Question 5

how to select a sample

Answer 5

1. select a sampling method
2. define target population
3. determine sample size

Question 6

high power

Answer 6

large sample size
little scatter

Question 7

low power

Answer 7

small sample size
scatter is large

Question 8

definition of paired data

Answer 8

when 2 or more measurements are made on the same observational unit

Question 9

descriptive statistics

Answer 9

organising and summarising the data , tables, histograms, pie charts etc, tables (frequency distributions and relative frequency distributions)

measures of central tendency (mean , median, mode)

central tendency describes location and variation describes SPREAD (red book lec 2 )

measures of variability ( range , variance, standard deviation)

Question 10

inferential statisics

Answer 10

using the sample that you worked with to make a general conclusion

uses probability to determines how confident we can be that the conclusions we derive are correct

Question 11

what are measures ovariation in descriptive statisitcs

Answer 11

IQ range
variance
SD
range

Question 12

mean

Answer 12

it’s the balance point

can be heavily affected by outliers so outliers can make the mean a bad measure of central tendancy

Question 13

median

Answer 13

it’s the middle value when the variables are ranked in order
its the point that divided a distribution into 2 equal halves

its unaffected by outlierss? not sure

Question 14

if you have normal distrubted data ( symmetric) how does this affect the central tendancy

Answer 14

mean and median will be the same and mode

Question 15

what happens in skewed data to the central tendency

Answer 15

the mean lies further towards the skew than the median does (because rememeber mean is affected by outliers)

in skewed date the median and mean are more towards the skew than the mode

Question 16

mode

Answer 16

the most common data point. its possible to have more than 1. if all values are unique there is no mode

Question 17

SD

Answer 17

takes into account all individual deviations

the larger the SD , the greater the variation around the mean

google is a measure of the amount of variation or dispersion of a set of values.[1] A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range.

Question 18

when is SD zero

Answer 18

only when all values are the same

Question 19

is SD affected by outliers

Answer 19

YES

Question 20

can range be affected by outliers

Answer 20

yes

Question 21

IQ range

Answer 21

a measure of variability based on dividing data set into quartiles

ranke data set

Question 22

what is the best to use in symmeterical data

Answer 22

mean + SD

Question 23

what is best to use in skewed data

Answer 23

median and IQ (as not affected by outliers )

Question 24

3 sigma rule - NB

Answer 24

ONLY WORKS for normal distrubted date

68% of the data lie within 1 SD of mean above and below

95% data lie within 2 SD of the mean
above and below

99% data lie within 3 SD of the mean above and below

Question 25

central limit theoreom

Answer 25

1. create a population with a known distribution that is not normal 2. randomly select many samples of equal size from that population 3. tabulate the means of these samples and graph the frequency distrubtion t states that if your samples are large enough the distribution of the means will approximate a normal distribution, even if the population is not normal or 'gaussian'

Question 26

what can be the cause of outliers

Answer 26

inavalid data entry biological diversity random chance experimental error skewed distrubtion

Question 27

tests use to eliminate outliers from results

Answer 27

chauvenet's criterion grubbs test pierce criterion

Question 28

confidence interval for population mwans what do we assume

Answer 28

1. normally distributed 2. random representative sample 3. independent observations

Question 29

what does confidence interval depends on

Answer 29

1. sample mean (leads to your population mean ) 2. SD 3. sample size 4. degree of confidence

Question 30

what is the purpose of confidence interval for the mean mistakes

Answer 30

it gives a range of values around the mean where the true population is expected to be located

Question 31

heal

Question 32

regression analaysis models

Answer 32

statistical models - describe the relationship between 2 variables deterministic - hypothesize exact relationships probabilistic- hypothesize 2 components 1. deterministic 2. random error

Question 33

types of regression models

Answer 33

simple ( 1 explanatory variable) divide into simple and linear multiple ( 2+ explanatory variables divide into simple and linear

Question 34

regression modelling

Answer 34

1. determine the problem 2. specify model 3. collect data 4. do descriptive data analysis 5. estimate unknown parameter 6. evaluate model 7. use model for predict (remember model is 25 )

Question 35

defintion of regression analayss

Answer 35

R A is helpful in assessing specific forms of relationships between variables and the ultimate objective is to predict the or estimate the value of 1 variable corresponding to a given value of another variable .

Question 36

advantages of mean

Answer 36

1. very sensitive measure 2. can be combined with the means of other groups to give the overall mean 3. considers all the available information

Question 37

disadvantages of mean

Answer 37

1. affected by outliers 2. can only be used on interval or ratio data 3. can only be used if you have a normal distrubtion

Question 38

advantges of median

Answer 38

1. unaffected by outliers 2. can be used with non numerical date

Question 39

disadvatnages mediana

Answer 39

1. only takes into account order - value is ignored

Question 40

disadvantage of mode

Answer 40

is a terminal statistic - a given subgroup could make this measure unrepresentative

Question 41

advantges of mode

Answer 41

1. quick and easy 2. unaffected by outliers 3. can be used at any level of meaures

Question 41

advantges of mode

Answer 41

1. quick and easy 2. unaffected by outliers 3. can be used at any level of meaures

Question 42

assumptions about bivaradte date For each value of X there is a normally distributed subpopulation of Y values.

Answer 42

1. For each value of X there is a normally distributed subpopulation of Y values. 2.For each value of Y there is a normally distributed subpopulation of X values. 3. The joint distribution of X and Y is a normal distribution called the bivariate normal distribution. 4. The subpopulations of Y values all have the same variance. 5. The subpopulations of X values all have the same variance.