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when are statistics needed in clinical experience

to quantify differences that are too small to recognize through clinical experience alone 


what is the result when comparing the mean between 2 samples from the same population

they should have fairly similar means


what does it mean if the means from two samples are statistically different

likely to be drawn from 2 different populations, ie
they really are different


what does hypothesis testing involve

(3 steps)

Making an initial assumption;

Collecting evidence (data);

Based on available evidence (data), decide whether or not to reject the initial assumption.


EVERY hypothesis test includes these


what is the assumption made in statistics

always assume the null hypothesis is true/ null hypothesis is the initial hypothesis




what is the null hypothesis

H0. : the absence of a difference or an effect.

  • no effect
  • rejected if significance tests shows data doesn't match H0


what is the alternative hypothesis

H', H1, or HA.: the complement(equal opp) of the null hypothesis.


relate the clinical trial analgoy to statistics


In statistics, the data are the evidence.

if suff evidence exists beyond reasonable doubt the jury rejects H0 and deems the
defendant guilty.

If there is insufficient evidence, then the jury does not
reject H0.

making the decision reduces to
determining "likely" or "unlikely."


what are the two ways to determine whether the evidence is likely or unlikley regarding the initial assumtption

  • "critical value approach"- old textbooks
  • “p-value approach"-research, journal articles, and
    statistical software


define probability 

A measure of the likelihood that a particular event
will happen.


  • shown as a value between 0 and 1.
  • the acc measurement is the rate in a group not just an event 
  • larger the p the more likley the event. 


what is the conventional cut off point 

if p is greater than 0.05 then the null hypothesis is greater as the result should only occur less than 5 times out of every 100 by chance

0.05 is completely arbitrary



what is  p-value/statistical significance  of a result

an estimate of the degree to which a result is true

probability of getting an event at least as extreme as your result if the null hypothesis is true


What is power

probability of rejecting the null hypothesis.


  • probability that youreject the null hypothesis when you should
    (and thus avoid a Type II error).
  • varies according to underlying truth e.g. the actual difference betw/ pop means 
  • power increases with increased diff betw/ pop means 


what is a type one

Rejecting the null hypothesis, when it is true

aka: α (alpha) which is also the power of the test when H0 is true




what is a type 2 error 

occurs when we fail to reject the H0 when it is false.

probabilty of type 2 error is known as β (beta).

power is 1-β when H0 is false 


when do type one errors often occur 

whe nmany tests are done on the same data 

if 100 tests are done 5 tests will inevitably fall into the rare 5 in a 100 so its dumb to say the one of those 5 is statistically significant if H0 is true 


what does the choice of statistical test depend on 

  • Level of measurement for the dependent and independent variables
  • Number of groups or dependent measures
  • Number of units of observation
  • Type of distribution
  • The population parameter of interest (mean, variance, differences between means and/or variances)


define multiple comparison 

two or more data sets, which should be analyzed

  • repeated measurements made on the same individuals
  • entirely independent samples


what is a degree of freedom 

number of scores, items, or other units in the data set, which are free to vary


what are one and two tailed tests 

  • one-tailed test of significance used for directional

  • two-tailed tests in all other situations


what is a sample size

number of cases, on which data have been obtained


which characteristics of distribution are senstitive to SAMPLE SIZE






define the student t-test

Difference between the means divided by the pooled
standard error of the mean


what is a 1- sample t-test

Comparison of sample mean with a population mean



what is a 2 sample t test

comparison of means from two unrelated groups 


types of t tests 

independant sample t test

  • independant samples & interval measures (parametric)

paired sample t-test

  • related samples & interval measures (parametric

man-whitney u-test

  • independant samples & ordinal/ non parametric 

wilcoxon test

  • related samples & ordinal/ non parametric


what is ANOVA

ANalysis Of VAriance

compares the differences in means between
groups but it uses the variance of data to “decide” if
means are different


F STATISTIC= Magnitude of the difference between the different

  • the p-value associated with F is the probability that
    differences between groups could occur by chance if
    null-hypothesis is correct
  • post-hoc tests needed as ANOVA can tell you if
    there is an effect but not where)


difference between parameteric and non parametric tests 

Parametric test: estimate at least one population parameter from sample statistics

  • variable is normally distro
  • more reliable test 

Non-parametric testdistribution free, no assumption
about the distribution of the variable in the population