lecture 3

Question 1

when are statistics needed in clinical experience

Answer 1

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

Question 2

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

Answer 2

they should have fairly similar means

Question 3

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

Answer 3

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

Question 4

what does hypothesis testing involve

(3 steps)

Answer 4

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

Question 5

what is the assumption made in statistics

Answer 5

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

Question 6

what is the null hypothesis

Answer 6

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

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

Question 7

what is the alternative hypothesis

Answer 7

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

Question 8

relate the clinical trial analgoy to statistics

Answer 8

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.”

Question 9

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

Answer 9

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

Question 10

define probability

Answer 10

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.
  *

Question 11

what is the conventional cut off point

Answer 11

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

Question 12

what is p-value/statistical significance of a result

Answer 12

an estimate of the degree to which a result is true

probability of getting an e_vent at least as extreme_ as your result if the null hypothesis is true

Question 13

What is power

Answer 13

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

Question 14

what is a type one

Answer 14

Rejecting the null hypothesis, when it is true

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

Question 15

what is a type 2 error

Answer 15

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

Question 16

when do type one errors often occur

Answer 16

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

Question 17

what does the choice of statistical test depend on

Answer 17

• 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)

Question 18

define multiple comparison

Answer 18

two or more data sets, which should be analyzed

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

Question 19

what is a degree of freedom

Answer 19

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

Question 20

what are one and two tailed tests

Answer 20

• one-tailed test of significance used for directional
  hypothesis
• two-tailed tests in all other situations

Question 21

what is a sample size

Answer 21

number of cases, on which data have been obtained

Question 22

which characteristics of distribution are senstitive to SAMPLE SIZE

Answer 22

mean

SD

skewness

kurtosis

Question 23

define the student t-test

Answer 23

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

Question 24

what is a 1- sample t-test

Answer 24

Comparison of sample mean with a population mean

Question 25

what is a 2 sample t test

Answer 25

comparison of means from two unrelated groups

Question 26

types of t tests

Answer 26

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

Question 27

what is ANOVA

Answer 27

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
conditions

• 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)

Question 28

difference between parameteric and non parametric tests

Answer 28

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

• variable is normally distro
• more reliable test

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