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Statistics Idiots Guide

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Compare the means of a continuous variable into samples in order to determine ... Sample size 30 if it's 30 use normal curve z test (binomial test) Dr.H.Qotba. 7 ... – PowerPoint PPT presentation

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Title: Statistics Idiots Guide


1
Statistics Idiots Guide!
  • Dr. Hamda Qotba, B.Med.Sc, M.D, ABCM

2
Definition
Statistics is the science of collecting,
organizing, summarising, analysing, and making
inference from data
Descriptive stat. Includes collecting,
organizing, summarising, analysing, and
presenting data
Inferential stat. Includes Making inferences,
hypothesis testing Determining relationship,
and making prediction
3
Variables
  • Quantitative
  • Discrete
  • Continuous
  • Qualitative
  • Ordinal
  • Categorical

4
Parametric Vs.
non parametric tests
  • Parametric decision making method where the
    distribution of the sampling statistic is known
  • Non-Parametric decision making method which does
    not require knowledge of the distribution of the
    sampling statistic

5
t-Test
  • Compare the means of a continuous variable into
    samples in order to determine whether or not the
    difference between the 2 expected means exceed
    the difference that would be expected by chance

What is probability the mean will differ?
6
  • Requirements
  • The observations are independent
  • Drawn from normally distributed population
  • Sample size lt 30 if its gt30 use normal curve z
    test (binomial test)

7
Types of t-Test
  • One sample t test test if a sample mean for a
    variable differs significantly from the given
    population with a known mean
  • Unpaired or independent t test test if the
    population means estimated by independent 2
    samples differ significantly (group of male and
    group of female)
  • Paired t test test if the population means
    estimated by dependent samples differ
    significantly (mean of pre and post treatment
    for same set of patients

8
chi² test
  • Used to test strength of association between
    qualitative variables
  • Used for categorical data

9
Requirements
  • Data should be in form of frequency
  • Total number of observed must exceed 20
  • Expected frequency in one category or in any cell
    must be gt5 (When 1 of the cells have lt5 in
    observed yats correction) or if (When 1 of the
    cells have lt5 in expected fischer exact)
  • The group compared must be approximately the same

10
Correlation and Regression
  • Methods to study magnitude of the association and
    the functional relationship between two or more
    variables

11
Correlation
  • Denote strength of relationship between variables

12
Regression
  • Method thats indicate a mathematical
    relationship between a dependant and one or more
    independent variables
  • Simple linear regression and multiple regression
    are appropriate for continuous variables like(BP,
    Weight)
  • Logistic regression applicable for binary
    response like alive/dead

13
Measures
  • If parametric
  • Pearson correlation coeff.
  • Continuous variables
  • Linear relationship
  • If nonparametric
  • Spearman rank
  • Both variables are continuous
  • Kendalls tau
  • Two ordinal or one ordinal one continuous

14
ANOVA
  • is used to uncover the main and interaction
    effects of categorical independent variables
    (called "factors") on an interval dependent
    variable

15
Types of ANOVA
  • One-way ANOVA tests differences in a single
    interval dependent variable among two, three, or
    more groups formed by the categories of a single
    categorical independent variable.

16
  • Two-way ANOVA analyzes one interval dependent in
    terms of the categories (groups) formed by two
    independents, one of which may be conceived as a
    control variable
  • Multivariate or n-way ANOVA. To generalize, n-way
    ANOVA deals with n independents. It should be
    noted that as the number of independents
    increases, the number of potential interactions
    proliferates

17
How to select appropriate statistical test
  • Type of variables
  • Quantitative (blood pres.)
  • Qualitative (gender)
  • Type of research question
  • Association
  • Comparison
  • Risk factor
  • Data structure
  • Independent
  • Paired
  • matched

18
Body of research question Association of 2
variable(dep, indep)
19
Comparing (difference) variables
Number of independent variable 2
groups paired data gt2groups
Variable
Quantitative Ordinal Categorical
T test
Paired T test
ANOVA
Kruskal wallis
Mann-Whitney
Wilcoxon
chi-square
chi-square
McNemar
When 1 of the cells have lt5 in expected
fischer exact When 1 of the cells have lt5 in
observed yats correction
20
Looking for Risk Factor
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