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Statistics Idiots Guide! Dr. Hamda Qotba, B.Med.Sc, M.D, ABCM 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 Dr.H.Qotba 2 Variables Quantitative •Discrete •Continuous Qualitative •Ordinal •Categorical Dr.H.Qotba 3 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 Dr.H.Qotba 4 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? Dr.H.Qotba 5 Requirements • The observations are independent • Drawn from normally distributed population • Sample size < 30 if it’s >30 use normal curve z test (binomial test) Dr.H.Qotba 6 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 sameDr.H.Qotba set of patients 7 chi² test • Used to test strength of association between qualitative variables • Used for categorical data Dr.H.Qotba 8 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 >5 (When 1 of the cells have <5 in observed yats correction) or if (When 1 of the cells have <5 in expected fischer exact) • The group compared must be approximately the same Dr.H.Qotba 9 Correlation and Regression • Methods to study magnitude of the association and the functional relationship between two or more variables Dr.H.Qotba 10 Correlation • Denote strength of relationship between variables Dr.H.Qotba 11 Regression • Method that’s 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 Dr.H.Qotba 12 Measures • If parametric • Pearson correlation coeff. »Continuous variables »Linear relationship • If nonparametric • Spearman rank »Both variables are continuous • Kendall’s tau »Two ordinal or one ordinal one continuous Dr.H.Qotba 13 ANOVA • is used to uncover the main and interaction effects of categorical independent variables (called "factors") on an interval dependent variable Dr.H.Qotba 14 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. Dr.H.Qotba 15 • 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 Dr.H.Qotba 16 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 Dr.H.Qotba • matched 17 Body of research question Association of 2 variable(dep, indep) Types of variable Dependent independent Test categorical categorical chi-square categorical Quantitative Log. regression Quantitative categorical 2 out come T test 3+out come ANOVA Quantitative Quantitative Spearman Correlation linear Regression Dr.H.Qotba 18 Comparing (difference) variables Variable Number of independent variable 2 groups paired data >2groups Quantitative T test Ordinal MannWhitney Paired T test Categorical chi-square* ANOVA Wilcoxon Kruskal wallis McNemar chi-square * When 1 of the cells have <5 in expected fischer exact When 1 of the cells have <5 in observed yats correction Dr.H.Qotba 19 Looking for Risk Factor Types of variables Test Dependent several indepen. categorical categorical Multiple log. Regression quantitative categorical ANOVA quantitative quantitative Linear, log regression Dr.H.Qotba 20