Презентация «Statistical data processing»

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Презентация «Statistical data processing»

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Статистическая обработка данных Prepared by Artur Galimov M. D.
Статистическая обработка данных Prepared by Artur Galimov M. D.
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Methods Section From JAMA (impact factor - 47. 661): In the Methods section, describe statistical me
Methods Section From JAMA (impact factor - 47. 661): In the Methods section, describe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to …
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Study Designs in Medical Research
Study Designs in Medical Research
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Distinguishing Between Study Designs
Distinguishing Between Study Designs
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Common types of experiments
Common types of experiments
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Experiment Introduce a treatment to observe its effects Might not involve randomization Might not ev
Experiment Introduce a treatment to observe its effects Might not involve randomization Might not even have a control group
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Randomized Experiment The gold standard for demonstrating causality Units (people, animals, groups,
Randomized Experiment The gold standard for demonstrating causality Units (people, animals, groups, etc. ) are randomly assigned to receive either treatment or control. If the sample is large enough, …
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Quasi-experiment There is a control group, but no random assignment to treatment vs. control Usually
Quasi-experiment There is a control group, but no random assignment to treatment vs. control Usually happens because it’s impossible or unethical to do random assignment Assignment to conditions …
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Natural experiment (Not exactly an experiment because the experimenter didn’t manipulate the cause,
Natural experiment (Not exactly an experiment because the experimenter didn’t manipulate the cause, but the cause occurred) Compare a group that experienced a cause with a group that didn’t (Or …
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Correlational study Nonexperimental because nothing is manipulated Measure some variables and see if
Correlational study Nonexperimental because nothing is manipulated Measure some variables and see if there’s a mathematical relationship between them Results can be consistent with causality, but …
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Even randomized experiments aren’t perfect Experimental conditions are usually artificial They’re co
Even randomized experiments aren’t perfect Experimental conditions are usually artificial They’re conducted in one particular time and place – might not generalize to other times or places But we …
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Populations
Populations
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«Statistical data processing», слайд 13
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Types of Data (Variables) Categorical
Types of Data (Variables) Categorical
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Types of Data (Variables) Categorical
Types of Data (Variables) Categorical
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Histograms Know how to interpret a histogram, i. e. , normal, skewed left (left tail), skewed right
Histograms Know how to interpret a histogram, i. e. , normal, skewed left (left tail), skewed right (right tail), and most importantly, infer from it the appropriate descriptive statistics and …
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Measures of Central Tendency Mean: what’s commonly called “average” Median (m): middle-most observat
Measures of Central Tendency Mean: what’s commonly called “average” Median (m): middle-most observation of ordered data n odd: m = the (n + 1)/2-th largest observation n even: m = average of the …
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Measures of Variability (Dispersion) Range: difference between largest and smallest observations (or
Measures of Variability (Dispersion) Range: difference between largest and smallest observations (or actual values) Interquartile range (IQR): the difference between the 25th and 75th percentiles (or …
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«Statistical data processing», слайд 19
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«Statistical data processing», слайд 20
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«Statistical data processing», слайд 21
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SPSS Output
SPSS Output
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SPSS Output
SPSS Output
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«Statistical data processing», слайд 24
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«Statistical data processing», слайд 25
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«Statistical data processing», слайд 26
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What is correlation? Correlation captures the extent to which two variables have a linear relationsh
What is correlation? Correlation captures the extent to which two variables have a linear relationship. Correlation coefficients are descriptive statistics that describe the degree or strength of the …
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SPSS output
SPSS output
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«Statistical data processing», слайд 29
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Simple linear regression Purpose: to model the change in one variable (Y, the “dependent variable”)
Simple linear regression Purpose: to model the change in one variable (Y, the “dependent variable”) as the other variable (X, the “independent variable”) changes. Assumptions Independence: For any …
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Procedure for linear regression Make a scatterplot of Y vs. X to determine if data are linear and ho
Procedure for linear regression Make a scatterplot of Y vs. X to determine if data are linear and homoscedastic. If the scatterplot looks reasonable, then assume the simple linear regression model: …
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«Statistical data processing», слайд 32
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Multilevel Structured Data Multilevel data frequently encountered in social sciences research refer
Multilevel Structured Data Multilevel data frequently encountered in social sciences research refer to data which contain multilevel (hierarchical or nested) structure. Multilevel structure indicates …
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Example of Multilevel Data in Prevention Research In school-based substance use prevention research,
Example of Multilevel Data in Prevention Research In school-based substance use prevention research, schools are usually the units of assignment to experimental conditions (program or control). Data …
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Missing Data Data are missing on some variables for some observations. Three goals of missing data h
Missing Data Data are missing on some variables for some observations. Three goals of missing data handling Minimize bias Maximize use of available information Get good estimates of uncertainty (get …
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Missing Data: Methods to Deal with Missing Listwise Deletion: Delete cases with any missing on the v
Missing Data: Methods to Deal with Missing Listwise Deletion: Delete cases with any missing on the variables being analyzed. Missing replacement by imputation: Mean replacement: using variable mean …
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Methods Section Outline Participants and Procedures Measures Data Analysis
Methods Section Outline Participants and Procedures Measures Data Analysis
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Participants and Procedures
Participants and Procedures
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Data Analysis
Data Analysis
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Q/A Session
Q/A Session
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Arthur Galimov e-mail: galimov@usc. edu IG: ar_galimov
Arthur Galimov e-mail: galimov@usc. edu IG: ar_galimov


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