Univariate analysis:Medical statistics Part IV

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Information about Univariate analysis:Medical statistics Part IV
Health & Medicine

Published on March 17, 2014

Author: ramachandrabarik

Source: slideshare.net

Description

Univariate analysis

Univariate Analysis Medical statistics Part IV

Univariate analysis :Watch one variable at a time across sample

Data analysis Descriptive Inferential

1 or 2 or multi Univariate Bivariate Multivariate

Variables Qualitative= Categorical Quantitative = Numerical  Values are mutually exclusive  Different values represent different categories  Discrete  Ordered Category Variables  multiple category variables that are formed by “sectioning” a quantitative variable age categories of 0-10, 11-20, 21-30, 31-40  most grading systems are like this 90- 100 A, etc.  Values are mutually exclusive  Different values represent different amounts  Discrete or Continuous  discrete  No “partial counts” just “whole numbers” e.g., how many siblings do you have  continuous  fractions, decimals, parts possible  must decide on level of precision e.g., how tall are you = 6’ 5’11” 5’10.65”

Define one Univariate analysis  Descriptive  Simplest  First procedure one does when examining data  Quantitative  One variable watched at a time  The tools involved depend with the kind of variable  Variable may be a continuous or discrete

3 major tools used in Univariate analysis  Distribution [of frequency]  Central tendency[mean,median and mode]  Dispersion

Distribution(of frequency)  individual value  range  Charts

finding frequency is key measurement Description of frequency 1) counts 2) percentages 3) percentile values 4) Central tendency 5) Dispersion[standard deviation 6) distribution: Skew=“direction of the distribution tail” 7) kurtosis 8) Standard Error of the Mean (SEM) 9) charts : bar charts and histograms 10) Box plot

Central Tendency Mean :summing all the scores and dividing by the number of students Median: the score found at the exact middle of the set of values Mode :the most frequently occurring value in the set of scores

Dispersion :Spread around the central tendency Range Standard deviation Range=highest value minus the lowest value The Standard Deviation shows the relation that set of scores has to the mean of the sample More accurate

Standard deviation

The SPSS tools • following procedures: "Frequencies", "Descriptives" and "Explore" all located under the "Analyse" menu.

Standard Error of the Mean (SEM) • Standard Error of the Mean (SEM) standard deviation • SEM = ---------------- n  The SEM tells the average sampling mean sampling error -- by how much is our estimate of the population mean wrong, on the average  the smaller the population std, the more accurate will tend to be our population mean estimate from the sample  larger samples tend to give more accurate population estimates

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