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Univariate analysis:Medical statistics Part IV
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Univariate analysis:Medical statistics Part IV


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Univariate analysis

Univariate analysis

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  • 1. Univariate Analysis Medical statistics Part IV
  • 2. Univariate analysis :Watch one variable at a time across sample
  • 3. Data analysis Descriptive Inferential
  • 4. 1 or 2 or multi Univariate Bivariate Multivariate
  • 5. 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”
  • 6. 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
  • 7. 3 major tools used in Univariate analysis  Distribution [of frequency]  Central tendency[mean,median and mode]  Dispersion
  • 8. Distribution(of frequency)  individual value  range  Charts
  • 9. 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
  • 10. 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
  • 11. 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
  • 12. Standard deviation
  • 13. The SPSS tools • following procedures: "Frequencies", "Descriptives" and "Explore" all located under the "Analyse" menu.
  • 14. 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
  • 15. Thanks