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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

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