Univariate AnalysisMedical statistics Part IV

Univariate analysis :Watch one variable at a time across sample

Data analysis

Descriptive Inferential

1 or 2 or multiUnivariate Bivariate Multivariate

VariablesQualitative= 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) counts2) percentages3) percentile values4) Central tendency5) Dispersion[standard deviation6) distribution: Skew=“direction of the distribution tail”7) kurtosis8) Standard Error of the Mean (SEM)9) charts : bar charts and histograms10) Box plot

Central TendencyMean :summing all the scores and dividing by the number of studentsMedian: 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 deviationRange=highest value minus the lowest value

The Standard Deviation shows the relation that set of scores has to the mean of the sampleMore 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

Thanks