Univariate analysis examines one variable at a time across a sample. There are three main tools used in univariate analysis: distribution of frequency, measures of central tendency (mean, median, mode), and measures of dispersion. Distribution examines individual values, range, and charts. Central tendency measures the average or middle value. Dispersion measures the spread around the central tendency, such as the standard deviation and range. Common univariate analysis procedures include frequencies, descriptives, and explore in SPSS.

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”

7. 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

8. 3 major tools used in Univariate analysis
 Distribution [of frequency]
 Central tendency[mean,median and mode]
 Dispersion

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

10. 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

11. 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

12. 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

13. Standard deviation

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

15. 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

16. Thanks