Univariate analysis

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