Univariate, Bivariate, and Multivariate Analyses

1. Univariate, Bivariate and
Multivariate Analyses
Yusuf Babatunde Adeneye
President, GSB Ph.D. Club

2. Univariate Analysis (One Variable)
• Continuous Variable
*Central Tendency (Mean, Median and Mode, t-test)
*Measure of Variation (Variance, Standard deviation, Range, Percentile,
Interquartile Range)
*Measure of Distribution (Normality test – Skewness and Kurtosis)
*Plots (Histogram, Box Plot, Stem Plot, Dot Plot, Line Chart, Time Series
Plot)
• Categorical Variable
*Frequency (Counts, Frequencies, Percentages, Odds, Z-test)
*Plots (Bar Graph, Pie Graph and Pareto Graph)

3. Continuous vs
Categorical Variables
• Most questions on variables
asked in Ordinal Scale,
Interval Scale, and Ratio
Scale qualify such variables
to be Continuous variable
• Most Categorical or
Demographic variable (i.e.
asked in a categorical way)
are Categorical Variable

4. Bivariate Analysis (Two Variable; Y & X)
• Categorical (Y as dependent variable) and Categorical (X as Independent Variable)
• Y-2 Categories [(i.e. Income is High Income (Cat 1) and Low Income (Cat 2)] and X-2
categories [(i.e. Work Experience is High Experience (Cat 1) and Low Experience (Cat
2)]
• Pearson’s Chi square
• Fisher’s Exact
• Y-3 Categories [(i.e. Income is High Income (Cat 1), Middle Income (Cat 2), and Low
Income (Cat 3)] and X-2 categories [(i.e. Work Experience is High Experience (Cat 1)
and Low Experience (Cat 2)]
• Pearson’s Chi square
• Mantel-Haenszel

5. X = Independent Variable
Y = Dependent Variable
• Categorical Variable with 2
Classification (i.e. Gender-
Male and Female; Season-
Rainy and Dry)
• Categorical Variable with
more than 2 classifications
(i.e. Experience – 5-10years,
11-15 years, 16-20 years, 20
years & above; Income – N1
–N100,000; N100,001-
N200,000; N200,001-
N500,000; N500,001 &
above

6. Multivariate Analysis (More than 2 Variables)
• Continuous Y
*Multiple Regression, Analysis of Variance, Analysis of Covariance
• Dichotomous Y
*Logistic Regression, Discriminant Analysis
• Nominal Y > 2 Categories
*Multinominal Logistic
• Ordinal Y
*Ordinal Logistic
• Y is “Time” Survival Analysis
*Life Table
• Multivariate Y
• *Repeated Measures, MANOVA, Factor Analysis

7. • Continuous Y = Ordinal,
Interval and Ratio Scales
• Dichotomous Y = Yes and No
(Probability that a firm will
liquidate = 1; Probability
that it will not liquidate = 2)
• Nominal Y = Gender (Male,
Female) as dependent var.
• Ordinal Y = Preference
Variable (i.e. Toyota, BMW,
Honda, Nissan, Ford)
• Time Survival Analysis Y =
Underweight (a risk factor
for mortality in dialysis
patients)
• Multivariate Y = Variable
with two or more measures
belonging to a group

8. •Thank you for coming and listening