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Presentation to the Research Methodology Winter Camp at AlMaarefa University on January 13, 2022 at 1.30pm. By Prof. Omar Hasan Kasule Sr. MB ChB (MUK). MPH (Harvard), DrPH (Harvard) Professor of Epidemiology and Bioethics, King Fahad Medical City
VARIABLES
OF THE CLASSROOM DATA:
- AGE (in
years),
- GENDER (male,
female)
- REGION of
birth (East, North, West, Central, West),
- ORDER in the family (first, second, third, higher),
- DEGREE
expected (bachelor, masters, doctorate, post-doctorate),
- WEIGHT (in
kilograms),
- HEIGHT (in
centimeters),
- wearing
GLASSES (yes, no),
- COLOR preference
(blue, red, green, yellow).
VARIABLES
OF THE CLASSROOM DATA, Con’t.:
- number of
BROTHERS,
- number of
SISTERS,
- type of
primary SCHOOL (private, public),
- type of
UNIVERSITY (public, private), J
- JUMPING rank
(1st. 2nd, 3r etc.),
- RUNNING rank
(1st. 2nd, 3r etc.).
SPSS
VARIABLE VIEW OF CLASSROOM DATA:
SPSS
DATA VIEW OF CLASSROOM DATA:
EXERCISE
5: LINEAR CORRELATION:
- Draw a
scatter plot of WEIGHT against HEIGHT:
▻
Import the data into SPSS v22.0 and
make sure to click on DATA VIEW
▻
In the menu, click on GRAPHS then
CHART BUILDER and choose the first SCATTER/DOT option from the Gallery and drag
it to the viewer.
▻
In the variables, drag HEIGHT into
the “X-Axis” and WEIGHT into the “Y-Axis” then OK. It does not matter if this
is done in the opposite way.
- Compute the
Pearson linear correlation coefficient for WEIGHT and HEIGHT:
▻
Import the data into SPSS v22.0 and
make sure to click on DATA VIEW
▻
In the menu, click on ANALYZE then
CORRELATE then BIVARIATE and tick the box ‘PEARSON.’
▻
In the variables, insert the WEIGHT
and HEIGHT into the viewer then OK.
EXERCISE
6: SIMPLE LINEAR REGRESSION ANALYSIS:
- Import the
data into SPSS v22.0 and make sure to click on DATA VIEW.
▻
In the menu, click on ANALYZE then
REGRESSION then choose the ‘LINEAR.’
▻
In the ‘DEPENDENT(S)’, insert the
‘weight’ and in the ‘INDEPENDENT’ variable insert the ‘height’ then OK.
▻
Test the significance of the linear
regression coefficient
- Construct a
simple linear regression equation and use it to predict the weight of
persons with the following heights: 100cm, 120 cm. 135cm and 150cm.
EXERCISE
7: SIMPLE LOGISTIC REGRESSION:
- Import the
data into SPSS v22.0 and make sure to click on DATA VIEW
▻
In the menu, click on ANALYZE,
click REGRESSION, ‘BINARY LOGISTIC.’ drag GLASS to dependent and GENDER to
covariate, then click OK