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Quantitative Research

Doctor with Computer

A. Study design

A reading resource on different study designs for quantitative research along with the pros and cons of each design.



A short-video explaining study designs

B. Sample size calculations

Don’t know how to calculate sample size? Unsure which sampling technique you are going to use? The first video is a general explanation on sample size calculation, subsequent videos give a step-to-step guide to calculating sample size for your research


1. Principles and concepts





2. Online sample size calculators could be accessed here:


  • Epitools - Sample size calculations

These utilities can be used to calculate required sample sizes to estimate a population mean or proportion, to detect significant differences between two means or two proportions or to estimate a true herd-level prevalence.

Link here:


  • G-Power

G*Power 3 is a statistical power analysis program designed to analyze different types of power and compute size with graphics options. It covers many different statistical tests of the F, t, chi-square, and z test families as well as some exact tests.

Link here:


  • OpenEpi

OpenEpi provides statistics for counts and measurements in descriptive and analytic studies, stratified analysis with exact confidence limits, matched pair and person-time analysis, sample size and power calculations, random numbers, sensitivity, specificity and other evaluation statistics, R x C tables, chi-square for dose-response, and links to other useful sites. OpenEpi is free and open source software for epidemiologic statistics. It can be run from a web server or downloaded and run without a web connection.

Link here:


  • PS: Power and Sample Size Calculation version 3.1.2, 201

PS is an interactive program for performing power and sample size calculations that may be downloaded for free. It can be used for studies with dichotomous, continuous, or survival response measures.

C. Sampling

These videos discuss different sampling methods that you could use for quantitative study.



D.Statistical analysis

1.The basics of statistical analysis:


a) An introduction and overall picture

Link here:   

(1_an introduction to the medical statistic – 18 minutes)


b) An introduction to basic statistical terms

Link here:


c) Steps involved in data analysis:

i. Steps in undertaking statistical appropriate statistics:

             Link here:

             (2_undertaking statistical analysis all in one - 47 min)

ii. Choosing a specific type of test:

     1. Two broad types of statistics: descriptive and inferential statistic

                    Link here:

                    (3_concepts of inferential and descriptive statistics)


                2. Descriptive statistic 

                    Link here:

                    (4_descriptive statistic)

      3. Inferential statistics (analyzing the difference between groups, correlational)

                     Independent T-test (5_independent t)

                     Chi-square (6_Chi-square)

                     Correlation (7_correlation)

                     Regression analysis (8_regression)

iii. Making a conclusion from the statistics

     1. Null hypothesis testing: the p value

                    Link here:

                    (9_Hypothesis test)


2. Advanced statistics

a) Overviews

The following provides an overview of multivariate analysis and a step-by-step explanation of the key concepts of regression analysis.

The video will explain the basic concept of regression with examples.

Part 1: (14m)

This video will provide more information on how to conduct regression analysis and interpret the statistical output.

Part 2: (22m)


b) Different Types of Regression

More detailed description of what regression is and elaborations on different types of regression – linear, logistic, multiple regression and ANOVA.

(1)ANOVA: (24m)


(2)Linear regression: (22m)


(3)Logistic regression: (11m)


(4)Multiple regression: (20m)


E. Statistical software for data analysis

SPSS is a commonly used licenced statistical software. Other popular statistical software includes SAS and STATA.


There are also much statistical software which is free and available online with variable quality. A good review of this software is available at Predictive Analytics Today.

Link here:


F. Recommended free statistical software download

1. GNU PSPP can be considered as an alternative to the licensed version of SPSS.

           Link here:


2. SAS University Edition is a free version of select SAS products for teaching and learning statistics and quantitative methods. You will need to create a profile before downloading the software.

Link here:


3. JASP is designed to be easy to use and it has a great graphical interface. It is simple and familiar to users of SPSS.

          Link here:


1. Importing data and basic descriptive statistics with JASP:

Link here:

2. Performing descriptive statistics with JASP

3. Regression analysis with JASP


1. Using PSPP


a) Importing data and basic descriptive statistics using PSPP:

b) Descriptive statistics using PSPP

c) Regression using PSPP: (10m)

d) Linear regression using PSPP: (8m)

e) Multiple regression using PSPP: (7m)


2. Using SPSS

a) Data entry into SPSS


b) Data cleaning 

  • involve generating descriptive statistics (4_SPSS)

c) Normality testing using SPSS

d) Descriptive statistics using SPSS:

     (1) Mean, Mode, Median, normality testing, maximum/minimum, frequency  (6_SPSS)

e) Inferential statistics using SPSS:

    (1) Independent T test (7_SPSS)

(2)Chi-square (8_SPSS) (8a_SPSS)

(3)Correlation and regression (9_SPSS)

(4)Multiple regression

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