Overview-of-Quantitative-Research-and-Data-Analysis.pptx

Quantitative Research

1. Quantitative Research and Data Analysis Irmalyn B. Paymalan, MS Surigao del Norte State University-City Campus

2. Learning Objectives

3. Choosing the right methodology Training- Workshop on Statistical Data Analysis: Phase II “the methodology that’s used comes from the research question, not from your personal preferences for one design or another.” - Dr. Linda Crawford, Walden University

4. 1 Determine the Research Problem 2 Find Background Information 3 Identify Research Objectives 4 Choose the research methodology 5 Data Cleaning, Processing and Analysis 6 Present Research Results and Findings Training- Workshop on Statistical Data Analysis: Phase II

5. Preliminary Activity: Data Processing Training- Workshop on Statistical Data Analysis: Phase II Data processing is the first step in transforming raw data into information It is a step in the research process where the data collected are transformed into a form suitable for data analysis This phase of research involves two steps: Editing the data Coding the data

6. Preliminary Activity: Data Editing Training- Workshop on Statistical Data Analysis: Phase II It is a step in the research process which is undertaken before data analysis, wherein the data collected are inspected and corrected, if necessary Phase When it is conducted? What are edited? 1 Right after data collection, before data are coded. This phase is usually done in the field Errors in data collection; errors in filling- in the data collection forms 2 Right after the data are entered into the Computer, before the statistical outputs are generated Errors in coding; errors in data entry

7. Preliminary Activity: Items considered in Data Editing Completeness of the data collection tool ex., items left blank; missing pages Values which are out of range ex., reported age of 60 for a female respondent in a family planning survey Logical inconsistencies ex., a death certificate for a deceased male whose cause of death is reported to be cancer of the ovary Comprehensibility ex., data collector’s handwriting cannot be read Irrelevant responses

8. Preliminary Activity: Data Coding and Encoding Row: Information/ Profile of each respondent/ sample Column : Variables/ parameters being measured from each respondent Training- Workshop on Statistical Data Analysis: Phase II

9. Objectives of the Study Type of Variable being Analyzed Study Design Number of variables included in the analysis Sample size Assumptions to Inferential Analysis (Extent to which usual requirements for the valid application of parametric tests are satisfied) Training- Workshop on Statistical Data Analysis: Phase II Factors to be Considered in Data Analysis

10. 1. Objectives of the Study: Example Training- Workshop on Statistical Data Analysis: Phase II Statement of Objectives Variable(s)/ Parameter(s) to measure Statistical Analysis Determine the climate condition in Butuan City in terms of Rainfall magnitude (in mm) Relative Humidity (%) Tmax (  C) Tmin (  C) Solar Radiation Rainfall magnitude (in mm) Relative Humidity (%) Tmax (  C) Tmin (  C) Solar Radiation Estimation of means Ascertain the incidence of acute respiratory infection (ARI) among residents of different age groups in each barangay of the City 2 years old and below 3 to 10 years old 11 to 19 years old 20 to 59 years old 60 years old and above Incidence of ARI among different age groups in each barangay Estimation of total, proportion Compare the incidence of ARI among different age groups Incidence of ARI among different age groups in each barangay Estimation of total, proportion Test for significant difference

11. 1. Objectives of the Study: Example Training- Workshop on Statistical Data Analysis: Phase II Statement of Objectives Variable(s)/ Parameter(s) to measure Statistical Analysis Determine the association/ relationship of the climate condition and the incidence of ARI among different age groups Same timeframe of climate parameters and incidence of ARI Rainfall magnitude (in mm) Relative Humidity (%) Tmax (  C) Tmin (  C) Solar Radiation Incidence of ARI for each group Test for significant relationship/ association Determine whether climate parameters are significant factors affecting the incidence of ARI among residents in Butuan City Independent variables: Climate parameters Dependent variable: Incidence of ARI for each group Regression Analysis

12. 2. Type of Variable being Analysed Variables Quantitative Qualitative Discrete Continuous assumes values that are names or labels, thus can be categorized (categorical variables) -Categories may be identified by either non- numerical descriptions or by numerical codes Ex. Civil status, religious affiliation, etc. Training- Workshop on Statistical Data Analysis: Phase II - variables that are measured on a numeric or quantitative scale - variables with a finite or countable number of possible values (no. of children infected with dengue virus) - variables that assumes any value in a given interval rainfall magnitude (in mm); temperature

13. 2. Type of Variable being Analysed Nominal Training- Workshop on Statistical Data Analysis: Phase II Ordinal Interval Ratio Nominal Level the data collected are labels, names or categories -frequencies or counts of observations belonging to the same category can be obtained every case must be nonoverlapping, mutually exclusive and exhaustive It is the lowest level of measurement 2. Ordinal Level data collected are labels with implied ordering does not indicate the magnitude of the differences between numbers 3. Interval Level - the level of measurement that does not only indicate ordering but also the exact distance between them - the data at this level has lack an absolute zero point 4. Ratio Level - the same as interval level, however, the number zero indicates the absence of the characteristics being measured (has absolute zero point)

14. 3. Study Design Training- Workshop on Statistical Data Analysis: Phase II Type of Study. Experimental, descriptive, etc. Mode of Sample Selection. Sampling design/ experimental design Type of Samples. Independent/ related samples (If comparison, number of groups being compared)

15. 4. Number of Variables Included in the Analysis Training- Workshop on Statistical Data Analysis: Phase II Univariate analysis Bivariate analysis Multivariate analysis

16. 5. Sample Size Training- Workshop on Statistical Data Analysis: Phase II Large samples Small samples Note: some statistical tests require a certain number of samples to warrant the application of these tests (e.g. correlational analysis; regression analysis, etc.)

17. 6. Assumptions to Inferential Analysis Training- Workshop on Statistical Data Analysis: Phase II Normality of the data – the observations must be drawn from a normally distributed population Independence of observations – the selection of any one case from the population for inclusion in the sample must not bias the chance of any other case for inclusion the score/value which is assigned to any case must not bias the score which is assigned to any other case Equality of variances (homoscedasticity) – when greater than or equal to 2 groups are studied, the populations must have the same variances (or on special cases, must have a known ratio of variances)

18. Exercise Training- Workshop on Statistical Data Analysis: Phase II Statement of Objectives Variable(s)/ Parameter(s) to measure Level of Measurement Data (Nominal, Ordinal, Interval/Ratio) Type of Analysis (univariate, bivariate, multivariate) Statistical Analysis

19. References/ Acknowledgement Training- Workshop on Statistical Data Analysis: Phase II Walpole, R.E., Myers, R.H., Myers, S.L. and Ye, K. (2007) Probability & Statistics for Engineers & Scientists. 9th Edition, Pearson Education, Inc. Verhaeghe, Pieter-Paul. (2022). Statistics for the social sciences. 2nd edition.

20. Thank you for participating!