APA Citation Guide

• The 7th edition of the APA Publication Manual was released in October 2019, with updated guidelines on citing and referencing.
• American Psychological Association (APA) Style is used in Social Sciences for citation and references.

In-text Citation and Reference List

• In-text citations are short citations in the body of the paper, appearing parenthetically or narratively.
• The Reference List contains full details of cited works at the end, enabling readers to find them.

Basic In-text Citation:

• Use (Author's Last Name, Year of Publication/ n.d.), with "n.d." if the publication date is unknown.
• Parenthetical Citation involves placing the author's name and year in parentheses.
• Narrative Citation integrates the author's name and year within the sentence.
• Example: Purposive Sampling deliberately chooses informants with certain qualities (Tongco, 2007).

In-text Citation for Short Quotations:

• Include the page number for direct quotes, using "p." for a single page and "pp." for multiple pages.
• Example: (Author's Last Name, Year of Publication/ n.d., page).
• According to Mack et al. (2005, p. 1), Qualitative research is useful for obtaining culturally specific information.

In-text Citation for Long Quotations:

• Quotations of 40+ words should be in a new line, indented 1/2 inch from the left margin.
• Example: Cabading (2015) found that participants prioritized employment in their country (p. 87).

Basic Rules in Formatting a Reference List:

• The Reference List starts on a new page titled "References" in bold and centered.
• Entries are alphabetized by the first author’s last name.
• Author names follow the format: Last name, Initials of First and Middle Name, (date of publication).
• Hanging indentation is used for all lines after the first line of each entry.

Two Authors: In-text Citation:

• Narrative Citation: Connect the two authors' last names with "and".
• Parenthetical Citation: Connect the two authors' last names with "&".
• Example: A study by Inocian & De Vera (2017) showed that participants were influenced by political posts.

Two Authors: Reference List:

• Example: Inocian, R. & De Vera, D. (2017). Influence of Facebook to Voters' Political Practices.

Three and More Authors: In-text Citation:

• Use the first author’s last name followed by "et al."
• Example: Khubchandani et al. (2021) observed that political affiliation predicts vaccine hesitancy.

Three to Twenty Authors: Reference List:

• List all names, separated by commas, connecting the last two with an ampersand "&".
• Example: Khubchandani, J., Sharma, S., Price, J., Wiblishauser, M., Sharma, M., & Webb, F. (2021).

More than 20 Authors: Reference List:

• List all names separated by a comma, using an ellipsis "..." between the 19th and 20th author.
• Example: Pegion, K., Kirtman, B. P., Becker, E., Collins, D. C., LaJoie, E., Burgman, R., Bell, R., DelSole, R., Min, D., Zhu, Y., Li, W., Sinsky, E., Guan, H., Gottschalck, J., Metzger, E. J., Barton, N. P., Achuthavarier, D., Marshak, J., Koster, R., ... Kim, H. (2019).

Group Author: In-text Citation:

• For works by organizations, government agencies, and reference works without credited authors, use the organization's name.
• Example: The Institute for Political and Electoral Reform (2003) states there are 4 phases of the electoral process.

Group Author: Reference List:

• Example: Institute for Political and Electoral Reform. (2003). A voter's choice: Myself: A psychological study on voting behavior of the Filipino electorate.

Sampling Techniques

• Slovin's Formula reduces the population to a statistically reasonable sample size.
• Formula: n = N / (1 + Ne^2).
  • n = sample size
  • N = total population
  • e = error margin

Sampling Techniques Categories

• Probability Sampling: Participants have an equal chance to be selected.
• Non-Probability Sampling: Participants are chosen based on the researcher's convenience.

Probability Sampling Techniques

• Simple Random Sampling
• Systematic Sampling
• Cluster Sampling
• Stratified Sampling

Non-Probability Sampling Techniques

• Convenience Sampling
• Purposive/Judgmental Sampling
• Quota Sampling
• Snowball/Networking Sampling

Quantitative Research:

• is an inquiry into a social or human problem based of testing theory composed of variables, measured with numbers and analyzed with statistical procedures.
• Determines whether the predictive generalizations of the theory are true.
• Quantitative research focuses on using statistics to collect and study numerical data.
• Quantitative research clarifies phenomena by gathering and examining information.
• Examples: weight, height, age, annual income, employee, and general weighted average.

Types of Quantitative Research

• Quasi-Experimental Research aims to establish a cause-and-effect relationship, but doesn't rely on random assignment.
• Experimental Research, or "true experimental," uses the scientific method with data gathered in controlled environments.
• Ex-post Facto Research, or "causal-comparative research," is used to measure the cause of pre-existing effects without variable control.
• Non-Experimental Research observes phenomena as they occur naturally, without external variables.
• Evaluative studies use social research methods for program assessment.
• Normative research studies describe the norm level of traits for a behavior within a population.

Statistical Treatment

• is the method used to test the hypothesis.

Descriptive Statistics

• Measure of Central Tendencies: mean, median, mode.
• Frequency and Percentage
• Variance and Standard Deviation

Descriptive Statistics Details

• Mean: sum of all values divided by the total value.
• Median: middle value arranged in ascending/descending order.
• Mode: most frequent value.
• Frequency: how many times each value/response occurs.

Percentage Calculation

• Percentage = (frequency / Total Sample Size) x 100
• Guiding Principle.
• Reject the null hypothesis if the p-value is less than the alpha-value (p < α).

Parametric Tests

• make assumptions about the given population (normal distribution), and are more powerful for detecting real differences.
• They provide more accurate estimates using means and standard deviations.

Nonparametric Tests

• are used when the population distribution is unknown, reliable for small samples.
• Works with ordinal data, better for unevenly distributed heights.
• Parametric tests are like highways (smooth data), nonparametric tests are like off-road vehicles.

Normality Test

• Shapiro-Wilk test: best for small samples.
• Kolmogorov-Smirnov Test: used for larger samples.
• Anderson-Darling Test: more sensitive than K-S
• Normal Q-Q Plot: visual checks for normality.
• Hypothesis for Normality.
  • Null: The distribution is normal.
  • Alternative: The distribution is non-normal.

Homoscedasticity Test

• Levene's Test (most common): checks variance in test scores.
• Barlett's Test: checks variance in multiple class sections.
• Breusch-Pagan Test: checks if experience affects salary variance.
• Hypothesis for Variance.
• Null: The variance is equal - parametric
• Alternative: The variance is unequal. Non-parametric

Relationship Tests

• Chi-square test
• Linear Regression
• Multiple Regression
• Scatter Plot