INTRODUCTION TO PRACTICAL RESEARCH | FOUNDATIONS OF RESEARCH PHENOMENOLOGY

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Contents of the Key

1. SOURCES OF RELATED LITERATURE AND STUDIES LESSON 3

2. VARIABLES is anything that has a quantity or quality that varies. Is the heart or central concept in research. Is primarily measurable characteristic that changes in value.

3. STATEMENT: For instance, during the quarantine period, your mother planted tomato seedlings in pots. Now common understanding from science tells you that several factors are affecting the growth of tomatoes: sunlight, water, kind of soil, and nutrients in soil.

4. STATEMENT: How fast the tomato seedlings will grow and bear fruits will depend on these factors.

5. VARIABLES ACCORDING TO RELATIONSHIP 1

6. DEPENDENT VARIABLES/ PRESUMED EFFECT The dependent variable is the variable that is being measured or tested in an experiment .

7. DEPENDENT VARIABLES It depends on other variables or factors. It is something that is influenced and affected.

8. INDEPENDENT VARIABLES/PRESUMED CAUSE - a variable that stands alone and isn't changed by the other variables you are trying to measure.

9. INDEPENDENT VARIABLES - affects the dependent variables. It is something you have control over, one which you can choose and manipulate. However, in some cases, you may not be able to manipulate the independent variable.

10. Example: The researcher wants to determine the effects of use of social media in the academic performance of students in Mathematics.

11. Example: Independent Variable: Number of hours studying for a test Dependent Variable: test score Test score depends on the number of hours studying for a test.

12. Example: Independent Variable: Kilowatts used in a household Dependent Variable: electricity bill Electricity bill depends on the kilowatts used in a household.

13. Examples of correlational research questions: What is the relationship between gender and attitudes toward music piracy among adolescents? Independent Variable: gender Dependent Variable: Attitudes toward music piracy

14. Examples of correlational research questions: What is the relationship between study time and exam scores among SHS students? Independent Variable: study time Dependent Variable: exam scores

15. Examples of correlational research questions: STATEMENT ABOVE: Independent Variable: The amount of sunlight, water, and nutrients in the soil Dependent Variable: The growth of tomatoes and the number of fruits produced

16. VARIABLES ACCORDING TO VALUES 2

17. QUANTITATIVE VARIABLES -also called numerical variables , are the type of variables used in quantitative research because they are numeric and can be measured . Under this category are discrete and continuous variables.

18. QUANTITATIVE VARIABLES DISCRETE VARIABLES CONTINUOUS VARIABLES

19. DISCRETE VARIABLES - are countable whole numbers. It does not take negative values or values between fixed points .

20. EXAMPLES: - number of students in a class, group size and frequency.

21. CONTINUOUS VARIABLES - take fractional (non-whole number) values that can either be a positive or a negative.

22. EXAMPLES: Height Temperature

23. *INTERVALS - are quantitative variables where the interval or differences between consecutive values are equal and meaningful, but the numbers are arbitrary.

24. *INTERVALS - Provides information about order and provides an interval. It also determine meaningful amounts of differences between the data.

25. Characteristics: - It is one of the two types of quantitative variables. It takes numeric values and may be classified as a continuous variable type.

26. EXAMPLES: the difference between 36 degrees and 37 degrees is the same as between 100 degrees and 101 degrees. The zero point does not suggest the absence of a property being measured.

27. *RATIO - type of data is similar to interval. The only difference is the presence of a true zero value. The zero point in this scale indicates the absence of the quantity being measured.

28. EXAMPLES: age, height, weight, and distance.

29. VARIABLES ACCORDING TO SCALE OF MEASUREMENT 3

30. QUALITATIVE VARIABLES - also referred to as Categorical Variables are not expressed in numbers but are descriptions or categories. It can be further divided into dichotomous, nominal or ordinal.

31. DICHOTOMOUS VARIABLES - consists of only two distinct categories or values , for example, a response to a question either be a yes or no.

32. NOMINAL VARIABLES - Represent categories that cannot be ordered in any particular way. It is only a matter of distinguishing by name.

33. NOMINAL VARIABLES - simply defines groups of subjects. In here, you may have more than 2 categories of equivalent magnitude.

34. Characteristics: -can be divided into two or more categories. - It is qualitative, means number are used here only to categorize or identify objects.

35. Examples: basketball player’s number is used to distinguish him from other players. It certainly does not follow that player 10 is better than player 8 .

36. ORDINAL VARIABLES - from the name itself, denotes that a variable is ranked in a certain order. This variable can have a qualitative or quantitative attribute.

37. Example: Champion First Runner Up Second Runner UP

38. EXAMPLE: - a survey questionnaire may have a numerical rating as choices like 1, 2, 3, 4, 5ranked accordingly (5=highest, 1=lowest )

39. EXAMPLE: - categorical rating like strongly agree, agree, neutral, disagree and strongly disagree.

40. EXAMPLE: - Other examples or ordinal variable: cancer stage (Stage I, Stage II, Stage III), Spotify Top 20 hits, academic honors (with highest, with high, with honors).