Practical Research 2 Types of Quantitative.pptx

Quantitative

1. Variables in Quantitative Research

2. Why is there a need to understand the different variables in research? 2

3. How do you think our body changes when we eat nutritious food and exercise regularly? What do you think causes our body to become unhealthy? 3 3

4. Variables are anything that can be observed by the researchers. A variable may be a person, thing, place, situation, or phenomenon. Variables in Quantitative Research 4

5. Different Types of Variables Variables can be categorized depending on the level of measurement and role . 5

6. Why is it important to understand the roles of variables in research? 6

7. Roles of Variables Independent and Dependent Variables The independent variable , also called causal variable , is presumed to cause the change towards another variable, which is known as the dependent variable or the outcome variable . 7

8. The independent variable may influence another variable to change. In experimental research, independent variables may also be manipulated to examine the specific effect they may have toward the dependent variable. 8 8

9. The dependent variables are the variables that are influenced by the independent variables. 9 9

10. Example: A researcher is determining the effects of self-motivation on the productivity of employees . Independent variable : Self-motivation Dependent variable: Productivity of employees How do you think self-motivation can have an effect on employee productivity? 10 10

11. Example: 2. A researcher is trying to determine the effectiveness of different coaching styles on volleyball teams. Independent Variable: Coaching styles Dependent Variable: Win streak How do you think the different coaching styles affect the win streak of volleyball teams? 11 11

12. Mediating Variables Mediating variables are also known as intervening variables since they intervene between the independent and dependent variables to show their connection. 12 12

13. Example A researcher wants to know the effects of working seven days a week on the employee’s productivity level. Independent variable: Seven-day work week Dependent variable: Productivity level Mediating variable: Job satisfaction What do you think makes job satisfaction the mediating variable? 13 13

14. 14 A mediating variable may act as a dependent variable and independent variable at the same time.

15. Moderating Variables Moderating variables are variables that have a strong conditioned effect, which may modify the relationship between the independent and dependent variables. 15 15

16. Example A researcher wants to know the effects of exercising regularly on one’s weight loss. Independent variable: Regular exercise Dependent variable: Weight loss Moderating variable: Gender What do you think makes gender a moderating variable? 16 16

17. 17 A mediating variable should act as a dependent variable with respect to the independent variable and may also cause change to the dependent variable, while a moderating variable must not be directly affected by the independent variable and should not result to it in any way.

18. Extraneous Variables Extraneous variables are variables that should be mainly excluded from the research study as they may interfere and compromise with the experiment and research results. 18 18

19. Example A researcher wants to know the effect of how poor garbage disposal can have an impact on pollution. Independent variable: Poor garbage disposal Dependent variable: Pollution Extraneous variables: Environmental factors; people What makes the variables environmental factors and people extraneous? 19 19

20. Level of measurement The measurement level, also called scales of measure , gives you an idea of the type of data you have. 20

21. Level of measurement can be classified into two: categorical and continuous measures of variables. A categorical variable is further categorized into nominal and ordinal levels, while a continuous variable is categorized into interval and ratio levels. 21 21

22. Categorical Variables A nominal variable is any variable that represents different types of data, which may be divided into groups or categories. There is no intrinsic order; hence, its frequencies can only be counted. The examples are race, ethnicity, and hair color. 22 22

23. Categorical Variables An ordinal variable is any variable that may also be divided into groups or categories, but it has intrinsic order or rank. Its frequencies can be both counted and ranked in which the distance between categories is not equivalent. 23 23 Some examples are year of graduation, brands of bags, and food preference.

24. Continuous Variables An interval variable is a variable that has a numerical value. It can be counted and ranked , and the differences between the ranked categories are meaningful. There is no true zero point . 24 24

25. Continuous Variables For example, you know that the difference or interval between 25 ° C and 35 ° C is the same between 10 ° C and 20 ° C. Just like in the example, if you say, -6 ° C, then that means below freezing point. 25 25

26. Continuous Variables A ratio variable is an interval value, but unlike the interval variable, it has a true zero. It has numerical value and meaning which can also be counted , ranked , and has a meaningful difference between values. There is a true zero point , which means that nothing exists for that variable and that zero simply means none. 26 26

27. Continuous Variables For example, A person’s weight can be counted, ranked, or you can determine the equivalent distance between a person’s weight with another. If you say that there is 0 kg, then there is no weight measured at all or there is no difference in their weight. 27 27

28. 28 It is important that as researchers, we are knowledgeable about our variables because research mainly revolves around them.

29. Practice List down as many variables as you can with the given phenomena: Climate change Political system in the Philippines Low customer retention 29