Ang research variables ay yung mga bagay-bagay that can be measured, that you can see in a research or in an experiment. They have quantitative and qualitative characteristics. Yun yung minimesure mo at yun yung tinidescribe mo. Isa sa mga bagay na nahihirapan ang mga mag-aaral sa pananalisi ay yung pag-identify. ang tinatawag natin mga types of research variables.
So, ano pang inaantay ninyo? Tignan natin at pag-aralan natin ang mga ito. Sa scientific research, merong dalawang klaseng research variable ang pinaka-common.
Ito yung tinatawag natin independent variable and dependent variable. So, unahin na natin yung independent variable. Pag sinabi natin independent variable sa isang research setup, malimbawa sabihin natin, nage-experiment ka, ito yung tinatawag natin, kinokontrol natin, o yung minapalipid natin.
In literature, sa mga libro, ito yung dinidefine nila as something that causes change. So, yun yung tinatawag natin independent variable. Dito sa example natin, nakalagay dito, one example of independent variable is what you call the kind of diet. So, alimbawa, gusto mong subukan kung ano yung tinatawag nating kind of diet na pwede mong i-adapt para mag-lose ka ng weight. Now, may mga prominente na pamamaraan ng pagdadiet.
Ito ay, pwede, you're going to do keto diet or... yung tinatawag natin diet na less on carbs and more on protein. Or, gusto mong itry yung isa, yung tinatawag natin intermittent fasting.
Pag sinabi natin intermittent fasting, in a certain time at a certain day, dun ka lang po pwedeng kumain. Parimbawa, common patterns niyan ay yung 16-8. Ibig sabihin, 16 hours. mapapasting ka, hindi ka kakain, tapos yung 8 hours, doon ka naman po pwedeng kumain within that 8 hour span.
So gusto mong malaman, alin sa dalawa, yung tinatawag natin makakapagpabawas ng weight mo o makakapagpabawas ng mass mo o ng timbang mo. So yun yung inocontrol mo. Yun yung binamanipulate mo. Yung kind of diet mo.
Okay? Now, so that is the independent variable. Actually, dun sa example pa lang natin, kitang-gita na kung ano yung dependent variable mo. Yung tinatawag natin resulta ng change o ng minanipulate mo na independent variable.
Okay? Kasi si dependent variable is simply the result of the changes that you have made. Kung pinili ko ba yung keto diet, bababawasan ba yung timbang ko? Kung pinili ko ba yung tinatawag nating intermittent fasting, bababawas ba yung, makakatulong ba yun? Para babawasan yung aking timbang.
Now, dito, another example in this slide, ng dependent variable, yung tinatawag nating, basahin natin, a grade someone gets on an exam depends on factors. Such as how much sleep they got and how long they studied. Buuhin natin yung senaryo. Ano ba sabihin natin, independent variable mo dito ay yung haba ng tulog mo. May dalawang persons.
Yung person A, person B. Sa person A, ang tulog niya ay 8 hours. Si person B naman, ang tulog niya... 4 hours.
Alright? Ngayon, kinabukasan si person A na may 8 hours na tulog at si person B na may 4 hours na tulog ay mag-take pareho ng exam. Pareho yung exam na iti-take nila, pareho yung hirap, pareho yung place na pag-take nila ng exam.
Now, yung resulta o yung scores nila doon sa exam na pareho nilang tinake, yun yung tinatawag nating dependent variable. Parang doon sa experiment na yun, gusto mo lang patunayan. na kapag ka mas mahaba-haba ang aking tulog, ano kaya ang score na makukuha ko sa exam?
Pagka, limbawang, maiksilang ang tulog ko, ano ba yung makukuha kong score doon sa exam? In certain studies like this, minsan gusto mong patunayan na pagka mas mahaba ang tulog mo, mas focus ka, mas concentrated ka, mas mataas yung... tinatawag natin, iscore mo. Minsan yun ang gusto nilang patunayan sa mga ganyang klase ng mag-aaral. Ngayon, try natin magbigay pa lang isang example bukod na.
Halimbawa sabihin natin, ito common example, pang elementary. Halimbawa sabihin natin, gusto mong malaman kung aling klase ng fertilizer yung mas effective. Yung tinatawag natin, natural fertilizer.
o yung tinatawag natin commercial fertilizer, o yung mga tinatawag natin synthetic fertilizer, o yung may chemicals, or made out of chemicals. So, ang yung independent variable doon, o gusto mong i-manipulate, ay yung klase ng fertilizer. Yung independent variable mo, yun yung independent variable mo, yun yung i-manipulate mo. Yung independent variable mo is ano ba ang magiging epekto? ng kada klase ng fertilizer dun sa halaman in terms of growth.
Yung growth ay yung height niya. Sabihin natin yung height. So, ang independent variable mo dun ay yung klase ng fertilizer.
Bawa, may dalawa kang halaman. Si plant A, ilalagay mo yung natural fertilizer. Si plant B, ilalagay mo yung tinatawag natin artificial fertilizer. o yung artificial, the right term is artificial, fertilizer.
Ngayon, after some time, palalakihan mo yung halaman, titignan mo kung sino yung mas mataas, yung high. Si plant A ba? Naginamitan mo ng tinatawag nating natural fertilizer? O si plant B ba? na ginamitan mo ng artificial fertilizer.
So, yun yung tinatawag natin, independent at dependent variable. Muli, pag sinabi natin independent variable, it is the part of the experiment or the component of the experiment that you change. It is the one that causes change. It is the one that you manipulate.
Whereas, pagka naman dependent variable, ito yung tinatawag natin, part na experiment na nagiging resolved. ng change na ginawa mo sa independent variable. I hope that's clear.
Next, mayroong mga other kinds of variables pero ito, they are lesser important as compared to the independent and dependent variable. But literature said that you have to always keep them in check. Kasi minsan, nakakaroon sila ng epekto o naapektohan nila yung kinakalabasan o yung resulta ng study.
Ito sila. Ito, intervening variable. Pag sinabi natin intervening variable, allow me to read the definition.
It acts as a mediator between the independent and dependent variable. It explains the relationship between them by suggesting a mechanism or process through which the independent variable influences the dependent variable. Example natin dito, yung tinatawag natin, driving skills.
Pag alimbawa, you wanted to... Look into the speed by which a specific vehicle will get into a place. Halimbawa, masahin natin. If the independent variable is the road one will take to get to a destination. So, halimbawa, sabihin natin.
Yung isa, road A ang kukunin. Yung isa naman, road B. And the dependent variable is the time of arrival to the designated place.
The skill of the one driving the vehicle. may be the intervening variable. Okay? Whereas, the driving skills of the driver of the vehicle may affect his or her speed in getting to the destination. Halimbawa, sabihin natin, yung kumuha or nag-take ng road game going to a certain destination, eh mas eksperto pala.
O mas magaling pala yung kanyang driving skills. Mas mataas. Whereas, yung kumuha o nag-take ng roadway going to the same destination ay medyo sakto lang.
O kung hindi naman mas mababa yung kanyang driving skills. Siyempre, unknowingly, maapektuhan nun yung bilis ng pagdating nila doon sa tinatawag nating destination. Okay?
So, yun yung sinatawag nating mga intervening variables. Hindi natin sila masyadong... kontrolado. But we have to make sure kung malalaman natin yung mga ito, itong mga factor na ito, we have to keep them in check. Or we have to make sure that if we have two things or three things that we are comparing in an experiment, dapat siguraduhin natin na pare-pareho sila.
O sa research, tinatawag natin niyang comparable. Next, meron din tayong tinatawag na moderating. variable. Kapag sinabi natin moderating variable, this influences the strength or direction of the relationship between the independent and dependent variables. However, it is stated here, it doesn't directly cause the effect, but it may have an influence to the dependent variable.
Kaya dapat maging mainga tayo dito. Example dito ay yung age. Suppose researchers are investigating the relationship between exercise and mental well-being. Siyempre, magkaiba ng reception o magkaiba ng understanding at kakayahan yung sabihin natin age group ng mga nasa 20 sa nasa 40s.
Siyempre, medyo pagdating sa body capacity, medyo mababa yung nasa 40s. Now, the male-deriving variable in this scenario could be age, just like what I've mentioned. The relationship between exercise and mental health or mental well-being may differ across different age groups, with younger individuals experiencing a stronger relationship compared to older individuals. Kasabihin natin, diba, sa senaryo na ito, sinasabi, si exercise ay nakakapagpaganda ng mental well-being ng isang tao.
Alright? Ngayon, Sa mga nasa 20s, meaning 21 to 29, they welcome it well. Alright? Paano they welcome it well? Kasi mas bata pa sila.
Kunti pa yung mga tinatawag nating mga body pains. So, pagka nag-exercise sila, maaaring mas magandang efekto nito sa well-being nila. Whereas, pag alimbawa, 40s, sorry po, sa ating mga 40 pataas, maaaring may nararamdaman nila na sila.
na po pwede nakaka-apekto dun sa well-being nila. Masaya silang nag-exercise sila. Pero po pwede yung mga joint pains nila could also affect the mental well-being na nakakaramdam sila ng pain.
So, apektado pa rin. So, we have to look out for these moderating variables as well. Okay?
Next. Meron tayong tinatawag na extraneous variable. So, these are unwanted factors that can, again, influence the dependent variable but weren't originally considered in the study design.
Okay? And they can introduce bias and distort the results, making it harder to determine the true relationship between the independent and dependent variable. Ibig sabihin lang nito, hindi mo talaga alam kung yung independent variable ba talaga yung nakapag-cause ng resulta.
Example po. In a study examining the... effectiveness of a new medication for treating depression, age could be an extraneous variable. Older individuals might respond differently to the medication compared to younger individuals.
Bakit? Yung mas bad, you're trying to treat depression. So baka mamaya, yung epekto ng gamot kay nakababata ay mas okay kasi lesser yung mga responsibilities niya.
Therefore, mas kokonti yung iniisip niya. So mas mabilis yung pagaling ng depresyon niya. Whereas, baka mamaya, again, this is hypothetical, yung mas matanda, mas lesser ang effect ng medication sa kanya kasi...
mas marami siyang pinagdadaanan, mas marami siyang responsibility. So, magkaiba yung epekto. Now, another example. Tignan natin yung physiological side. Ano ba kasabihin natin?
Balik tayo dun sa tinatawag natin. Ang independent variable natin ay yung tinatawag natin mga mode or kind of diet. Ulitin ko ha, baka mamaya na-confuse tayo dito. Pag sinabi natin yung diet, Hindi yung iba to sa reduce.
Kasi nasabi kasi diet ka ba? O nagda-diet ka. Ang ibig sabihin na nagre-reduce ka ba? Mali yun.
Pag sinabi ng diet, ito yung klase ng pagkain mo. O yung manner ng pagkain mo. So that is diet.
Ngayon, ito sa another example natin. Si diet, or kind of diet, yung independent variable mo. Independent variable mo, sabi natin kanina.
you might want to lose weight. Now, you wanted to find out if you're going to lose weight, if you're going to either use keto diet or intermittent fasting. Kaso nga lang ang problema ganito.
Kung may dalawang tao, si person A, magtetake siya ng intermittent diet or yung intermittent fasting. Tapos si person B, ay magtetake ng keto diet. Baka mamaya, si person A pala. nag-intermittent fasting, ay mabagal pala yung kanyang tinatawag na metabolism. Kundi syempre, hindi na fair.
No? So, baka mamaya, mag-deduce ka na CB, mas pumayat siya, therefore, mas effective ang keto diet. Kasi nga, mas pumayat siya.
Eh yun pala, mayroon palang underlying factor. At yung underlying factor na yun, ay yung rate of metabolism. Now, Kaya nga dapat palaging isipin natin, yung rate of metabolism, medyo generally, mas mabagal na siya sa mga matatanda as compared sa mga younger people. So yun, dapat take it in consideration mo yun.
Ito yung mga hindi mo nakikita, pero makakapekto sa resulta ng study mo. Next, you also have the confounding variable. Ang sabi sa literature, Itong confounding at extra use, halos pareho.
Pero, meron pa rin siyang tinatawag na pinakaiba. Tignan natin example. In a study examining the relationship between education level and income, socioeconomic status could be a confounding variable.
Still, it may affect the result. People from higher socioeconomic backgrounds might have access to better educational opportunities kasi may pera sila. leading to higher education levels and subsequently higher income.
Okay? So, kahit na sabihin natin, pareh sila ng education level na tinatawag. Pareh sila ng, nabawa, college degree graduate.
Okay? Meron pa rin pinagkaiba ng efekto ito doon sa kanilang income. Alright? So, nabawa, sabihin natin sa person A, college degree graduate, pero...
medyo mahirap siya. Sabihin na lang natin, si A yung may pera. So pagka may pera ka, pwedeng sabihin natin, mas maganda yung school na napagtapusan mo.
Mas marami kang correction na nagawa doon. Whereas sa person B, college graduate siya, pero yung socioeconomic status niya medyo mas mababa. Siyempre, sabihin natin, doon siya nakapag-aral sa hindi masyadong kilalang school, lesser ang connection. Ngayon, si person A, ay mas mataas ang tendency na mas kumita siya ng maraming pera o mas mataas yung income niya. Kasi nga, greater connections may lead to higher income dahil maaaring mas maganda yung mapasukan mo na trabaho.
So, factor pa rin yung socioeconomic status. Pero take note, hindi mo siya ina-account doon sa study. Hindi mo siya kinoconsider.
Ang pinag-uusapan mo lang dito, babalikan natin, ang independent variable mo lang dito ay yung tinatawag nating education level at yung dependent variable mo dito ay yung income. Alright? I hope nasusundan pa tayo, no?
And, of course, we also have the what we call control variables. Pag sinabi natin control variables, ito yung ginagawa nating constant, no? All throughout the study.
Alright? So, example dito. In an experiment, dapat ito yung pareho lang ha, sa lahat ng setup.
In an experiment, studying the growth of plants. the species of plant or the kind of plant and the kind of soil can be controlled variables. Saban na natin pati yung klase ng tubig na ipinandidilig mo.
Sabihin natin, meron kang dalawang setup, plant A, plant B. Sabibali ka natin yung study natin earlier na si plant A, bibigyan natin ng natural fertilizer. Si plant B naman, titreat natin ng artificial fertilizer. Alin yung mas mataas ang growth ng halaman after a few weeks, after a few months. Ang control variable natin doon na kailangan natin mapanatiling pareho doon sa set up A, sa plant A, at sa plant B ay yung klase ng halaman.
Kasi pagminsan kahit nasabihin mong monggo, meron yung mga variation. Pag sinabi natin eggplant, may iba't ibang klase yan. So dapat yung species niya pareho. So yung soil, dapat pareho yung soil kasi dapat pareho ng amount ng nutrients yan.
Yung amount of sunlight, dapat constant yan. Baka mamaya yung plant A, tama lang yung sunlight niya. Tapos yung plant B, lesser yung amount of sunlight na sa loob ng kwarto. O di ba, astunted yung growth nun.
So yun yung mga tinatawag nating control variables. Dapat constant sila in all the setups. ginagawa mo.
Tandaan na, ang setup ay hindi lang limited sa dalawa. Pwede maging tatlo, apat, o mas marami pa. Okay?
Alright. Okay. And that ends our discussion regarding research variables and their types.
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