A4B-VARIABLES IN QUANTITATIVE RESEARCH.pdf

VARIABLES IN QUANTITATIVE RESEARCH EXPECTATIONS ◦define what variables are and identify its types; ◦ identify the variables involved in different research-related life situations; and ◦ realize the importance of variables in quantitative researches  THE NATURE AND KINDS OF VARIABLES VARI...

VARIABLES IN QUANTITATIVE RESEARCH EXPECTATIONS ◦define what variables are and identify its types; ◦ identify the variables involved in different research-related life situations; and ◦ realize the importance of variables in quantitative researches  THE NATURE AND KINDS OF VARIABLES VARIABLES Variables ◦the heart or central concept in research ◦measurable characteristic that changes in value Variables ◦may be different from characteristic to another characteristic, one group to another group, one person to another person or even with the same person over time Variables ◦may be different from characteristic to another characteristic, one group to another group, one person to another person or even with the same person over time Variables ◦anything that may assume different numerical or categorical values Examples of Variables ◦Sex ◦it may be male or female ◦won’t be applicable as a variable if the setting of a research is an exclusive school for the girls. Examples of Variables ◦Socio-economic status ◦it deals with the earnings of every employee or worker and may range from zero to billion pesos Examples of Variables ◦Parents’ educational attainment ◦educational background of the parents from did not attend school to post- doctorate degree  TYPES OF VARIABLES Types of Variables ◦ 1. Continuous and ◦ 5. Constant Variables Discrete Variables. ◦ 6. Continuous Variables ◦ 2. Discrete variable or ◦ 7. Dichotomous categorical variable Variables ◦ 3. Dependent and ◦ 8. Latent Variables Independent Variables ◦ 9. Manifest Variables ◦ 4. Confounding variables and Control ◦ 10. Extraneous Variables Variables Types of Variables 1. Continuous and Discrete Variables ◦Continuous variable is a variable that can take infinite number on the value that can occur within a population. Examples: Age, height, and temperature. ◦Interval variable and Ratio variable Types of Variables 1. Continuous and Discrete Variables - Interval variable ◦It gives meaning on the measured difference of two values for example the difference between a temperature of 60 degrees and 50 degrees the same difference as between 30 degrees and 20 degrees. The interval of temperature difference between values makes sense and can be interpreted. Types of Variables 1. Continuous and Discrete Variables - Ratio variable ◦have the properties of interval variable and has a clear definition of zero, indication that there is none of that variable. ◦Examples Height, weight, and distance. Types of Variables 2. Discrete variable or categorical variable ◦is any variable that has a limited number of different values, and which cannot be divided into fractions like sex, blood group, and number of children in the family. ◦For example, your age can be 15.5 years old so it is a continuous variable but your parents cannot have 3.5 children, so it is a discrete variable. Types of Variables 2. Discrete variable or categorical variable ◦Nominal variable ◦Ordinal variable Types of Variables 2. Discrete variable or categorical variable - Nominal variable ◦is a discrete variable with no quantitative value. It has two or more groupings although does not imply ordering of cases. Types of Variables 2. Discrete variable or categorical variable - Nominal variable ◦Examples are eye color, business type, and religion. A sub- type of nominal scale with two categories just like sex (e.g. male/female) is known as dichotomous. Types of Variables 2. Discrete variable or categorical variable - Ordinal variable ◦discrete variable that has two or more categories which can be ranked. Types of Variables 2. Discrete variable or categorical variable - Ordinal variable ◦For example you asked participants if they liked listening to music while studying and they could answer either “Never”, “Sometimes” or “Always” then you have an ordinal variable. ◦ Despite the fact that we can rank them, we cannot place a value to them. In this category, distances between attributes do not have any meaning. Types of Variables 2. Discrete variable or categorical variable - Ordinal variable ◦Example, you used educational attainment as a variable on a survey, you might code: ◦elementary school graduate =1 ◦high school graduate = 2 ◦college undergraduate = 3 ◦college graduate = 4. Types of Variables 2. Discrete variable or categorical variable - Ordinal variable ◦ Example, you used educational attainment as a variable on a survey, you might code: ◦ elementary school graduate =1 ◦ high school graduate = 2 In this measure, lower ◦ college undergraduate = 3 number means lower ◦ college graduate = 4. education and vice versa. Types of Variables 3. Dependent and Independent Variables ◦Independent variable ◦The cause variable or the one responsible for the conditions that act on something else to bring about changes and it can stand alone ◦Experimental or predictor variable Types of Variables 3. Dependent and Independent Variables ◦Dependent variable ◦result or effect of the changes brought about by another variable (independent variable) ◦what the researcher is interest in outcome variable Example: Identify IV and DV ◦In one study, a group of selected students was subjected to aroma therapy using essential oils while reading while another selected group of students read under normal conditions, then after a month of the process both groups took a reading comprehension test. Example: Identify IV and DV ◦Elaine wants to know how the types of teaching style of teachers impacts the achievement test results Example: Identify IV and DV ◦Elaine wants to know how the types of teaching style of teachers impacts the achievement test results independent variable Example: Identify IV and DV ◦Elaine wants to know how the types of teaching style of teachers impacts the achievement test results independent variable Examples: Identify IV and DV ◦In one study, a group of selected students was subjected to aroma therapy using essential oils while reading while another selected group of students read under normal conditions, then after a month of the process both groups took a reading comprehension test. Examples: Identify IV and DV independent variable ◦In one study, a group of selected students was subjected to aroma therapy using essential oils while reading while another selected group of students read under normal conditions, then after a month of the process both groups took a reading comprehension test. 4. Confounding variables (confounders) ◦are variables that are related to both the independent and dependent variable which may lead to a wrong conclusion about the relationship or causation between the two variables 4. Confounding variables (confounders): Example ◦During the rainy season, Iris found out that there are high cases of common cold and cough when there is an increased consumption of instant noodles.  4. Confounding variables (confounders): Example Does this mean that ◦During the rainy season, Iris found out instant noodles may that there are high cause common cold and cases of common cold cough? and cough when there is an increased consumption of instant noodles. Of course, not ! Hence, temperature is a confounding variable  4. Confounding variables (confounders): Example ◦ Comparing cleaning products, the brand of cleaning product would be the only independent variable measured. ◦ The level of dirt and soiling, the type of dirt of the stain, the temperature of the water and the time of cleaning cycle are just some of the variables that must be identical to between experiments.  4. Confounding variables (confounders): Example ◦ Comparing cleaning products, the brand of cleaning product would be the only independent variable measured. ◦ The level of dirt and soiling, the type of dirt of the stain, the temperature of the water and the time of cleaning cycle are just some of the variables that must be identical to between experiments. Failure to standardized even one of these controlled variables could cause cofounding variable and nullify the result  5. Constant Variables ◦are traits or characteristics that do not change throughout the experimentation or research process  6. Continuous Variables ◦are those variables which fall under interval and ratio scale of measurement. ◦Examples are height and weight of objects.  7. Dichotomous Variables ◦are those variables with only two possible results. ◦Examples are Yes-or-No responses and Head-or-Tails in a coin toss.  8. Latent Variables ◦are variables which cannot be explicitly seen, observed, or measured. ◦Examples are feelings, emotions, and attitudes towards a certain thing  9. Manifest Variables ◦are variables which can be seen, observed, or measured directly. ◦Examples are color of hair, height, and sex. 10. Extraneous variable ◦Variables that are not independent variables which can affect or relate to another variable Manolo proposes that background music can affect task performance among bank employees. 10. Extraneous variable extraneous variables: “loudness of background music”, “genre of music”, “job motivation” or even “employee’s tiredness” independent variable Manolo proposes that background music can affect task performance among bank employees. dependent variable 10. Extraneous variable Extraneous variables and their effects in the study can always be controlled by the researcher. Randomization of respondents or subjects in the study is one way of controlling the effect of extraneous variables. A thorough procedure of designing the methodology of your study can also help control your extraneous variables 10. Extraneous variable: Control Variable Variable does not wish to examine in a study. Constant and unaffected in an experiment. Strongly influences values. Held constant to examine relative impact of independent variables 10. Extraneous variable: Control Variable Control Variable should not be confused with controlled variable, which is an alternative term for independent variable. Control Variable The use of control variables is generally done to answer four basic kinds of questions: 1. Is an observed relationship between two variables just a statistical accident? Control Variable The use of control variables is generally done to answer four basic kinds of questions: 2. If one variable has a casual effect on another, is this effect a direct one or is it indirect with other variable intervening? Control Variable The use of control variables is generally done to answer four basic kinds of questions: 3. If several variables all have causal effects on the dependent variable, how dies the strength of those effects vary? Control Variable The use of control variables is generally done to answer four basic kinds of questions: 4. Does a particular relationship between two variables look the identical under various conditions? Moderating Variable: ◦A moderator variable is a variable, which is thought to temper or modulate the magnitude of the effect of an independent variable on a dependent one Intervening Variable ◦ An intervening variable is a variable that handles the change in the dependent variable due to the change in the independent variable. ◦ In other words, the outcome of the dependent variable is decided through the intervening variable, which itself gets influenced by the independent variable. ACTIVITY: Google Classroom