Scientific Research Methodology PDF 2020

Scientific ResearchMethodology Unit 5: Identifying Variables Al Ain University College of Business First semester...

Scientific ResearchMethodology Unit 5: Identifying Variables Al Ain University College of Business First semester 2022-2023 R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 1 / 22  Outline 1 Variables and Concepts 2 Types of Variable Viewpoint of causal relationships Viewpoint of study design Viewpoint of unit measurement 3 Measurement Scales R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 2 / 22  Variables and Concepts Research Journey R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 3 / 22  Variables and Concepts What is a Variable? l In the process of formulating a research problem (quantitative research), there are two important considerations: ) The use of concepts ) The construction of hypothesis Concepts are highly subjective as the understanding of them varies from person to person. Therefore you have to make it as measurable as possibleby converting concepts to variables. set operational - definitions for concepts Variable: An image, perception or concept that is measurable. ) Variables take on different values often expressed as numbers. ) Some variables are incapable to directly measure like feeling, preferences, values and sentiment. Thus, it may vary from person to person. Examples: satisfaction is not exactly easy to measure ) Age (years) Cue it's subjective ) Gender (male/female) ) Salary (in Dhs) ) Weight (in Kg) R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 4 / 22  Variables and Concepts Difference between concepts and variables Measurability is the main difference between a concept and a variable. Concepts cannot be measured (e.g. satisfaction has different meaning to different people) Variables can be measured (e.g. persons weight in kg) Concepts Variables Subjective impression Measurable though the degree No uniformity as to its of precision varies from scale to Understanding among scale and from variable to vari- different people able. (e.g. Attitude subjective, Can’t be measured Income- objective) Examples: Effectiveness, Examples: Gender, income, satisfaction, self-esteem, age, weight, price, etc. high achiever, etc. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 5 / 22  Variables and Concepts Converting concepts into variables If you use a concept in your study, you need to think of operationaliza- tion how it is measured. To operationalize, you first have to think of indicators which then can be converted into variables. Indicator is a set of criteria reflective of the concept. -bridge between - both - Concepts Indicators Variables ex · facial expressions show now a person Example: feels (concept of feeling Variables Concept Indicators Variables Working definition Rich/Poor 1. Income Total income per year Rich if income is > $200,000 2. Value of all assets Total value of;home, Rich if total value of cars, investments, etc. assets is > $2,000,000 R. Hijazi & M. Rahrouh Scientific ResearchMethodology kill me please 2020 6 / 22  Types of Variable Types of Variable Variables can be classified in a number of ways based on the causal rela- tionship, study design and unit of measurement as shown below. there's a relations isn't it ? Asked i peer - per they are exist ? R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 7 / 22  Types of Variable Viewpoint of causal relationships From a viewpoint of causal relationships In studies attempting to investigate a causal relationship or association may involve four types of variables: Independent variable (IV): the hours you study price ) A variable responsible for bringing changes in a phenomenon or a situa- tion. ) A phenomena that is manipulated by a researcher and is predicted to have an effect on other phenomena (Williams & Monge, 2001). ) Examples: A teaching method, a medical treatment, or training regimen. Dependent variable (DV): the grade/mark you get Demand ·) The outcome of the changes brought by an independent variable. ) * A phenomenon that is affected by the researcher’s manipulation of an- -Y other phenomena. ) ⑦ Examples: Achievement is the effect of a teaching method, cure or not the effect of a medical treatment, and higher skill level or not (achieve- ment) the effect of a training regimen. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 8 / 22  Types of Variable Viewpoint of causal relationships From a viewpoint of causal relationships not included in the model > - Extraneous variables: if I study most of these my results will be more precise ) Other variables, not measured in a study, may increase or decrease the magnitude or strength of the relationship betweenIV and DV. ) Example:When investigating the effect of television watching (IV) on achievement (DV), type of program is an extraneous variable. Intervening (mediating) variable: helpful when "direct" relationship the between A connecting or linking variable that links the IV and DV. This is an no ) situation where the relationship between IV and DV can’t be established without the intervention of another variable. ) Example:When studying the association between income andlongevity, access to medical careis an intervening variable. , In research the more of these I include the stronger the relationship , I should mention variables Intervening that extrenous variables weren't included in my ~ research model Income Independent Dependent - then access a intervening a then life spana Extraneous R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2125-849 2020 9 / 22  Types of Variable Viewpoint of causal relationships Examples not included in research R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 10 / 22  Types of Variable Viewpoint of causal relationships Examples Read R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 11 / 22  Types of Variable Viewpoint of causal relationships Examples Read main interest is IV & DV R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 12 / 22  Types of Variable Viewpoint of causal relationships Exercise this identify Vs #o -. decide I or ex List and label the variables in the following situations and illustrate by means of diagrams the relationship among the variables. A study suggested that elementary students who watch TV more than 3 hours aday are more likely to be overweight than students who watch less TV. People are demotivated to consume alcohol knowing the consequence that it damages the liver leads to liver cirrhosis. Perhaps behavioral therapy works better for malesand cognitive therapy worksbetter for females. Research suggests that children who eat hot breakfast at home perform better at school. Many argue that not only hot breakfast but also parental care of children before they go to school has an impact onchildren’s performance. Lucy examined relationships between middle-school students’ self-esteem and their performance in Mathematics. Her data analysis indicated that students with higher self-esteem perform better than those with lower self-esteem. Her investigation further revealed that students with higher self-esteem are more willing to invest effort in solving mathematics problems. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 13 / 22  Types of Variable Viewpoint of study design From a viewpoint of study design wasn't in class nur I study these by yourself In controlled experiments the independent (cause) variable may be intro- duced or manipulated either by the researcher or by someone else who is providing the service.In these situations there are two sets of variables. Attribute variables: ) Variables that cannot be manipulated, changed or controlled and that reflect the characteristics of a study population. ~ ) Examples: gender, age, level of motivation, nationality, education, etc. ~ Active variables: can be active if the study is about gender-changing ) Variables that can be manipulated, changed or controlled in a designed experiment. They are also called experimental variables. ) Examples: Teaching methods, temperature, product design, etc. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 14 / 22  Types of Variable Viewpoint of unit measurement From the viewpoint of unit measurement Quantitative variables ) Variables have values that represent quantities and can be classified as either discrete or continuous. (a) Discrete : have numerical values that arise from a counting process (mea- suring how many). For example, household size, number of sections, number of accidents, etc. can take & (b) Continuous : produce numerical responses that arise from a measuring any value process (measuring how much). For example, age, income, distance, etc. Qualitative (Categorical) variables ) Variables that have values that can only be placed into categories and can be classified as: much now (a) Dichotomous variable: has two categories, e.g. yes/no, male/female, precise you good/bad. Wanna be (b) Polytomous variable: has more than two categories, e.g. marital status: --- single, married, divorced, widowed. Note: the measurement of income in dirhams and fils is classified as the measurement of a quantitative variable, whereas its subjective mea- surement in categories ’low’, ’middle’ and ’high’ groups is a qualitative variable. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 15 / 22  Measurement Scales Types of measurement scales The way a variable is measured determines the type of analysis that can be performed, the statistical procedures that can be applied to the data, the way the data can be interpreted and the finding that can be communicated. There are four types of measurement scale: Nominal or classification scale Ordinal or ranking scale qualitative Interval scale Ratio scale quantitative The scales are defined based on whether a variable has the following four characteristics: classification, order, distance and origin. In practice, categorical or qualitative variables tend to be reported in nominal and ordinal scales while quantitative variables are reported in interval or ratio scales. Higher levels of measurement generally yield more information and are appropriate for morepowerful statistical analysis. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 16 / 22  Measurement Scales Measurement Scales: Nominal Scale A nominal scale enables classification of individuals, objects or re- sponses into categories based on a common or shared property or char- acteristic (No natural order between the categories). A nonnumeric label or numeric code may be used. If we use numerical symbols to identify categories, these numbers are recognized as labels only and have no quantitativevalue. The counting of members in each group is the only possible arithmetic operation when anominal scale is employed. Nominal scales are the least powerful of the four data types (no order or distance relationship and no arithmeticorigin). Examples: ) Gender (male, female) ) Marital status (single, married, divorced, widowed) ) Work sector (public, private) ) Get promoted (yes,no) R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 17 / 22  Measurement Scales Measurement Scales: Ordinal Scale Ordinal scale not only categorizes variables in such a way as to classify the various categories, it also rank-orders categories in some meaningful way. The use of an ordinal scale implies a statement of “greater than” or “less than”, without stating how much greater orless. Ordinal scales tell us relative order, but give us no information re- garding differences between the categories (Observations need not be equidistant). Examples: ) Job performance (excellent, good, fair, poor) both got an A ) Course grade (A, B+, B, C+, C, D+, D, F) ex> -. but one person got so ) Income level (low, medium, high) while other got 100 ) Satisfaction level (very dissatisfied, dissatisfied, neutral, satisfied, very satisfied) ) Education level (less than high school, high school, some college, college, postgraduate) R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 18 / 22  Measurement Scales Measurement Scales: Interval Scale The data have the properties of ordinal data, but only difference be- tween two observations is meaningful (the scaled distance between 1 and 2 equals the distance between 2 and 3). in ordinal distance may > - not be similar The zero point is arbitrary and does not mean the absence of the quantity that we are trying to measure. That is, there is no absolute zero or natural origin. Ratios are meaningless in this scale. I can't say I feel 50 % of the heat Researchers treat many attitude scales asinterval. Examples: EPA interval in is is ① doesn't mean "no marks" > - it's just a label ) Centigrade and Fahrenheit temperature scales: Note that 0 ◦ C means “cold,” not “no heat”; 40 ◦ C is not twice as warm as 20 ◦ C. starting point ↳ can be classified important is ) Calendar time ↑ here Differences are very imp - Note: Researchers treat many attitude scales (measured on Likert scale) asinterval. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 19 / 22  Measurement Scales Ratio Scale The ratio data have all the properties of interval data and the ratio of two values is meaningful. Ratio scale contains an absolute zero or origin that indicates that noth- ing exists for the variable at the zero point. One can use all mathematical operations on this scale. Ratio data represent the actual amounts of a variable. Examples: ) In business and finance: salary, profit, age, price, etc. ) In pharmacy: concentration, drug dose, etc. ) In IT: installation time, CPU speed, download time, etc. ) In general: age, height, weight, distance, etc. Because of the measurement precision at higher levels, more powerful and sensitive statistical procedures can be used. When we collect in- formation at higher levels, we can always covert, rescale, or reduce the data to arrive at a lower level. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 20 / 22  Measurement Scales Scales: Summary The nominal scale highlights the differences by classifying objects or persons into groups. The ordinal scale provides some additional info by rank-ordering the categories of the nominal scale. The interval scale, not only ranks, but also provides us with information on the magnitude of the differences in the variable. The ratio scale indicates not only the magnitude of the differences, but also the proportion. Characteristics zero absolute Scale Classification Order Distance Origin Nominal Yes No No No Ordinal Yes Yes No No Interval Yes Yes Yes No Ratio Yes Yes Yes Yes R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020 21 / 22  Measurement Scales Data Measurement Levels Ratio is highest & · R. Hijazi & M. Rahrouh Scientific ResearchMethodology 018 2 2 / 22  Measurement Scales Exercise Classify each of the following variables as either; qualitative or quantitative, active or attribute, and identify the level of measurement (nominal, ordinal, interval, ratio). 1- Prices on the stock market. Marital status, classified as “married” or “never married”. - Number of computers owned by ahousehold. Asking whether a patient is allergic to any medication. 5- Grades: A, B, C, D, or F. 6- Quality of medical care at a hospital. 7 Number of errors in a C++ program. - 8 - Grade point average from 0.0 to 4.0 in increments of 0.1 I- The number of hours you spent studying each day during the past week. The temperature in cities throughout UAE. 10The birth weights of babies who were born at Tawam Hospital last week. R. Hijazi & M. Rahrouh Scientific ResearchMethodology 2020