Media Information Literacy, Study notes of Philosophy

Download Media Information Literacy and more Study notes Philosophy in PDF only on Docsity! PRACTICAL RESEARCH 2 HANDOUTS Name: ________________________________________ Grade & Section: ____________ Semester: _____________ Quarter: __________________ INQUIRY VS RESEARCH The most important element of inquiry is asking questions, exploring answers or solutions, tackling problems, and sharing the answers in the most fitting form. PRACTICAL RESEARCH 2 HANDOUTS Name: ________________________________________ Grade & Section: ____________ Semester: _____________ Quarter: __________________ CHARACTERISTCIS, STRENGTHS, AND WEAKNESSES OF QUANTITATIVE RESEARCH Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions. Quantitative research Qualitative Research Focuses on testing theories and hypotheses Analyzed through math and statistical analysis Mainly expressed in numbers, graphs and tables Requires many respondents Closed (multiple choice) questions Key terms: testing, measurement, objectivity, replicability Focuses on exploring ideas and formulating a theory or hypothesis Analyzed by summarizing, categorizing and interpreting Mainly expressed in words Requires few respondents Open-ended questions Key terms: understanding, context, complexity, subjectivity Kinds of Quantitative Research Design Descriptive is used to describe a particular phenomenon by observing it as it occurs in nature. There is no experimental manipulation and the researcher does not start with a hypothesis. The goal of descriptive research is only to describe the person or object of th~ study. aie Me CTC re eel the different kinds of physical activities and how often high school students do it during the quarantine period.” Correlational identifies the relationship between variables. Data is collected by observation since it does not consider the cause and effect for example, the relationship between the amount of physical activity done and student academic achievemer”. 1S Decl teats) | teenagers’ sense of humor with positive psychological capacity PRACTICAL RESEARCH 2 HANDOUTS Name: ________________________________________ Grade & Section: ____________ Semester: _____________ Quarter: __________________ KINDS OF VARIABLES AND THEIR USES What is a variable?  The root of the word variable is related to the word “vary,” which should help us understand what variables might be.   Variables are things you measure, manipulate and control in statistics and research.  A variable's value can change between groups or over time.  Variables are properties, or characteristics of some event, object, or person that can be assigned with different values or amounts.  Variables are often manipulated or controlled. Types of Variables: Demographic Variables. Social workers are often interested in what we call demographic variables. Demographic variables are used to describe characteristics of a population, group, or sample of the population. Examples of frequently applied demographic variables are  age,  ethnicity,  national origin,  religious affiliation,  gender,  sexual orientation,  marital/relationship status,  employment status,  political affiliation,  geographical location,  education level, and  income. Independent Variable. Independent variable is hypothesized to affect the dependent variable. It is what the researcher manipulates to see if it changes the dependent variable. An independent variable is a singular characteristic that the other variables in your experiment cannot change. Dependent Variable. A dependent variable relies on and can be changed by other components. It is the variable that changes as a result of an intervention or experiment. Independent variables can influence dependent variables, but dependent variables cannot influence independent variables. Intervening Variable. An intervening variable, sometimes called a mediating or mediator variable, is a theoretical variable the researcher uses to explain a cause or connection between other study variables —usually dependent and independent ones. It links or bridges the gap between the independent and dependent variables. Extraneous Variables. Extraneous variables are factors that affect the dependent variable but that the researcher did not originally consider when designing the experiment. These unwanted variables can unintentionally change a study's results or how a researcher interprets those results. Extraneous variables should be controlled because they can offer an alternative explanation of the dependent variable. Quantitative Variable. Quantitative variables are any data sets that involve numbers or amounts. Examples might include height, distance or number of items. Researchers can further categorize quantitative variables into two types: 1. Discrete Variables – are variables that assumes a distinct or discrete value on a scale Ex.) number of puppies, number of children in a household 2. Continuous Variables – are variables that assumes a continuous point on a scale Ex. ) height, weight, average daily temperature, volume Qualitative Variable. Qualitative, or categorical, variables are non-numerical values or groupings. Examples might include eye or hair color. Researchers can further categorize qualitative variables into three types: 1. Binary: Variables with only two categories, such as male or female, red or blue. 2. Nominal: Variables you can organize in more than two categories that do not follow a particular order. Take, for example, housing types: Single-family home, condominium, tiny home. 3. Ordinal: Variables you can organize in more than two categories that follow a particular order. Take, for example, level of satisfaction: Unsatisfied, neutral, satisfied. Confounding Variable. A confounding variable is one you did not account for that can disguise another variable's effects. Confounding variables can invalidate your experiment results by making them biased or suggesting a relationship between variables exists when it does not. For example, if you are studying the relationship between exercise level (independent variable) and body mass index (dependent variable) but do not consider age's effect on these factors, it becomes a confounding variable that changes your results. What are the four levels of measurement? 1. Nominal measurement Nominal measurement categorizes data without the use of numeric values. When you evaluate data using nominal measurement, you don't have a specific order of values and can't add, subtract, multiply or divide this type of data. For example, if you're evaluating different groups of marketing data, you might label these categories as "Geographic location," "Search term frequency" and other labels that categorize your marketing data with no specific order. The data doesn't have a particular order and there is no calculation you can apply to the data. 2. Ordinal measurement In ordinal measurement, you can categorize data that appear to have a set order. The ordinal level of measurement uses a specific order to rank data, such as from least to greatest value or first to fifth place. Financial analysis often relies on ordinal measurement to place certain data in various specific orders. For instance, businesses can measure sales numbers and