Practical Research Reviewer Q3 PDF

Practical Research Reviewer Q3 Lesson 1: Characteristics, Strengths, understand how prevalent it is by looking for projectable results for a weaknesses, and kinds of Quanti Research...

Practical Research Reviewer Q3 Lesson 1: Characteristics, Strengths, understand how prevalent it is by looking for projectable results for a weaknesses, and kinds of Quanti Research larger population. -​ Concerned with numbers and their Quantitative Qualitative relationship with events measurable behavior -​ Objective, systematic empirical investigation of observable statistical narrative phenomena through the use of objective Text-base computational techniques. intervention Unstructured observation -​ Highlights numerical analysis of data hoping that the numbers yield Experimental group inductive unbiased results that can be Tables and charts subjective generalized to some larger population and explain a particular deductive subjective observation generalizable Small sample Characteristics of Quantitative Research Research - systematic investigation and 1.​ Objective study of materials and sources to create - Accurate measurement and facts and new conclusions. analysis of target concepts - Not based on guesses 2 types: - Data are gathered before proposing Qualitative research conclusions or solutions -​ Expressed in words 2.​ Structured research instruments -​ Understand concepts, thoughts, or - Data are gathered using structured experiences research tools such as questionnaires -​ In-depth insights on topics that are to collect measurable characteristics not well-understood of the population -​ Ex: open-ended questions, 3.​ Clearly defined research questions observations described in words, - Researchers know what they are and literature reviews that explore looking for. concepts and theories - Questions are well defined for Quantitative research which objective answers are sought. -​ It is expressed in numbers and - The study is carefully designed. graphs 4.​ Numerical data -​ Used to test or confirm theories and - Data are in the form of numbers assumptions and statistics, organized using tables -​ Establish generalizable facts about a and charts to consolidate large topic numbers of data to show -​ Ex: experiments, observations relationships among variables. recorded as numbers, and surveys 5.​ Large sample sizes w/ closed-ended questions - Arrive at a more reliable data -​ Structured way of collecting and analysis, a normal population curve analyzing data obtained from is preferred. different sources (International - Large sample size depending on the Market Research, 2018) variety of characteristics a -​ Uses computational statistical and population has. 6.​ Replication mathematical tools to derive results - Study can be repeated to verify or -​ Conclusive in its purpose as it tries confirm the correctness of the to quantify the problem and results in other settings which Practical Research Reviewer Q3 strengthens the validity of the findings eliminating spurious conclusions. 7.​ Future outcomes - Complex mathematical calculations and with the aid of computers, if-then scenarios may be formulated thus predicting future results Experimental Lesson 2: Strengths and Weaknesses -​ The researcher manipulates of Quantitative Research variables to identify casual relationships or the degree of Strengths:​ effectiveness of an intervention 1. Numerical data and large sample size allows quantitative research to come up ​ True-Experimental with objective and reliable results.​ -​ Employs experimental and 2. The use of statistical tools allows control setups that are quantitative research to analyze, present, assigned randomly to test the and interpret large sample sizes easily.​ effectiveness of intervention 3. A well-structured and well-defined with a well-established quantitative research limits external sample selection process variables that influence biases.​ ​ Quasi-Experimental 4. Large sample size conclusions that can be -​ Establish cause-and-effect used to generalize the entire population.​ relationship of variables and 5. Quantitative studies are replicable. have a control group, no ​ random pre-selection Weakness:​ processes 1. A large sample size is needed to establish ​ Pre-Experimental reliable generalization.​ -​ The simplest form of research 2. Reproduction of research instruments design, no control group or covering large sample sizes is expensive.​ comparison group is 3. Numerical data obtained often are employed superficial as contextual data are often neglected.​ 4. Sensitive issues and information are difficult to gather using structured research instruments.​ 5. Numerical data obtained often are incomplete and respondents may guess and not respond seriously and honestly ​ Lesson 3: Kinds of Quantitative Non-Experimental Research Design -​ Observe the perception of respondents about certain Research Design phenomena as they occur naturally, -​ It is the overall strategy that the this means no interference from the researcher chooses to integrate the researcher. different components of the study coherently and logically. ​ Correlational Practical Research Reviewer Q3 -​ aims to establish correlation Let's say a school tries a new and relationship among way of teaching math. To variables being studied. study the impact ex-post -​ Bivariate Correlational Study facto, they wouldn't force gathers 2 data from 2 some kids to learn the old way variables from one subject and others the new way. and establishes their Instead, they'd look at the correlation. (Example: Hours students' test scores after the studied vs. test score) new method was already -​ Prediction Study used. They might compare utilizes the predictor variable these scores to past test scores (one variable predicts ( from before the new method) another) to predict the or to the scores of students at criterion variable. (Example: a different school who didn't SAT scores predict college use the new method. They're GPA) looking back at what already happened (the test scores after ​ Survey the new teaching method) to -​ used in gathering data from try to figure out if the new large group of population method made a difference. which is used to identify the They're not controlling who general perception of the got the new method; they're population as it offers a analyzing the results after the general picture of how large fact) population perceived certain ​ Normative phenomena. (Example: -​ describes the norm level Surveying students about (what’s “normal” for a their favorite subjects) group) of certain attributes ​ Comparative for a given behavior as -​ compares and contrasts two observed by the population. populations considering as to (Example: Studying the how they perceive, assess, or average reading ability of view certain variable or 10-year-olds) basically just see how they ​ Methodological differ. (Example: Comparing -​ utilizes different approaches the study habits of students and methodologies in in two different schools) establishing scale-matched ​ Ex-post Facto approaches whereas data -​ also known as obtained from across Causal-Comparative disciplines can be integrated. -​ utilizes past observations and In other words, combines conclusions in deriving different research methods generalizations and to get a more complete predictions to explain why understanding (Example: A and how certain scenario or researcher might use phenomena happens. surveys, interviews, and (Example: Studying the experiments to study the impact of a new teaching effectiveness of a new method by comparing teaching method) students' test scores before ​ Evaluative and after its implementation: Practical Research Reviewer Q3 -​ aims to assess the conduct, - When you collect quantitative data, the progress, implementation and numbers you record represent REAL processes involved in the AMOUNTS that can be added, subtracted, implementation of certain divided, etc.​ program, event, or activity. - Can be Discrete or Continuous​ (Example: A school might ​ evaluate its new after-school Quantitative: Discrete​ program by looking at - counts of individual items or values in a student participation rates, finite amount of time​ grades, and feedback from ​ parents and students) Examples:​ - Number of students in a class​ Lesson 4: Variables in Research, - Number of different tree species in a forest​ Quantitative and Categorical Variables; ​ Interval, Ratio, Nominal, Ordinal Variables Quantitative: Continuous​ ​ - can take an infinite value and can be In quantitative study RESEARCHERS CAN: ​ divided into smaller increments​ - measure and describe a variable​ - cannot be counted​ - determine relationship between variables​ - can be Interval or Ratio - examine differences among groups​ ​ - experiment (cause and effect)​ Quantitative: Continuous: Interval​ ​ - measures the difference in measurement of Research Variables​ values and provides interpretation based on - Variables are elements, attributes, the difference​ characteristics, categories and values which - NO TRUE ZERO​ are being considered, measured, given ​ value and often times manipulated in Example:​ conducting research.​ - Temperature in Celcius and Farenheit​ ​ (In Celsius, 0oC means the freezing point of Data​ water. In Fahrenheit, 0oF means the - Data is a specific measurement of a freezing temperature of a solution of brine.​ variable. It is the value you record in your This means that 0 represents a value. In data sheet.​ short, there can be negative values)​ ​ ​ Data is generally divided into two Quantitative: Continuous: Ratio​ categories:​ - takes the values and measurements which - Quantitative data represents AMOUNTS​ has an ABSOLUTE ZERO VALUE​ - Categorical data represents GROUPINGS​ ​ ​ Examples:​ - Age, Height, Volume Distance​ (0 means 0, A negative value is impossible. Only zero and positive numbers.)​ ​ Categorical Variables​ - also known as qualitative variables which represent groupings of some kind​ ​ - sometimes recorded as numbers, but the ​ numbers represent categories rather than ​ actual amounts of things.​ Quantitative Variables​ - can be Nominal or Ordinal​ Practical Research Reviewer Q3 ​ - amount of salt you add to the water​ Categorical: Nominal​ - the species of plants being studied​ - cannot be arranged in order​ - variables related to plant health like growth - doesn’t take a numerical values or and wilting.​ ​ measurement​ ​ - can be Dichotomous or Polytomous​ ​ ​ 1. Amount of Salt​ Examples:​ I. Is the variable a category or label? (C or N)​ - Sex, Eye Color, Religion, Brands​ - No (It’s measurable amount, Numerical)​ - Proceed to Question IV (Numerical Question)​ ​ ​ Categorical: Nominal: Dichotomous​ IV. Can the value of the variable take decimals, - can take on exactly two values​ or is it countable in whole units only? (N)​ Ex. Sex (Male and Female)​ - Take Decimals ​ (grams, milliliters, teaspoons, Continuous)​ Categorical: Nominal: Polytomous​ - Proceed to Question V (Numerical Question)​ - with more than two possible values​ ​ Ex. Blood Type (A, AB, B, O)​ V. Does zero represent the absence of the ​ characteristic being measured? (N)​ Categorical: Ordinal​ - Yes (Zero means no amount of salt, Ratio)​ ​ - can be arranged in order or rank either Therefore, the amount of salt is a continuous from highest to lowest or from smallest to ratio.​ largest​ ​ ​ 2. Species of Plants​ I. Is the variable a category or label? (C or N)​ Examples:​ - Yes (Category and Label, Categorical)​ - rating scale in survey​ - Proceed to Question II (Categorical - finishing place in a race Question)​ ​ II. Can the categories be ordered or ranked? (C)​ Worksheet: Sample Problems - No (Nominal)​ - Proceed to Question III (Categorical ​ Question)​ 5-Questions framework to identify the ​ variables. ​ III. Is the variable composed of only two ​ categories or more than two categories? (C)​ (Exclusively prepared by 11-Volt ^^)​ - Multiple Categories ​ ​ (Rose, Tulip, Daisy, Polytomous)​ ​ Acronyms​ Therefore, the species of plants is a nominal C - Categorical​ polytomous.​ N - Numerical​ ​ ​ 3. Growth of plants​ I. Is the variable a category or label (C or N)​ I. Is the variable a category or label? (C or N)​ II. Can the categories be ordered or ranked? (C)​ - No (Measurable)​ III. Is the variable composed of only two - Proceed to Question IV​ ​ categories or more than two categories (C)​ IV. Can the value of the variable take decimals, IV. Can the value of the variable take decimals, or is it countable in whole units only? (N)​ or is it countable in whole units only? (N)​ - Take Decimals (Continuous)​ V. Does zero represent the absence of the - Proceed to Question V​ characteristic being measured? (N)​ ​ ​ V. Does zero represent the absence of the Sample Problem​ characteristic being measured? (N)​ - Yes (0 means no height, Ratio)​ Test whether some plant species are more ​ salt-tolerant than others​ Therefore, the growth of plants is continuous ​ ratio.​ Variables:​ ​ Practical Research Reviewer Q3 ​ 4. Education Level of Survey Respondents Worksheet: Sample Problems Respondents are asked about their highest level ​ of education (e.g., High School, Bachelor's, 1. Plant Species in a Garden Master's, PhD). A study is done on a garden with different plant ​ I. Is the variable a category or label (C or species, including Roses, Tulips, and Daisies. N)? ​ II. Can the categories be ordered or ​ I. Is the variable a category or label (C or ranked? (C) N)? ​ III. Is the variable composed of only two ​ II. Can the categories be ordered or categories or more than two categories ranked? (C) (C)? ​ III. Is the variable composed of only two ​ IV. Can the value of the variable take categories or more than two categories decimals, or is it countable in whole (C)? units only? (N) ​ IV. Can the value of the variable take ​ V. Does zero represent the absence of decimals, or is it countable in whole the characteristic being measured? (N) units only? (N) ​ V. Does zero represent the absence of the characteristic being measured? (N) 5. Weight of People in a Fitness Study A study records the weight of people (in 2. Temperature in Celsius kilograms). A study measures the temperature in Celsius ​ I. Is the variable a category or label (C or every hour. N)? ​ II. Can the categories be ordered or ​ I. Is the variable a category or label (C or ranked? (C) N)? ​ III. Is the variable composed of only two ​ II. Can the categories be ordered or categories or more than two categories ranked? (C) (C)? ​ III. Is the variable composed of only two ​ IV. Can the value of the variable take categories or more than two categories decimals, or is it countable in whole (C)? units only? (N) ​ IV. Can the value of the variable take ​ V. Does zero represent the absence of decimals, or is it countable in whole the characteristic being measured? (N) units only? (N) ​ V. Does zero represent the absence of the characteristic being measured? (N) 6. Number of Children in a Household The number of children in a household is 3. Number of Cars in a Parking Lot recorded. The number of cars in a parking lot is counted. ​ I. Is the variable a category or label (C or N)? ​ I. Is the variable a category or label (C or ​ II. Can the categories be ordered or N)? ranked? (C) ​ II. Can the categories be ordered or ​ III. Is the variable composed of only two ranked? (C) categories or more than two categories ​ III. Is the variable composed of only two (C)? categories or more than two categories ​ IV. Can the value of the variable take (C)? decimals, or is it countable in whole ​ IV. Can the value of the variable take units only? (N) decimals, or is it countable in whole ​ V. Does zero represent the absence of units only? (N) the characteristic being measured? (N) ​ V. Does zero represent the absence of the characteristic being measured? (N) ​ ​ ​ Practical Research Reviewer Q3 ​ Worksheet: Answer Keys 1. Plant Species in a Garden ​ I. Yes, it's a category or label (C). ​ II. No, the categories (Rose, Tulip, Daisy) cannot be ranked. ​ III. More than two categories (Polytomous). ​ Answer: Nominal-Polytomous. 2. Temperature in Celsius ​ I. No, it’s a measurable value (N). ​ IV. Yes, it can take decimals (N). ​ V. No, zero does not represent the absence of temperature (Celsius has a negative range). ​ Answer: Continuous-Interval. 3. Number of Cars in a Parking Lot ​ I. No, it’s a countable quantity (N). ​ IV. It cannot take decimals (N). ​ Answer: Discrete. 4. Education Level of Survey Respondents ​ I. Yes, it’s a category or label (C). ​ II. Yes, the categories are ordered (e.g., High School < Bachelor's < Master's < PhD). ​ Answer: Ordinal. 5. Weight of People in a Fitness Study ​ I. No, it’s a measurable value (N). ​ IV. Yes, it can take decimals (N). ​ V. Zero represents the absence of weight (N). ​ Answer: Continuous-Ratio. 6. Number of Children in a Household ​ I. No, it’s a countable value (N). ​ IV. It can’t take decimals (N). ​ Answer: Discrete.